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https://devpost.com/software/2maway

2mAway logo Inspiration We have been staying home for the last two months. I know it is hard for some of us because there are some times we have to go out. However, how can we know if it is going to be safe out there or not? Our Project helps people to feel secure every time they want to go out, not only during this time. What it does 2MAway is a website help user to stay safe during this challenging time by: Track people, you exposed to Provide services to report your health status Track location you intend to go to to see if it safe Visit our website here How I built it We use Firebase as our database, and we also integrate Google-Maps-API into our Project. We track the location of the user in our website and measure the distance between users We let the users know if they have contacted (less than 2 meters) with the person who reported to be Corona infected. We measure the number of people in an area that user choose to alert about the crowd status Challenges I ran into There were some issues behind the behind to calculate the distance and keep it up to real-time data that make us struggles a bit. However, we manage to make the back-end fully functional. Secondly, This is the first time we exposed to JavaScript. Both of us did not have any experience with JavaScript before. We learned the language and did the project at the same time. Potential Development Our Project will not only be limited to this pandemic time only. During normal days, when a user wants to go shopping, they can absolutely use our website to check the location because it is crucial to keep a safe distance with other people. Moreover, it will allow us to check the density of people at the given destination to serve different public purposes such as avoiding traffic jams, time-consuming shopping, ... What's next for 2MAway For this application, we hope that we will be able to extend the version of the app to wider uses such as check-in by location, avoid traffic jams by looking at the density of people on the road, make full potential use of shopping to avoid waiting,... Furthermore, we can make more features that will allow users to use the web application more efficiently. Built With css3 firebase google-maps html5 javascript Try it out github.com 2maway.tech

https://devpost.com/software/conqueryourspace

Logo The app works for strangely shaped squares as well, such as this plaza in Italy. We account for the presence of barriers placed at the perimeter of the space, as well as obstacles in the space itself. The largest square in Europe! This takes approx 20 seconds to be generated, but it's a lot of people! All 2m apart at minimum. What inspired us In the "new" normality we are going to live in for the foreseeable future, we are in dire need of getting back our public spaces from COVID. We want to repopulate our plazas, start organising again events and gatherings, and attend to markets and fairs. In essence, we need to get back to public spaces for the immeasurable social value they represent. But... we need to do it in a safe, regulated manner. We need to respect social distancing. As physicists, we asked yourself: can we build something that can provide a solid, reliable estimate of a public space capacity, when taking into account social distancing measures? Can we build it fast? And would people be interested in it? And one hour later, we started this project: ConquerYourSpace! What it does ConquerYourSpace is a web-app that estimates the number of people that can fit into a public space. It's very simple: Look for your space of interest (a square, a park) in the map Draw the perimeter of the space Add obstacles and/or barriers on the perimeter Set the MINIMUM social distance you'd like to be observed Press the button and enjoy! ConquerYourSpace will estimate the number of people that can fit in the space, using a physics concept known as Random Packing. It accounts for the "stochastic" nature of people, so it truly is one of the best way to provide a guideline for crowd control! How we built it One of us pitched the idea to a number of local artisans. They have been severely affected by COVID in their business, and they absolutely loved it -- they truly saw it as the way to get back to their foot as fast as possible, and start organising again local markets and events to launch their business again. So, we first prototyped the physics model behind the idea. Then, using Wolfram Mathematica, we started applying it to squares and parks around the world. We have an arXiv preprint based on this: check it out! https://arxiv.org/abs/2005.07038 Then we started thinking about how to make it accessible to everyone. So, we signed in for the hackathon, assembled a ragtag team of developers and students and, with the help of the artisans in the team, who provided feedback and ideas, we built our prototype app. We used Python in the backend, Javascript, Node.js and CSS in the frontend, and we deployed it as a React app on the cloud. Challenges we ran into One of the first thinks you'll notice is... The app only works for Europe so far :( The reason is essentially time -- we tested it extensively on European squares and parks but when we tried outside Europe we found out our geo-localization method was not appropriate. However, changing it was, unfortunately, challenging. Something we definitely did not expect. We are very sorry for it! Another challenge we faced is calculation speed. There is a lot of number crunching behind it. While we could implement the physical model relatively painlessly, making it so that the calculation would be "almost" real time for a user of the app has been very challenging. Luckily, we managed to solve that at the end! Finally, it was relatively hard to agree on the "best" user interface. While the concept is simple, we could not satisfactorily find a way to present the app to the user with all the functionality, but in the simplest way possible. Shall we allow the user to draw the plaza shape? Shall we use predefined polygons? How should we design the buttons and such? These challenges were absent when we prototyped the physical model, but took us a lot of time when developing the app. Accomplishments that we're proud of We are really proud of the feedback we have received so far. While we were kind of expecting praising from artisans and public event organisers, what we loved was people reaching us to implement it for indoor spaces as well, such as offices and university laboratories. This made us realise that this idea could really make an impact across all societal levels for regaining working and social normality during the "new" normality, not only in the public but also in the private. We also showed the app to professors and academics. What we did not expect is that they all backed us! Yes, implementation is simplistic and yes, a lot could be added. But they all loved how far a simple physical idea could be translated to tackle a societal issue such as this. We are very proud of their feedback. We are also really proud of what we achieved as a team in, essentially, a weekend. We "clicked" so well and engaged so much, that we achieved what we thought it would require us more than a week. And we loved the experience, so much that we plan to keep working on it as a possible start up! What we learned We learnt a lot from all the other team members, all with different backgrounds. We learnt from the model developers that everything can start from a simple idea. We learnt from the backend developers that robustness and speed of the implementation are of utmost importance, no matter how solid the theory behind it is. We learnt from the frontend developers that a beautiful interface makes the difference between an app which is impossible to use and an app you can have fun using. And we learnt from our artisan "stakeholders" that none of this matters if they cannot use it! Overall, we really learnt a lot about project development, from beginning to end. This was a very inspiring and precious lesson for all the people in the team. What's next for ConquerYourSpace We plan to add a lot of things in the near future. To start with, we would like to expand this idea to be used in indoor spaces as well; this is our top priority. Then, we plan to add the option of specifying "escape" routes. We would also like to add the option of simulating the presence of couples, alongside individuals. Finally, we would like to start implementing a simple simulation of crowd dynamics to make it more realistic. All in all, these are our initial bullet points, but in essence we are really thinking to "scale" it up. However, the first step in absolute is that... the app should be used by as many people as possible. This will provide us the feedback and the suggestions for implementations and improvements, as well as the momentum to get this project to fly. We hope this is going to happen in the next immediate weeks, and we are really looking forward to it! Built With google-maps javascript node.js python react Try it out ec2co-ecsel-1374rr8nsrhuo-139205145.eu-central-1.elb.amazonaws.com github.com

https://devpost.com/software/a-c-c-t-s-automated-comprehensive-contact-tracing-system

window.fbAsyncInit = function() { FB.init({ appId : 115745995110194, xfbml : true, version : 'v3.3' }); // Get Embedded Video Player API Instance FB.Event.subscribe('xfbml.ready', function(msg) { if (msg.type === 'video') { // force a resize of the carousel setTimeout( function() { $('[data-slick]').slick("setPosition") }, 2500 ) } }); }; (function (d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = "https://connect.facebook.net/en_US/sdk.js"; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); This is an example of the data stored in the data base. This is what will be shown if Jhulian Batul (Tested Positive) was searched. Cellphone Message that you will receive once the system had been updated with a positive patient you've been in contact with. Cellphone Message that you will receive once the system had been updated with a positive patient you've been in contact with. Scan this and your entry will be recorded on https://docs.google.com/spreadsheets/d/1yZVPnMnBQh2Wtf5TIyktppOHUj5VrV-bwgB_60YWo0o/edit#gid=0 Scan this and your exit will be recorded on https://docs.google.com/spreadsheets/d/10XQftHvqN88Gz_4ASJKf0y9BIJYDUCt2gN5DkzbxmXU/edit#gid=0 This is the basic flowchart of the database. This is what it looks like in the system made. Fillup Inspiration A lot of people here in the Philippines do no have food anymore. A lot of people have become unemployed. We can't stand to see people having anything to eat. With that said, we had thought of a way in order to flatten the curve effectively which wouldn't cost anything since we would be using QR codes and the system database is based online. This way, the third world-countries will also have a way to flatten the curve even if they do not have advanced infrastructures. We want to solve the pandemic as a whole so we can all get back to our normal lives. What it does A.C.C.T.S Automated Comprehensive Contact Tracing System How does it Work? ENTRY SYSTEM Each establishment will be equipped with a smartphone or any type of scanner that can be bought at a low cost that has the ability to read QR code or bar code. This can be done for free using a smartphone app and using the smartphone as a scanner. The data will then be stored in a database wherein it could be accessed. This means that it will be possible to determine when and where a person was at a particular time and who did he have in contact with at that certain time. ID SYSTEM Every person will have an ID. There will be two types of IDs for flexibility. The proposed ID will contain basic information including family members, name, age, address, and contact number. The first type of ID will just be a QR code or bar code that could be saved as an image on the phone. Everyone doesn’t have smartphones and so they can be given a laminated copy of a printed picture of their QR code or bar code. This approach was chosen because little to no money will be spent on the ID. SEARCH SYSTEM All of the entry and exit data of every person in stores within the city will be stored in the database that could be accessed by the system. For example, Jhulian went to Sm Hypermarket from 3 pm-4 pm, Dwight went there from 3:30 pm - 4:30 pm and Lance went there from 4:pm-5 pm. Let’s say that Jhulian was tested the next day and it turned out that he was COVID-19 positive. The database will then be updated with his status as positive. Once the name Jhulian Batul was searched on the system, it will show everyone that had been in the same place as him as well at the same time. In short, Jhulian was in the same place as Dwight. That means Dwight would then be a PUI. However, Dwight also interacted with Lance. Lance did not interact with Jhulo but he interacted with Dwight who is now a PUI. Although there is a low probability, there is still a chance that Lance might have been infected. This is where the probability system comes in. PROBABILITY SYSTEM There will be a scale that will determine the degree of possibility that someone had been infected. This will include very high, high, low, mild, very mild. The terms first contact, second contact, third contact, and so on will be used for explanation to avoid confusion. In this case, Dwight is a first-contact, while Lance is a second-contact. In the system, Dwight’s possibility status will be labeled “very high” and Lance will be labeled as “high”. Those who were in the same place and time as Lance who did not come in contact with the COVID-carrier will then be labeled low. Why is this important? The system will help health professionals determine who must be tested first and who is the top priority to the least. The targeted testing becomes more systematic and in this way, we will be able to save test kits and be able to reach more that has very high chances of being positive. SMS SYSTEM Going back to the example, once the status of Jhulo had been updated to positive, the built system will automatically message the cellphone number of everyone who had been at the same place and time with him. This will include the first contact up to the fifth-contact. They will be immediately messaged that they should observe home quarantine since they are now a PUI. Their data will automatically be sent to the local government unit as a PUI. It is possible to message them since the QR code that was made contains their information including cellphone number and address. SIGNIFICANCE This system will be able to effectively trace everyone who might have been infected with COVID and is symptomatic. In a maximum of 3 weeks, the curve can be effectively flattened in each city if this is to be adapted. It also has the capability of preventing a second and third wave. What’s more amazing about this is that it becomes a preventive measure for future outbreaks or pandemic. Once this had become adapted on a national level, it would even protect us if ever a pandemic occurs again and an infected person from another country would have traveled to ours. COSTING The system will only cost little to nothing. This is because it utilizes QR codes which could either be printed or saved as an image on the phone. The establishments, on the other hand, can use their phones to scan the QR wherein the data collected would be saved in the online database. How we built it For the entry/exit system we had used IFTTT. We used a webhook and turned it into a QR trigger. Through that, every time that the QR had been scanned, the data attached to it will automatically be added to the database. This is also helpful because establishments won't need to buy scanners and can use their phones for scanning. For the application and web dev, we used Android Studio and VsCode. Challenges we ran into The only challenge we had was time. This is because the telecommunication signals are weak and that makes it hard to communicate with the team members. We also discovered the hackathon just yesterday so we only had 26 hours to do the system. We were not able to integrate the SMS system because we didn't have much time left. We wish we had more time to polish the system since we just joined one day ago. Accomplishments that we're proud of We had already reached out to government officials. This system will be able to help third world countries with limited budgets and finish contact tracing within a month if implemented. Previous Accomplishments of the team: 2 International Gold Medal Science Fair 2 International Bronze Medal Science Fair 2 National Student Scientists Medal 1 World Research Conference Invitee (Abstract Paper Entry) 1 National Student Research Conference Invitee (Abstract Paper Entry) 1 National Business Innovation Award 1 National Business Innovation Finalist 1 Regional Science Fair 1 Judge at International Robothon Competition (Southeast Asia) 1 3rd Place Holy Angel University and SunMoon University Autonomous Car Design(International Adventure Design) Finalists at AnimoLabs 1 2nd Place Holy Angel University and SunMoon University Autonomous Car Design(International Adventure Design) What we learned We had learned a lot of shortcuts that can be used in this hackathon. We had also learned a variety of new skills. What's next for A.C.C.T.S (Automated Comprehensive Contact Tracing System) We have contacted the local government, looking to implement it. Once it works well, we will publish it as a paper so that it can be a preventive measure that can be adapted by the world. It has the capability to end the first wave in less than a month, prevent a second and third wave. It is also good not just for first-world countries but works really well with third world countries since it won't cost that much. Built With android-studio database ifttt vscode webdev

https://devpost.com/software/crisis-response-mapping-4dwvch

Data map showing cases as well as health policies in each state Chart displaying average new daily cases per 1 million for each policy Sample data table showing policies implemented in each state Crisis Response Mapping Message Provide Clarity, Prevent Confusion, and Proceed Forward Background The United States of America has been combating the COVID-19 pandemic for months. With this crisis, new policies and procedures have been enacted to help slow the spread of the virus. This site was built at during COVID HealthHack 1 and originally tasked to track the spread of the disease and the emerging policies to follow. But because the US plans on reopening in the near future, the task of the site was broadened to not only show the trends of the virus spread between the states but also how policies implemented within each state affected the trends of the disease. Objective The essence of our project is to provide a better, dynamic map and trends dashboard for the spread of the virus, as well as the policies enacted for preventative measures. Our goal is to provide clarity and awareness to the ongoing pandemic as the focus shifts to reopening. Ultimately, we aim to assist policymakers, as well as the public, in what is being done to stop the pandemic. Target Audience Policymakers - Create a tool they can use to see other state's policies and procedures, and how well those states are doing in terms of infection Citizens - An accessible database to see how their state is fairing against the virus, as well as what policies the state has enacted to protect them. How We Built It For this site we used the python Flask micro web framework as the backbone because it is lightweight and easy to use, perfect for our website and hackathons in general. The site itself is built with vanilla HTML, CSS, and JavaScript with most of the heavy lifting happening behind the scenes in Python. In order to use the KFF spreadsheet database we used the google sheets API and to use JHU's Github csv repo database we used the python Pandas module. The data is then processed and displayed on the website using the google maps and google sheets API's. The site is hosted using Heroku and Gunicorn. Challenges We Ran Into We ran into challenges in terms of skillset and utilization of git but overcame that by persistence and learning from web sources. What We Learned With this project, we learned how to use Google APIs and furthered our programming skills. The project also revealed how rewarding it is to work on a project that matters and that can help people during this difficult time. What's Next for Crisis Response Mapping We plan on keeping the website up to date and to improve the site through user input. The repo is completely open to the public so any and all pull requests or suggestions are greatly appreciated. Built With beautiful-soup css flask git google-chart google-maps google-spreadsheets heroku html javascript python requests Try it out covidpolicies.herokuapp.com github.com

https://devpost.com/software/cleanse-y9uikg

Here is Cleanse in the context of a bathroom. Here is Cleanse in the context where a bathroom is not available (e.g. at supermarkets). The group as a collective felt that it was necessary to contribute in the fight against COVID-19 and we thus decided to come up with a solution which will limit the spread of the disease. After several brainstorming sessions and thorough discussions, we eventually came up with Cleanse. Cleanse is a hygiene compliance software that cultivates healthy hand hygiene habits amongst front line workers & essential workers (e.g. restaurant/grocery workers) through proper guidance and reminders.Through this, we aim to improve and raise awareness about the importance of hand washing, especially in this time of crisis, where the disease is spreading like wildfire. The Cleanse prototype utilizes multiple machine learning algorithms and models to track and guide users through various handwashing actions. We created a custom data set by capturing and feeding images of the correct hand poses for the 7 different handwashing steps. These captured data are collected and normalized to allow the model to recognize variations in hand sizes. The data is then fed into a neural network where we trained the model before deployment. Through bluetooth, the micro bit receives signals through the cloud, communicating with and activating the lighting system, signaling to users when each step is completed. Through this project, we learned to use different libraries and frameworks like p5js, ml5, tensor flow, mediapipe and the microbit. One of the biggest difficulties that we faced was trying to train an accurate hand washing model for Cleanse. We had to take special care of various angles and hand sizes during the data collection stage which could affect the accuracy of the results. With Cleanse, we hope to empower these frontline workers with the necessary knowledge and technology, to protect them against the potential threats of COVID-19 as first responders in this pandemic. Built With css figma html javascript mediapipe ml5.js p5.js tensorflow.js Try it out tinyurl.com github.com

https://devpost.com/software/reshape

Main Screen Kitchen Listing Page Kitchen Listing Page with Options Empty Floor Plan Adding New Reservation Social Distanced Seating Inspiration For the past 4 years as students of Stevens Institute of Technology, we’ve relied heavily on the independent businesses that make Hoboken feel like home. They’ve provided us with not only food and services, but places to study, conduct business, and build relationships. Due to the coronavirus pandemic, many local businesses are facing struggles that don’t just affect their patrons, they affect almost half of the American workforce. According to the U.S. Small Business Association, 47.3% of the American workforce is employed by small businesses, nearly 60 million people. We’ve strongly felt the absence of these Hoboken businesses, and we wanted to develop a solution to help the businesses we love reopen, and stay open. What it does ReShape is a dynamic, two-part platform for small business owners to collaborate, communicate, and optimize their business while remaining compliant with social distancing regulations. One half of our solution is an e-Marketplace dedicated to facilitating the collaborative spirit of local Hoboken businesses. On our platform, business-owners can offer and request resources that benefit one another. For example, businesses can offer physical space such as kitchen, storage, or floor space in return for a set price, profit sharing, or any other agreed upon terms. ReShape’s e-Marketplace platform is adaptable to the needs of local organizations and facilitates the communication between Hoboken business owners. The other half of ReShape is a tool, tailored to restaurants with dine-in services. The tool is designed to dynamically change the layout of a restaurant or bar to maximize the number of patrons while maintaining the CDC social-distancing guidelines. Any restaurant will be able to digitize their floor plan in our web app and specify the amount, type, dimensions and capacity of seating available. As reservations enter the restaurant’s system, the platform will automatically optimize the layout to ensure the safest and most efficient means of serving customers. How we built it Prior to developing the solution, the team used a series of agile problem-solving techniques similar to Google Design Sprints to understand the unmet needs of the customers we wanted to help. The layout and wireframe functionality was all built in Figma to model the user’s experience while navigating ReShape. Challenges we ran into Developing our understanding of what the “new normal” might look like. To overcome this hurdle, the team modeled our solution to reflect the steps taken by countries that are beginning to reopen, despite being devastated by COVID-19. Identifying the scope of the problem we intended to address. We communicated with local business owners and restaurateurs in the Hoboken area to identify the immediate challenges they were facing locally, so we can design something that was both feasible and purposeful. Coordinating and maintaining communication with a diverse group of individuals using online platforms. With clear and direct management, we were able to optimize the skills of 9 different teammates to work collaboratively towards a common goal. Accomplishments that we're proud of We were able to pivot quickly when we determined that one of our original concepts was not addressing the Hackathon prompt We identified a problem and interviewed customers to determine their pain points and adapt our scope before creating a solution. We developed a marketplace that addresses actual needs and help businesses cope with the new normal. Hearing from local Hoboken business owners that they not only find great value in our solution and would use it in their establishments, but they would invest in the product if we were to take it beyond this Hackathon. What we learned The customer is the center of every solution and UX design is imperative not only in designing a front end solution, but the overall viability of a product. Managing communication is difficult online, especially across multiple parties with varying agendas during this unprecedented pandemic. Organizing an internal infrastructure with specific communication channels is imperative in maintaining synchronicity in a collaborative design effort. Work quickly in small sprints by clearly identifying actionable items and delegating responsibilities across teammates' skills What's next for ReShape Conduct small scale experiments (fake front door experiment, Wizard of Oz experiments, etc.) to determine the desirability, feasibility, and viability of the e-Marketplace and floor planner solutions. Interview more target market customers to determine the most important features necessary to include in the Minimum Viable Product Once experiments have proven that our solution would be desirable, feasible, and viable, we would develop the entire technical solution for customer use Additional Materials: click here For additional materials, please visit the linked appendix above to view important auxiliary information that further outlines our design process... Customer Interviews Market Research e-Marketplace Technology Floor planner Technology Business Model Health, Safety, and Liability Concerns Built With agile-development-methods figma html5 mit-app-inventor

https://devpost.com/software/caresnow

Inspiration With millions of people losing their jobs every week and struggling to file and receive unemployment benefits due to the COVID-19 pandemic, we wanted to come up with an idea to help expedite this process. In our current system, recently unemployed workers file claims with state government unemployment offices, which then proceed to verify with employers that termination was not the employees' fault. By having employees file benefits, there exists a huge backup where unemployment systems are overwhelmed with multiple calls from people trying to compete to be first in line and can't get benefits to recently unemployed workers. What is CARESNow CARESNow is a system that allows employers to easily file unemployment benefits for their employees--it is designed to leverage existing financial relationships rather than use the slow verification systems that exist currently. By having employers file, this system avoids overwhelming phone and online processes as only 1 claim is filed per worker. Our system works by having the employer submit identifying information, compensation details, and reason for termination to CARESNow, which acts as a vendor that files claims to unemployment offices. Then CARESNow sends a unique employee ID to both employers and employees as a receipt for tracking and verification purposes. Employees then have the option of submitting corrections for any information from employers. Once the claim is approved, employees begin receiving unemployment benefits. This process eliminates the need for unemployment offices to wait for claims from employees and having to manually check with employers for termination reasons. As a result, this system is streamlined, accountable, and is faster and more convenient for all parties involved. CARESNow allows unemployment offices to process claims faster, reduces workloads for enterprises, and allows recently unemployed workers to receive their benefits quickly and without hassle. Accomplishments that we're proud of We designed an easy to use system with an intuitive UI and solves a major problem in the COVID-19 crisis. We believe that the solution we have will make a big impact and improve the lives of many in these difficult times. What we learned Unemployment benefits are complex. This system only touches the tip of the iceberg when it comes to the many problems with our current system. From outdated systems, to antiquated processes, there is a lot of room for innovation in this space. We learned that it's difficult to design a streamlined system, as there are multiple parties involved, logistical issues, and concerns for all stakeholders CARESNow must address. We found that it's important to figure out a solution that works and benefits employers, employees, and governments alike. What's next for CARESNow CARESNow needs to be fleshed out and incorporate security standards to protect the privacy of its users. In addition, integration needs to made with existing unemployment systems and partner with enterprises to begin beta-testing. We need to work with policymakers, employee representatives like unions, and enterprises to tailor to their needs. The biggest challenge for CARESNow is adoption, especially as government can be slow to upgrade and adapt to modern systems. The COVID-19 crisis, however, has shown that there is a need for system upgrades and we believe that CARESNow can capitalize on this need and be the solution that fixes our broken system. Built With bootstrap html5 javascript jquery Try it out github.com

https://devpost.com/software/litfit

Login Screen Achievements Calorie Calculator Tips and Health Resources Steps/Main Page LitFit Wearable (M5StickC) Heart rate and blood oxygen level sensor Inspiration Obesity is one of the deadliest killers in society today. About 1.9 billion people over the age of 18 are overweight: 1/4 of the entire planet and 650 million people out of that 1.9 billion being obese. Obesity alone causes 2.8 million deaths every year . It is safe to say that obesity is one of the most common killers of today, and is overlooked heavily by people. We sought to facilitate weight loss and encourage healthy living by creating a product that encourages you to be mindful of your daily activity. During the lockdown, people are more sedentary than ever. LitFit aims to eliminate a sedentary lifestyle and encourages users to adopt a healthier lifestyle. What it does Our app has multiple features that all are geared toward adopting a healthier lifestyle, whether it be through increased exercise or better eating habits. Our app tracks your movements and exercise using Step tracker, which tracks your daily, weekly, and total steps. Total steps are then translated into Exercise points, which earn you achievements, giving the user a sense of accomplishment, motivating them to live even healthier and be more active. The Calorie Calculator utilizes a novel Machine Learning algorithm to detect the food calories as well as the type of food given an image, which is uploaded by the user. The Health tab tracks your pulse and oxygen percent saturation, as well as gives you tips on how to live a more active lifestyle: the three golden rules of LitFit. We also provide useful resources on quick workouts that the users can quickly jump. All of these features contribute to an amazing application that promotes healthy living. How we built it We build the front end entirely out of flutter, a multiplatform mobile application SDK. The hardware base for this project is an M5StickC microcontroller. The M5StickC has an ESP32 as its base with an in-built 6 axis IMU sensor. The IMU takes the accelerometer and gyroscope reading which are then used to calculate the number of steps taken by a user. External hardware plugins were also used to gather surrounding data. These sensors provide us with ambient temperature (outside temperature), Ambient Humidity, Ambient air pressure, and heart rate (pulse). All the reading from the wearable device are then relayed to an open-source mobile app giving the user a real-time data with a user-friendly interface The backend servers are implemented as APIs running on a virtual server and using MongoDB as the primary database. Challenges we ran into One challenge we ran into was uploading the image onto a server. James, the frontend designer, had trouble figuring out how to stream the data back from the output of the backend into the UI asynchronously, however, he figured it out after a few hours of trial and error. M5StickC is a 2019 product, there is little to no online support for troubleshooting. Working with such new hardware and navigating through its library to get useful functionality out was a huge challenge. Accomplishments that we're proud of We are proud to actually accomplish what we set out to do in the beginning. Our initial goals were to build the ML algorithm for calorie detection and track steps, heart rate, and blood oxygen. However, we went above and beyond our initial goals through hard work and implemented further capabilities, such as the achievements page, login, additional resources, inspirational quotes, and more. Linking up the hardware with the software felt amazing because it seemed like everything was clicking into place. What we learned I learned a lot about how servers communicate with clients. I learned how to use HTTP get and post requests, as well as sending images to a server in a multipart server request. I also learned how to create a better and simple UI for a better UX. - James What's next for Lit Fit We hope to develop LitFit further to be more lightweight, as well as polish the Front-end and add more features. Some of the features are not fully functional, such as Login and achievements, but those features can be implemented with more time. We believe LitFit can actually be a revolutionary weight-loss miracle product and hope to pursue that goal of promoting a healthy lifestyle. Built With arduino flutter mongodb python Try it out github.com

https://devpost.com/software/cover-u

Main Screen of the User (with Contacts and Special Group "Close Proximity Contacts") Health Status of Your "Close Proximity Contacts" Proximity of Infection based on Fused Location Techniques Notification Alert when a "Close Contact" of the User is Diagnosed with COVID-19 Inspiration For many people worldwide, severe limitations on daily life because of COVID-19 have become the new normal. The economic, social and personal impact of all the wide-reaching restrictions imposed by governments all over the world is immeasurable. Economies are struggling, people are losing their jobs and they feel insecure as they are terrified to go out or to get in touch with anyone. Even numerous of restrictive measures and general lockdowns in a country level cannot handle the spread effectively. This comes as a direct result of the inability of the governments to instantly, accurately and efficiently trace all those who have come into close contact with an infected person. Identify and analyse each and every new case is typically a very labour intensive endeavour, demanding a great amount of effort of the personnel of the Health Authorities. As a result, the real number of the COVID-19 cases and the estimation of the spread is impossible to be accurately calculated. For these reasons, we need more effective ways in suppressing the pandemic in order to return to our daily lives now and safely. It is also extremely important to provide a cost effective exit strategy to governments in their target to avoid or manage a second wave of COVID-19. What it does COVer-U , a mobile Contact Tracing Application , offers decentralised and free tracking of the contacts of a person that is diagnosed with COVID-19 with respect to people’s privacy. Tracking will be a combined result of 2 pools of data resources : Fused location techniques such as Bluetooth Low Energy (BLE), GPS, Wi-Fi, Cell Networks . These Location techniques will follow a decentralised way of storing data so as to overcome any privacy risk. The data will be stored in the user's mobile only and will be correlated locally with the data of any affected user with the proper level of Anonymity . Information sharing between specific contacts and groups that each person optionally can create in the application (based on the voluntary participation and approval of each user). Each Group will follow some principles and proper Terms of Use on what information can be shared to this specific Group. Only authorised members and only in specific groups can receive notifications about the change in the Health Status of a group member. With the combination of 2 pools of data resources the solution aims to cover even bigger percentage of tracking the infection, where other similar solutions fail. By information sharing, it will cover cases even when someone is not carrying a mobile phone at the time of infection! It will follow the regulations regarding Privacy and Sensitive Data handling (GDPR, Terms of Use, Anonymity, Encryption, data will be deleted after 2 weeks period). Using Groups & Contacts A user will be able to optionally add Contacts and create various Groups . Each Group will follow some principles and proper Terms of Use on what information can be shared only on these Groups and nowhere else. Close Proximity Group : There will be a mandatory Group, named “Close Proximity Contacts”. Each user will be able to add people in this group under the following principle: User is advised to add only the persons that is expected to come into close proximity on a frequent basis (at least once every 2 weeks) • The purpose of using “Close Proximity Contacts” group is to ensure that the application will cover more cases of a user running into an infected person within each user’s social network in everyday life, thus increasing the coverage of the application. • These contacts can be Family, Friends, Co-workers, Neighbours, Local Shop Owners and Employees, in general every day persons that the user comes into close contact. • User will be notified with status changes in their avatar: “COVID-19“, “Stay Home” Icons. • Optionally and if approved by the user, the “National Health Care System” will be notified. Checking Health Status Each user will have a "Health Status" Button. The user can optionally press this button, i.e. to check every day the status. Then, the application: • Will do the match on each user's mobile between the user's location data and the location data of the positive tested people. • Send notifications to the proper target users based on some matching criteria for the last 2 weeks with a level of probability of infection. These people should be informed that they were possibly infected by another person so as to take precautionary measures. Data will be encrypted during the whole procedure and will not include any personal data (i.e. no name, mail, phone etc). Where we Differentiate By using both GPS and Bluetooth technologies, we expect to have bigger coverage of tracking than any other solution now can offer (as they use only one of these technologies) By using Contact Information Sharing we expect even greater coverage. These cases cannot be covered by any Location Technology (e.g. Bluetooth, GPS, Wi-Fi, Cell Network) We cover cases when a person touches a contaminated surface. This infection could have been caused even between 2 persons that never met. These cases cannot be covered by using only Bluetooth Technology. We cover cases where the infection caused by the virus that was transmitted through droplets generated when an infected person coughs, sneezes, or speaks. This infection could have been caused even between 2 persons that never met. These cases cannot be covered by using only Bluetooth Technology. We can trace incidents when someone is not carrying a mobile phone at the time of infection. We believe that such incidents cover a great percentage of the overall number. Some examples can give some insight: CASE 1: John goes for a while to a neighbour market, grocery, pharmacy without his phone. The owner of the shop is infected. CASE 2: Mary works in a company and drops by to the 2nd floor to meet a teammate or attends a scheduled meeting in a room with some co-workers from a different department and leaves her phone at her desk. One of these co-workers is already infected. CASE 3: Ronald plays football with another team and leaves his phone in the locker room. A football player from the other team is infected. How We Built it At this point the target is the Android mobile phones. It is built with Android Studio, by using Java and Google Firebase. Currently, there is a team of 6 highly skilled and talented people working to prepare an MVP. Challenges We ran into • Finetune the algorithm for choosing the proper location technology to store data during daily activity of the user based on various metrics (i.e. anonymity, accuracy, low power consumption, simplicity). • To cover each aspect of Privacy and sensitive data concerns (GDPR, Terms of Use, Anonymity, Encryption etc). First level discussions with various mentors on Legal departments specialised in such areas have realised in order to verify that there are no blocking issues. • To explore options for the interworking of the application with the "National Health Care System" of Greece, any other local Authority or any other country that will support this solution. Accomplishments that We are Proud of The idea won in the category "Ready to fast-track" at the Greek Hackathon (CrowdHackathon) on the weekend of 4-5 of April 2020, supported by the Attica Regional Government (Athens) and various other public sector entities. CrowdHackathon • Personal interview to Insider.gr a well-known Greek web newspaper, posted at the link below: Insider.gr • MVP ready • Collaborating with a team of 6 people, fully motivated with the idea in a very short timeframe. • Starting discussions with various mentors of Crowd Hackathon of Greece for the next steps. • Ongoing support and help from the organizers of Crowd Hackathon for the realization of the idea. End User Engagement • The more the user keeps the application updated with contacts the more protected the user will be. The moto here is: Participate in order to protect and be protected • Will boost proper precautionary measures to all people that were in close contact with persons that have been diagnosed with COVID-19 so as to reduce the spread of infection. • Will help everyone with an easy and intuitive way to be informed about the health status of user's target contacts. Value • It will be available for free and can be easily accessible. No need to go anywhere to buy it, “Stay Home” and just download it from the relevant App Store and Google Play Store. • It will save money for governments and local authorities. • A great tool in the hands of any National Health Care System. • It can be easily adapted and used by people and countries all over the world in their fight against the spread of the virus. • Yet, there is no “instant and automated tracking system” of COVID-19 promoted by EU Authorities for all the Europeans. • It can cover cases that standard location tracing approaches cannot compute. For example, there are thousands of cases and periods of time within a day where one person does not carry the mobile phone but eventually will come into close contact with other (possibly infected) people, i.e. neighbourhoods, local shops and local businesses. • It will be extremely useful not only during extreme shut down measures imposed by the governments, but also post - lockdowns . As it will be proved as the best and cost effective measure of early detection and ultimately avoid or manage a second wave of COVID-19. • It can be re-used in other contagious diseases and epidemics. What's next for COVer-U • Next steps is to present MVP at the next cycle of Crowd Hackathon of Greece. • Participate to country level Hackathon "Digital Innovation Initiatives Against COVID-19" supported from Greek Government . The process is ongoing and at this phase the submission is approved. Digital Innovation Initiatives Against COVID-19 - #GreeceVsVirus • Starting discussions with local authorities on how this application can be used and adapted accordingly. • Continue the implementation and add more features into the application. Support of iOS mobile phones will be our next target. Optional collection of statistics anonymously for plotting the spread of COVID-19. Integration also to other social applications is a part that we will also explore. Built With android android-studio firebase java Try it out covilisation.github.io

https://devpost.com/software/purifyre

Inspiration PPE shortages can cause big issues for medical institutions and first responders, especially during a global pandemic. To help combat consumer demand of disposable PPE, reusing equipment is vital. To allow people to reuse equipment, their equipment must be safely sanitized after use. What it does Purifyre is a low-cost hardware system that sterilizes and sanitizes through UV LEDs, heated air flow, and vaporized Alcohol. It is designed to be suitable for household and medical use. The system utilizes five primary components, a heater, enclosure, UV Led array, fan, and tub of isopropyl alcohol. The hardware enclosure system is designed to be flat packable or ready-to-assemble by the end user. This allows for easier shipping and distribution. It is also designed to be manufactured out of flat sheet material, which is abundant in a variety of materials. After consulting with a few medical professionals, we have determined a basis for a sequence of operations: Dry heat 15min at 80C IPA pumped in to the tray from a small tank, Heat at 70C for 20 min, Heat to 40C for 15 min Heater off for 15min How we built it Soldering iron, wires and code. Acrylic cut via laser cutter. Container was repurposed hydroponics equipment. UV LED panel was created from UV led adhesive strips. What we learned UVC LEDs burn out What's next for Purifyre Better prototype and hopefully funding. Built With arduino c electronics python raspberry-pi uvc

https://devpost.com/software/coronavirus-hotspot-tracker

HomePage Corona Form COVID Map Background Problem Page Solution Page Applications Inspiration: To combat the spread of corona-virus, many countries have imposed strict lockdowns. The goal was to limit how much people were traveling to reduce the spread of corona-virus. However, due to economic reasons many countries need to reopen business and ease restrictions. Currently many people track the amount of cases in each state and county, but we wanted a platform that could keep track and inform citizens of dangerous areas outside of their homes that they should avoid or take extra precautions around. Problem: COVID-19 is difficult to deal with because of how rapidly it can spread. The disease can be contracted either airborne or from surfaces. On surfaces, COVID-19 can last up to five to six days, which allows a person who has COVID-19 to spread it to others over a long period after they have left. So someone who is positive for coronavirus and has not identified it, can be traveling and touching surfaces at stores and restaurants leaving those who aren't infected to potentially touch the same surfaces and contract the virus. The problem we address is accounting for the travels of the person before they are confirmed as having COVID-19. Solution: We decided to build a platform that helps people visualize a more detailed view of where exactly the virus could be because the spread of the virus which occurs through air and surfaces, which makes public places like stores and restaurants danger zones. In the initial stages of this idea, we rely on everyone in the community to be doing their part and rely on the data coming from reliable sources, however with time, we plan to scale it to have only government officials report data, which we will talk about in a further section. Goal: Our goal is to give people the normality in their lives and provide relief to front line workers. How are we Different? We are different because our platform displays red zone areas and severity of the contraction of the virus, whereas other platforms notify someone if they were in contact with someone who tested positive. The ultimate goal of this platform is to make sure that people take proper precautions before going to a designated area or even avoid COVID red-zone area, thus promoting proper social distancing techniques and flattening the curve. Security and Privacy: Our platform complies with the HIPAA (Health Insurance Portability and Accountability Act) privacy policies as we do not store any health records, the individual’s name or address, and the individual’s IP address. The only data that is stored are the locations the individual has traveled to, which is self-reported. Finally, we added information on the self-reporting form to inform people the situation that is taking place. What it Does? There would be two types of users that access our platform: those who have already contracted the virus, and those who haven’t. Those who have already contracted the virus would access the website, and fill out the form with information on where they travelled in the last five days, as the virus lasts for a maximum time for five days on surfaces. Then, by updating this on the map of our platform, this would help the second type of users, those who haven’t contracted the virus, to be extra precautious of where they choose to go during this pandemic. The heatmap locations will be updated with data that is not older than six days since the virus is proven to die within that time. How we built it? We used HTML and CSS to design the homepage, which discussed the background of COVID-19. On the click of the “STOP COVID Button”, we used Flask on python to retrieve data from the HTML form and store the data within our python file. We were able to do this by creating a localhost server that connected the HTML to our python file. The python file would send a request to HTML and the HTML would send the data through an HTTP supported method of transportation “POST”, which safely sends encrypted data over the web server to the python file. We also used python to import certain packages such as the GeoCoder (translates Address to latitude and longitude), Pandas (to store data in a frame and to write to an Excel File), and Folium (to display the heatmap to represent the severity of COVID-19). Challenges we ran into: As the project progressed, we realized we had to constantly modify the initial project because of restraints we had. Due to the lack of time, we compromised certain features and focused solely on providing a fully working solution. In addition, we were not aware of how to implement many of our ideas, which required us to self teach many concepts using HTML, CSS, and Python.In Python, we had to research the most effective packages for parsing data and visualizing the map locations. We also had to learn how to create and implement a server that could secure an encrypted communication between the HTML and the python file. Accomplishments we are proud of: To create our project required more than learning about code, we had to learn to manage our time and work effectively with each other. We collaborated as a team to find a time that would work with all of us. In addition, we kept checks on each other to make sure each member was getting their deliverables completed on time. What We Learned: As a group, we learned there are so many resources out there and if we all work in unison, we can find solutions to any problem. We learned to create a working product, and that we must first identify a problem and then address it. The solution we create must be realistic and feasible. We learned the best approach is with agile principles and constantly modify the requirements to fit our goals and needs. Through this project, we learned the product we created can make a real impact on society and truly reduce the risk of contraction. Scalable Opportunities: Our project can be extended to be applied to University and Work campuses where they can supply a map of the campus and we show students and staff recent positive cases which cater to their location. For example, Stevens Institute of Technology would supply a detailed campus map to us, which in turn we would generate a heat map for them where their students and faculty can use for more specific information. The government can also adapt our platform to provide more accurate data, rather than self-reporting, by using their contact tracing team to submit the locations where COVID patients have traveled to provide more accurate data. What’s Next? We will build this platform to a commodity that every community uses. The next immediate change that we plan to do is build a secure web database using Amazon Web Services (AWS) in order to securely store the user data. In this hackathon, we had to build an excel file full of data in order to simulate a database to present our platform, however that wouldn’t be used in the final implementation of the platform. After we have a secure database for our platform, we will make the program more user-friendly. We will extend this idea to be an app for users to access so they can always check the COVID status of locations on the go easily, without having to go to the website every time. In addition, instead of the user inputting a street address, we will implement a drag and drop feature, where the user can click on the location they were at, which saves the user time to look up the street address of where they went. "Even 15 reports can save 15 lives or more." - CoronaVirus HotSpot Tracker Team Built With css excel flask folium geopy html numpy pandas python Try it out github.com

https://devpost.com/software/test-project-fej821

PreCon AR Inspiration In this current situation, people are still struggling to adapt and doing daily activities. The government enforces some rules and gives suggestions for the public, so that people can deal with this problem. But, there are many people who still underestimate the fast transmission of COVID-19, disobey the rules, ignore the advice and those who aren’t sure which shouldn’t be done, etc What it does Using Augmented Reality (AR), we made PreCon (Prevent Contagious) in order to help the public in experiencing real life situations inside AR. The app helps to educate people on how to prevent this virus from being transmitted. Inside the training simulation, people will interact with the virtual environment and learn how they should act accordingly, because the important thing is to prevent something bad from happening to us rather than try to cure it. Since all the events happen inside the virtual world, this training simulation is safe to use by everyone. Beside AR training simulation, there are still several features that PreCon have. Here all the feature of this app : AR Training Simulation. Experience real life training simulation and interact with the object inside the virtual world. Advice from WHO with easy to learn illustration step by step. AR Selfie. Take a selfie photo with a mask and face shield. COVID-19 status all around the world. Intelligent assistant to provide us some answer about everything. How I built it Unity as our main tools for making the application. Using C# Language. ARFoundation to provide the Augmented Reality technology. Postman public API. Wolfram Alpha API as Intelligent Assistant. echoAR to provide a flexibility for 3D object and real-time info update. Challenges I ran into I need to find more information about Augmented Reality also do trial and error, sometimes makes me overwhelmed. Accomplishments that I'm proud of This project actually. Somehow proud that I can be part of "helping others" in this pandemic with my own way. Especially helping medical team to prevent other people being infected. Helping people with Extended Reality technologies are something that really change the views of AR/VR/MR application. What I learned From this project, I'm more learn new things about AR, how to solve problem, how to adapt to the new things, also more exploring about COVID19 also for my self I'm learning more about what should we do and should't. More exploring some advice for being healthy during this pandemic. Also learn about how to integrate my application with Wolfram and echoAR system. What's next for test project Adding more training case inside the current application. Also if we can really continue with this project, we maybe will try to do Virtual Reality Training Simulation, so it can be more immersive to do a training. Built With android api arcore arfoundation c# echoar speech-recognition unity-technologies wolfram-technologies Try it out precon.rgplays.com

https://devpost.com/software/learning-curve-d2geat

Inspiration COVID-19 has impacted how education is provided for students. As classes move online, students lose the necessary qualities of traditional learning. While there are online tools, such as Khan Academy and BrainPop, that serve as educational resources for students, they fail to provide the proper interaction and flexibility necessary in keeping students engaged. Our team wanted to create an interactive enrichment platform for students to supplement their education and help fill the gaps created by this pandemic. What it does We have designed an interactive platform for students to supplement and enrich their education. We also provide a social platform for students to interact with their friends and tutors to improve the lack of social interaction resulting from the pandemic. We also provide encouragement and resources for students to pursue extracurricular activities to allow them to express themselves in a fun and creative manner. How we built it We divided the work into two teams. The first team performed extensive research on grade-specific curricula and created study plans for students. Moreover, this team provided most of the information presented on the website. The second team implemented this information into the website and executed the majority of the technical work involved with developing the website. This team also improved designs made by the first team to make them more feasible for the platform. Challenges we ran into One major challenge we ran into is how to make the platform interactive and fun for students. To combat this, we tried to give each student as much freedom as possible in terms of the subjects they choose and how long they spend on it. Also, we allowed for sessions where students can work together with their friends. Accomplishments that we’re proud of We are proud that we are able to provide a platform that improves the educational and social deficits that result from the coronavirus pandemic. Our Tech Lead, Bryan Kyritz, recently developed a video-chatting forum, called Secure Meeting, with similar features as Zoom. Though the platform was made before the hackathon, Bryan implemented significant changes to make the website more user-friendly, such as chatting, video controls, etc. Our study plan curricula also integrate the importance of mental health and activities they can work on at home! What we learned As Learning Curve, we targeted one of the fundamental challenges of the post-pandemic era, education cap. COVID-19 is bound to promote social reconstruction of society, and though there are plenty of resources available, such as Khan Academy and Brain Pop, there is a lack of a platform which integrates all the resources in a cohesive manner. Therefore, we learned that if we can provide them with customizable resources and a little bit of constructive competitions, the students will be motivated to continue their education during the post-pandemic era. What’s next for Learning Curve In the future, we plan to allow high school students to sign up as tutors to gain volunteer hours hours by hosting tutoring sessions and make study plans for their students for their college applications.We also plan to extend our partnership with local institutions, such as libraries, as they generally host events to educate children from K-12. Built With MongoDB, Express.js, React, Node.js Built With express.js mongodb node.js react Try it out www.learningcurve.school

https://devpost.com/software/covid-19-rescue

This is screen shot of the Corona Relief App Running on Microsoft PowerPlatform Inspiration I saw that many people who are poor or belongs to middle class families are facing Food Scarcity due to this Covid-19 Pandemic because their income source is stopped due to the Lockdown. There are many pregnants women, children, old aged people who are facing the same situation and they cannot afford food for them because they are in short of money and they are helpless. I saw that many organizations are helping these kinds of people by are taking live call in Television Channels to address people problems and helping as they require. Only one calls can be taken at a time on a live television. Also, there will be problem of network Busy and those organizations cant reach many people in this way. So I thought to develop and application so that people can report their problem and the organizations will get to know about the problem and help them as they need. What it does Basically my app minimizes and speeds up the process of addressing people Problem so that their problems can be fixed as soon as possible in this Pandemic. So when the app runs, user will enter their name and they need to choose whether they want to request for Food Help(Basic Need Relief) or Corona Check(this is additional feature added in app) When they choose the Food Help or Basic Need Relief then they will be asked with several questions such as total family member, no of pregnant women, kids, old aged, and remaining food stock, and also a option to send an attachment. Whereas, when people will choose the option for corona check then they will be asked with several questions like gender, what the symptoms seen on person so you are checking corona, has he came from abroad or not and so on.. . Now, When the user will submit this information then these data will be recorded in Microsoft Sharepoint where the admin or the organization can view the problems or people along with the GPS CORDINATES and Date that will be automatically sent while submitting the problem inside the app. Then from this information, the organization can directly go with the necessary relief to the needed families using the GPS Cordinates that is sent while submitting the app How I built it I built it using the Microsoft Power Platform Challenges I ran into I had learnt some Flutter. And I was trying to make this app using Flutter but my laptop got some ransomware and i lost my everything and I reformatted it again and installed flutter. I did made the forms but the conditional things, GPS Location and so on was very complex for me as I am beginner to Flutter. And learning everyconcepts from the beginning and developing the app would really be difficult and time consuming. Then I heard about Microsoft Power Apps, I already had and idea and I just needed to implement it properly so I started learning Microsoft PowerApps and I tried to bring my idea to life. Using PowerPlatform also I had some Difficulties in Conditional Forms for Corona Check and Basic Need Relif. But finally I figured it our after couple of research. Accomplishments that I'm proud of I don t know that the project I have made will be used by some organizations that are really doing these kinds of Relief Programmes but I think this app will really be helpful for them because if they can address many people problems in less time then they can provide reliefs to many people as possible and poor and needy people as well as middle class people who are deprived of food, pregnant womens, kids who are not getting nutritious food due to the Covid-19 Pandemic and lock down in the country will get relief and should not die out of hunger. Because we dont t know how long this Pandemic is going to take place. What I learned I was complete beginner to Microsoft Power Platform. But I had an idea that must be implemented to help people so I started learning by heart and got to know many things about the Microsoft Power Apps and I think it also increased my creative skills and logical thinking capacity. What's next for Covid-19 Rescue Currently this app can be run under the Microsoft PowerPlatform only but it needs to be platform-independent. So I am planning to make it platform independent very soon if I will get some good mentors to support my project.I have also planned many other features in this app that can be really beneficial and helpful for the people facing Covid-19 Pandemic. I think this kinds of apps must be developed to address poor people`s problem who can be helped by the person who can help them. Problem sending app demo link Since it is dependent on Microsoft PowerPlatform. I require your email to show you this app. It must be opened within Microsoft Power Platform so i couldnot send the link but i have sent image on how it looks when the app is running and demo video for working of the app. Built With powerplatform

https://devpost.com/software/vox-of-life

Sign Up Time to Talk Notification Text Confirmation Voxers on call Wireframe People are by nature social creatures. These past few months of having to isolate and distance yourself from others has been extremely difficult, both physically and mentally. In today’s world, communication and social contact are a huge part of daily life, larger than they have ever been before. This situation happened so quickly, and it may continue indefinitely. We believe that one can abide by the ‘new normal’ and still maintain social contact by using Vox of Life. In Latin, the word ‘vox’ means ‘voice’. Vox of Life strives to be the ‘voice’ that can be used to initiate, maintain and communicate with others in a safe, controlled environment by the use of the Vox of Life app. The Vox of Life is an opportunity to socialize with others with the same interests, hobbies in you choose, or with someone else who may just need to talk and hear another human voice. What are you interested in accomplishing? What might be reasonable to accomplish? Encourage spontaneous meaningful interactions between all walks of life Reduce impact of social isolation Make conversing with new people comfortable Encouraging extroversion in a time where we’re all distanced Is this something you want to do within the timeframe of the hackathon only, or are you interested in working on this after the 12th? The effects of COVID-19 are far reaching, and mitigating the effects of social isolation is our goal. We believe we can do this by connecting new people on 1:1 phone calls to meet new walks of life. Even after the curve is flattened and social interaction becomes safer, we will be transitioning our efforts to continue reducing the impact of social isolation, and creating ways for improved communication between individuals and groups. What is your bandwidth to contribute? We, the members of this team, are extremely passionate about our mission and are currently balancing this initiative with full time professions. We are capable of supporting this initiative but are seeking support to ensure our mission continues to have a greater impact. Who is on your team? Please describe your background and why you’re the right person/team to work on your idea. Magus Software Engineer Design thinker Social enterprise enthusiast Right person: I like to make things, and also love to make things better.I aspire to work and make products that can create lasting social impacts globally Shiv Client facing Biomedical engineer Health focused Right person: I desire to make an impact that can positively affect people and improve the way people see the world and others Sam Marketing Specialist Client facing Right person: I have a desire to network with others and get to know other people and Vox of Life is heavily geared toward networking Patrick Full stack developer Highly competent in multiple technologies Right person: I am not a fungus, I am a fun guy and I like building fun tech Inspiration Vox of Life was inspired after noticing heavy the toll self-isolation was putting on the mental health of friends and closed ones. Social distancing and self-isolation don't have to mean loneliness and silence. VOL's on the mission to encourage people to have meaningful social interactions, while still practicing safe social distancing. We enable this by pairing different walks of life to each other through just a voice call and simply by the time they both are available. Built To rapidly execute on this mission, the proof of concept initially was "pretotyped" with a combination of traditional software engineering frameworks (NodeJS/Nest) and even no-code tools (Zapier, Airtable, Wix). We used NestJS to build our matching algorithm and backend server, and used the no code tools to build our frontend. The first prototype was complete in the first half of a weekend, and the private beta started the very next day. A lot was learned from our testers and the project went through multiple iterations over the course of the trial very quickly. Challenges Initially, VOL calls only worked over the web on desktops. Multiple testers provided feedback to make it also accessible over their mobile devices. In less than a week's time, the testers were able to dial-in to their calls. Future Nursing Homes Build relations with nursing homes, to allow the isolated elders to have one on one calls with volunteers Slack Integration for Slack, where users can have spontaneous one on one interactions with in their existing communities Built With airtable html javascript nestjs sendgrid twilio typeform wix zapier Try it out voxoflife.com instagram.com github.com

https://devpost.com/software/trachio

Trachio Logo. Inspiration As we can tell by an enormously growing infection rate, it's important that we diagnose potential symptoms of COVID-19 and communicate with our local health departments. What it does Trachio is a web app that allows you to upload spectrograms of a patient’s lung sounds in order to diagnose and report potential symptoms of COVID-19 to one’s local health department. How I built it I created a Flask backend that communicates with a dynamic HTML/CSS frontend, which allows you to upload audio spectrograms. A classification is made through the Google AutoML Vision API and returned to display potential symptoms on the frontend. There is also a feature that allows you to quickly contact local health authorities via email, which is plain HTML. Challenges I ran into Of course, getting Google Cloud authentication to work properly was a hassle. Also, I was a bit slow to develop because I had never used Flask before. Accomplishments that I'm proud of But regardless, I'm really proud of how many tools I learned to use in the past 24 hours. I dared myself to go solo and I feel like it paid off for my own learning. What I learned Basically the entirety of Flask, and servers in general. What's next for Trachio Improve the model's accuracy, and make the frontend prettier. Built With css3 flask html5 keras python teachable-machine tensorflow Try it out github.com

https://devpost.com/software/obskill

Inspiration Due to COVID-19, one of us lost our own internship for the Summer of 2020. Many of our peers have felt a similar effect. With access to a large student network and large company network, we felt the need to give both sides support by joining the two. Some businesses are struggling to adapt to the new remote work style. We first hand noticed interns being paid for 40-hour work weeks when because of the new remote style, they were only working half of that. We began to question if it was worth it for businesses to continue the same pay-rate for internships, with a drastically decreased rate of productivity. The answer is it’s not. The internship program has to adapt as well. What it does To provide a route for the internship program to adapt, we encourage companies to host workshops for students to work on. These workshops are short term company-student interactions that can last anywhere from a week to three months. The website is currently functioning to connect students to employers to continue career development in this remote manner. By organizing these opportunities into workshops, it is allowing us to track the level of work being completed by students. This allows the rest of the industry to see some evidence of how well students can work in a remote environment. This opens relationships and opportunities on both sides for the brighter future. How we built it The original site was launched as an online survey to collect interest through a wordpress site. We hosted the site through AWS servers. As interest expanded, we focused more on the improvement of the wordpress website. All the back-end work was being done by hand, such as organizing user data and matching students to positions posted by companies. For the hack-a-thon we focused on creating our prototype in figma to better explain our vision for ObSkill and the benefits it can bring. Challenges we ran into A major challenge we ran into was not having a full stack developer join our team. This caused us to have a main focus on creating a front-end prototype in figma. This allowed us to plan out all of the site functions, preparing us for the future of working with a full stack development team. These challenges are occurring because of the growth of our idea, as more students and companies sign up it is becoming harder to run without the process automated. Accomplishments that we're proud of We are proud of how the prototype came out. We feel it is a great representation of the first phase of ObSkill. We are also proud of the fact that we have already assisted a handful of students in getting connected to opportunities for this summer. The positive feedback from the students and companies is what keeps us going with the further development of this idea. What we learned We learned about the difficulties of bringing our ideas to reality. Our initial idea of making this platform through wordpress was unrealistic, and now we understand all the planning and mock-ups required for a successful website. As two students without web design experience, we had to quickly teach ourselves tools such as wordpress and figma to portray our idea. We now know the importance of getting a strong back end development to improve ObSkill for the future. What's next for ObSkill Our immediate goal is to create or find a developing team that can help us create an automated web application based off of the figma mock up we created. We are reaching out to more companies that could use our assistance while the number of students on the platform grows. We plan to launch an updated version this summer with an automated back end, thus allowing us to support and benefit more students and companies moving forward. Built With figma wordpress Try it out obskill.com www.figma.com

https://devpost.com/software/c-trac-app-for-tracking-corona-hotspots

Inspiration During this current COVID 19 pandemic, I see health worker is curing the patients, doctors are innovating new medicine, the police is controlling the crowd movement and even bus drivers are helping people to get back to home. As a future engineer, I felt like my contribution is none, so I felt motivated to do my part and try to bring a positive change and to make sure my product can also be used in a future pandemic. problem our project solves we all can agree that this pandemic needs to overs soon so as we can meet our loved ones, in order to contain this pandemic, the government is using CONTACT TRACING APPS ( CTAs ). Research says if contact tracing is done correctly it can reduce the number of case 3 folds, then why the number is still rising? , the problem with these CTAs is they only tell whether you have come in contact with an infected person or not, what it doesn't tell us that from where the person caught the infection ( the parent source ). let's take an example if there are two-person 'X' and 'Y' and Y got infected then X will get notified by the current CTAs that he might have got an infection as he came in contact with Y, but it doesn't tell from Which PLACE y got the infection, this is crucial as if we don,t find out that PLACE then many other people who had visited that PLACE may get the infection. what our project does Our project C-TRACK 1st of it's kind of reverse contact tracing app, so let me explain how Reverse contact tracing works, whenever the user visits a place too frequently like a shopping mall. then that particular location will be saved inside the app and if in future user found COVID +ve then we can track down that shopping mall, the app will also send a notification to all over people who have visited that exact shopping mall, now health authorities can sanitize and lockdown that specific shopping mall instead of locking down the whole locality. the location stored is fully encrypted and can only be accessed by the user. it also has two additional feature 1.) it sends 'wear mask ' notification when the user leaves then house and 'wash hand' notification when the user returns the house, this small precaution can bring a huge change by keeping you and everyone around you safe. 2.) whenever the user enters a government certificated hotspot or RedZone he will get a warning notification Challenges I ran into 1,) we lack financial support as we have to make this app from scratch. 2.) the problem in collecting data regarding government-certified hotspot and also we have to do a lot of research regarding the spread pattern of COVID-19. 3.) It was hard for us to get in contact with health workers as they were busy fighting an increasing number of patients so we have to talk to retired doctors. 4.) It took us too long to use it in real-time as during lockdown it was too hard to go outside in the quarantine but finally, after lockdown loosens a bit we tested it and it gave an excellent result. What I learned All team members of C-TRACK were able to grow their area of competence by participating in the whole process of idea definition, market research, validation, prototyping, and presentation. Through different mentor sessions, we learned that problems could be approached by many means, but most importantly our mission should be clear. What's next for C - TRAC App for tracking corona hotspots our app can be used for a future pandemic or seasonal diseases such as swine flu or bird flu. Built With android android-studio java

https://devpost.com/software/covid-oversight

Details SS1 SS2 SS3 Inspiration Let's consider the story of Chris. He is still under lockdown and he is worried about his health. Currently he is not aware of the risky areas surrounding him. So he cannot leave his home to visit the local grocery store (which he prefers to buy from over online stores) without panicking. Also he fears he might take a route through a region infected with the virus which can affect him as well. And even if he reaches the store safely, he might be faced with a crowd which doesn’t maintain social distancing; and even if they do so, they all come at the same time leading to long queues. Even after all this, there is still a chance that he might be affected but asymptomatic and he might further infect others as he might be unaware of whether he had been in contact with anyone before. What it does COVID-Oversight tries to mitigate the above problems with a one-stop solution for visualizing local risky areas, finding safe stores and safer routes for visiting them, creating systematic queues for reducing delays and a case reporting mechanism for leveraging crowd-sourced data to map the crisis and protect one and all How I built it Here maps, Twilio API, IBM Cloudant, IBM Cloud Foundry, Postman Accomplishments that I'm proud of Completed the hack in under 24 hours Created an end-to-end communication, reporting, and verification system What I learned Apllication of Twilio and Postman Cloud hosting What's next for COVID-Oversight ● Integrate chatbot inside the web app ● Use IBM Watson API for further diagnosis on chatbot ● Use IBM Watson Studio to design a forecasting algorithm for better queue management and COVID spread ● Use Here Maps geofencing API and Twilio Notify API to alert users when they enter risky areas Built With flask here-geocoder here-map-image ibm postgresql postman python twilio Try it out github.com

https://devpost.com/software/uncle-jon-gatekeeper-a-i-powered-digital-guard-u7c5kl

Homepage Uncle Jon issuing Digital ID Office Locator on Map Office Reception Get Issued ID Nearby COVID-19 Clusters From Office Coffee Break Nutritionist Room HR Mary Live Call With HR Leave Alert Uncle Jon: A.I powered Gatekeeper As coronavirus recedes, companies will have a daunting challenge to choose which employees work from home and who come to the office. Is there a solution to this problem? Yes, Uncle Jon has an idea! He suggests that each employee will have to take an A.I powered test which will evaluate how likely they are to be affected by COVID-19. Then, based on the results of the diagnosis test and the position of the employee in the company hierarchy, Uncle Jon will automatically suggest which employees should be called to the office and how they must be seated. These results will be shared with the HR team who can then modify it as per their needs. Uncle Jon will issue a digital identity card to the employees who have to come to the office. The identity card would generate a token id, which the employee would have to enter at the office gate. The identity card would be valid for 7 days, post which the employee will have to take the A.I based test again to validate their health. That’s Uncle Jon. The most exciting features of Uncle Jon Gatekeeper that we have developed are: Automated A.I based realtime communication between Uncle Jon and the employee Generation of unique digital ID with the associated risk factor Companies can decide which employees work from home and which employees can visit the office Offices and workplaces can list their locations in a realtime map In-built one-on-one and group audio and video calls Nearest COVID-19 hotspot locator so employees can plan the best routes to stay safe Automated H.R Mary to help the employees on general issues and set up appointments Coffee Break Room where employees can relax and calm to increase their productivity during the break hours Nutritionist Room, which has a customized diet plan based on body parameters Main Idea: This test segregates to ensure that high priority cases work from home, while the low priority cases come at the office. Built With backend css3 html5 javascript machine-learning mongodb tensorflow Try it out github.com www.unclejon.xyz

https://devpost.com/software/corono-info-corner-amvh0p

Symptoms checker Navigation over features Front page of app ...email icon for emergency email contact Website containing all the covid details and hospital near me feature. Helpline number Donation FAQ's issued by government Locates nearby hospital from current user location(nearest) Fake news reporter Friendly chatbot Inspiration Nobody wants to keep separate apps to access necessary functionality during the time of emergency. There are 100’s of useful apps to help us through this time of turmoil, What if we had many such useful features on the same app? This is exactly what our app gives the user features that might come in handy for What it does These are few features we have worked on Daily Use: Fake news Verification: With the number of rumours making rounds on the internet , it is important to be informed about the news that is fake. The app allows you to view the fake news and also to report the news that might be fake, The reported news will be cross verified by the authorities before being uploaded. Shops trackers: Since it is difficult for the people to go outside and buy groceries .Using our app, we redirect it to some online groceries facilities like BigBasket, who will deliver at your doorstep with no contact delivery. Emergency: Hospital tracker: The location and the distance of the closest hospital is provided to the user. Using the existing map data from openstreetmap (an open source world map). The information from the GPS of the user's device along with the location of the hospitals on the maps allows for seamless navigation. Symptoms check: A Questionnaire is given to the user based on which an assessment of vulnerability to corona is provided. This is not a complete proof of corona, the app will only recommend the user to consult a doctor if they are vulnerable to corona virus. Helpline: A list of all the helpline numbers in India can be found here. Miscellaneous: Corona cases tracker: Graphical representation of the overall effect of the virus on a country wide scale with complete analytics of the same. Keeping the user well informed of their situation with easy to understand dynamic interface. FAQ’s: The most commonly asked questions and important news related to corona virus. Donation: A direct portal to donate to the PM cares fund through any UPI app of your choice. Queries: An easy way to send your queries to the official government body that is dealing with the virus Chatbot: To answer all the queries regarding the FAQ’s . How I built it Android studio: To develop the app and test it. HTML: For the webpage layout CSS: Cascading Style Sheets is a style sheet language used for describing the presentation of a document written in HTML Google JavaScript maps API: For location of the user. JavaScript: To get the distance and direction between user and hospital and to process as required .To make the web application dynamic and user friendly. Chatbot which answers all the queries regarding corono virus is implemented All are accessed within a single app with multiple use Challenges I ran into Google had temporary stopped the new registration for google cloud .So we had to implement using the open source API' s which were available. Few errors while creating GUI for android app Accomplishments that I'm proud of Within this short duration we were able to come up with an app with all the features required for a common person.The whole team played the important role in achieving such a big task. Link for website: https://covid-19iit.000webhostapp.com/ What I learned Team work how to split up the work and complete the task within the given deadline What's next for Corono info corner So in the future we are trying to integrate a feature where the cop can use his mobile camera to check the social distancing in the public area Also helping the cops to track the people quarantined in the house. Put the app on Playstore and App store. Built With android android-studio css firebase html5 java javascript Try it out github.com

https://devpost.com/software/countthepeople

Inspiration People are still gathering in mass despite the social distancing order to prevent COVID-19 spread. What it does From the CCTV cameras, relevant authorities can know if an area is not being crowded with people. It can be used as a crowd monitoring tool to detect large crowd gatherings. How I built it GluonCV AI/ML can detect objects such as people from an image. Therefore we can count the density of people in an area being monitored. Challenges I ran into Legality to get publicly available CCTV footage. Accomplishments that I'm proud of What I learned Need to complete AWS Computer Vision: Getting Started with GluonCV from CourseRA. What's next for CountThePeople Learn how to improve the algorithm to calculate the distance between detected people. Built With bootstrap gluoncv mxnet php python s3 sagemaker

https://devpost.com/software/informavirus-9cnxek

Symptoms Screen Heat Map Zoomed Heat Map Inspiration We noticed the importance of tracking cases when it comes to illnesses such as Covid-19 or influenza. This information can be used for allocating supplies to hospitals and mandating certain policies. The current way to do track cases is to look at the number of people who have tested positive for the virus. This relies on an abundance of accurate tests. Another way we could get a grasp of trends of illnesses through a population is to use what everyone has: a phone. People may not know what illness they have, but they will know what symptoms they have. With this data, we can create a real time visual representation of spreading illnesses, and we can figure out what symptoms are correlated with which illness. This visualization will also provide public awareness in regards to the importance of sanitation. What it does it do Users log into Informavirus and are immediately prompted to click "yes" or "no" for whether they have a specific symptom, like a fever or cough. If they click yes for a symptom, their location will start being tracked and plotted on a heat map that corresponds to that symptom. After checking all of the symptoms, they will be directed to a page with a heat map for each symptom. Users can't see the map until they check the symptoms they have. Seeing the map is the incentive for checking their symptoms. They will be tracked until they either go back into the app and check "no" on the symptom or the average duration of the symptom has elapsed. We understand that everyone with a symptom will likely not report it, but the goal of Informavirus is to see general trends, not specific numbers. How I built it Informavirus was designed as a web and IOS app, using the Quasar framework (using Vue.js), as well as the related VueX and VueRouter for the multipage and state-management functionality. Google Firebase is used to securely store user data (username and password), as well as location data. We designed the application to be as secure as possible - the location data is linked with their user ID, and can only be retrieved if the user decides that they would like to retrieve the data. Challenges I ran into One challenge was deciding how to structure our database. We wanted to ensure privacy for the users but also maximize the data's usefulness. If we attached each user's coordinates to that user's node, then it would be easy to delete that user's coordinates if we no longer wanted to track them, but having the user's coordinates attached to that user would be a risk to the user's privacy. Instead, we used two separate nodes, one with all of the users and one with all of the coordinates. We then attach the user's random ID to their coordinates in the other node as a way to deal with specific users' data. Accomplishments that I'm proud of I am proud of making an app that is very easy for users to use. If an app like this isn't easy to use, even with the incentive of seeing the map in the end, it wouldn't be likely that people would use it. The idea was to make a simple, clean app, and I think we accomplished that. What I learned I learned how important database structure is, and I learned that it will pay off greatly if things like database structure and overall structure of the app are planned before its creation. I also learned how important communication between team members is when working on a projects that has so many moving parts. Communication allows for more efficiency and a better product in the end. What's next for Informavirus Of course, since we only had a couple of days to get the project up, we had to compromise with our functionality. There are features that we want to add, but have not had the time to, such as merging symptoms onto one heatmap, using different colors to denote each symptom, as well implementing an algorithm that can use machine learning to see what areas are more likely to become "hot-spots" for the virus. Another functionality that we plan to implement after this algorithm is a method in which the application can send the results of the machine learning algorithms to the nearest hospitals, alerting them if there are more cases that may pop up. Of course, there would be some statistical analysis involved, as there are no perfect predictions, but if we are able to get even the slightest prediction, the extra preparation could be of help in the future. We also understand that for Informavirus to operate effectively, we need as large a user base as possible. So it may be most effective to team up with a company that already has a user base and a reason to attract users, like a social media app. Built With css3 firebase geolocationapi html5 javascript vuegoogleheatmap vuegooglemaps vuejs vuerouter vuex Try it out github.com

https://devpost.com/software/grocial-distancing

Inspiration: A lot of small retailers are going bankrupt because they were not prepared for the long-term shutdown. However, if more grocery stores are allowed to reopen, they might cause another coronavirus outbreak. Therefore, we wanted to create a tool that will help stores plan reopening while providing shoppers with a safe shopping environment as a part of getting back to their normal lives. What it does: Our application evaluates the infectivity of COVID-19 in a store based on its layout and other high-impact parameters. Store managers can simulate and test different layouts of their stores to maximize capacity and minimize infectivity. The app also provides shoppers with information such as infectivity and the safe capacity limit so that they can make informed decisions about their shopping behaviors. How we built it: The Grocial Distancing demo was built using standard web technologies, including HTML, CSS, and JavaScript. No third-party software libraries were used. Challenges we ran into: One challenge was deciding which features would be available to the customer and store owner user bases. Initially, we planned that users would only be able to see layouts made by managers; these interactions would be overseen by an account system. However, for simplicity, all features were ultimately given to all users, including full editor and simulator capabilities. Another challenge found during design was selecting a pathfinding algorithm for implementation. We performed some research on pathfinding methods, but ultimately, we chose a light-weight approach with smoothed A*. Although this algorithm served well in the current implementation, we may need to reconsider in the future to add deeper features like customer collisions and hard wall collisions. Accomplishments that we're proud of: We successfully implemented pathfinding and goal searching in our canvas layout. We also provided a relative metric of the infectivity of various layouts given the map and customer parameters. Finally, we implemented a intuitive model for COVID spread by measuring customer distances and increasing infectivity with less distance. From our product planning, we believe that these features should help store owners and users gain insight about shopping in the wake of COVID. What we learned: Academic models for the spread of COVID-19 are fairly simple, while simulation outcomes return intuitive results. Even an uncomplicated model can identify potential patterns and issues. What's next for Grocial Distancing: A key point of future development will be increasing the realism of the simulation. For example, the infection algorithm could change based on research of COVID spread. Further, with more development time, customer movement could be altered to detect collisions and interact more realistically with goals and other customers. Lastly, we also hope to coordinate Grocial Distancing with other utilities, such as Google services and data from app users. These developments could also see the return of the account system. Built With css html javascript Try it out github.com

https://devpost.com/software/ibm__hackathon__troubleshooters

Inspiration What it does How we built it Challenges we ran into Lots of Challenges Accomplishments that we're proud of What we learned What's next for MEDICO Built With css deeplearning django html image-processing javascript postgresql python rasa tensorflow

https://devpost.com/software/cybermike-2

App Screenshot Facebook page banner Inspiration Flash applet at https://albinoblacksheep.com/flash/mike is no longer compatible today. So I decided to continue the project in another way. What it does Provides a self help decision path for persons with suicidal or murderous tendencies. How I built it Made it using Chatfuel. Challenges I ran into Initially was supposed to use Dialogflow / Botman framework, however there are logistical difficulties in getting them to communicate with the Messenger platform properly. With time running out, the prototype was made using Chatfuel. Chat also got stuck on the first message. Did not realise that the setting in the Facebook page Messenger platform section had an option for 1st contact message that needed to be set to the Chatfuel. Accomplishments that I'm proud of The bot working properly. What I learned Using Chatfuel, linking up the Facebook Messenger platform to the proper App so that it can communicate well and not get stuck on the first message. What's next for CyberMike 2 Expanding using natural langauge processing and having more menu options with a friendlier conversational interface. Shift back to using Dialogflow due to its built-in machine learning and natural language processing. Built With chatfuel facebook facebook-chat facebook-messenger html5 messenger Try it out m.me www.facebook.com

https://devpost.com/software/virtual-malls

All shops in a shopping mall Take Away Store App (Side) All Shoping Malls Take Away App Products in the shops Inspiration Being under lockdown alone has triggered hunger and anger in some nations as we observe the WHO recommendation to national governments. However, the lockdown state affects a number of things including crippling of the economy, increase in domestic violence, hunger, depriving populations of basic needs among others. To help maintain global recommendations as well as ensuring basics are accessible to people, innovative ways, mechanisms and approaches are required to counteract the insurgency, maintaining peace and sustained lives like providing access to basics including also food and health necessities. The Takeaway application under pilot since the 20th of March, 2020 is in the market aiding solutions that liberate populations with facilities that support online ordering and delivery of basics, as they reduce contact as much as possible. To date, looking for a given product from the shopping malls in Uganda is a hectic and tiresome endeavour as you have to move from shop to another, initially to get an idea of the price and also to look for the product. This is time-consuming for customers. To overcome this many customers, go to the well-established super markets as these have organized sections and prices for the items. This, however, implies that the small shops in the same malls are always outcompeted and fail to see their 4th birthday. This platform empowers small and medium enterprises to advertise what they have. Someone can move directly from their offices and go to the ground floor in a small shop “xx” in the shopping mall “yy” to get the product he/she has identified from our platform. His/her can also use the Takeaway app so that everything is delivered to them. What it does Virtual Malls provides the public with access to any malls, navigate each, mall and order for any item from their favourite shops in any mall. Virtual malls specifically perform 2 major functions. Navigation through shopping malls ( http://globalautosystem.pythonanywhere.com/ ) – The platform has a web and mobile version that enables any one to navigate through every shopping mall, check for any particular shop of item from the shops. The mall's platform also helps the mall's manager to keep track of his tenants and also empower the tenants to set up virtual shops. Take Away App – Takeaway is a mobile application based on the android platform that enables people living in Mbarara and neighbouring districts to order and receive desired products at the comfort in their homes. The innovation is a liberating application developed for people of all kind including the youth, the old and the young. As a self-service application, Takeaway is innovatively modelled with theories of design thinking. It includes 4 core modules that realistically operative as a single coherent system. Distributed-wise, Takeaway is built with the aim of observing total social distance and avoiding all forms of contact at all levels as we fight the COVID-19 pandemic. Its core modules include: - (1) UX ( https://play.google.com/store/apps/details?id=ug.global.takeaway ) module utilized for making orders of products like Personal Protective Equipment (PPE) directly from stores and receive the products through our trained deliverers; (2) Admin module is used administering of orders as they come in. In its simplest form, store owners on the app use it to register and approve stores, deliverers, and monitor the transaction process; (3) the store module( https://play.google.com/store/apps/details?id=ug.global.jubustore ) for managing and coordinating store functions including stocking and stocking level monitor, enabling store agents, for example, pharmacies to add their product/s with pricing, receive orders and deliver the orders; (4) and lastly the delivery module used by delivering agents like Boda-Boda deliverers whenever they get orders near to them for delivery and delivery confirmation. The delivery module algorithm allows for searching for the nearest deliverer to the order source, enabling them to receive orders from a store, pick the package and deliver it to the shown address. With the UX module interacts with the delivery module delivery confirmation through displaying a barcode on delivery that a user scans at the end of the transaction. How I built it First of all the platform is being developed using the concepts of social-technical systems where we recognize the interaction between people and technology in workplaces. Furthermore, the concept of design thinking is driving the design process where the end-users are at the centre of the design. Our platform is an all in one integrated platform comprising of a shopping mall information management system managed by the mall administrator who gives tenants’ rights to initiate their own instance of an online shop, inventory management and website. The platform has both a web and mobile application version. Finally, our platform is artificial intelligence (AI) empowered to enable the shop owners to monitor and make decisions about their stock. Challenges I ran into We started working on the idea during the COVID-19 crisis and testing it with malls owners has not been very easy. Accomplishments that I'm proud of We have hosted the platform and collecting feedback from end users. We have over 50 downloads and users in less than 1 month. What I learned Physical business will take time to stabiles, online is the way to go. What's next for Virtual Malls Our next step is to do more advertisement. Built With android django python Try it out globalautosystem.pythonanywhere.com

https://devpost.com/software/natural-mask

Inspiration: To save world What it does: Personal protective product How we built it: Using homemade materials like cloth, natural herbs. Challenges we ran into: Availability of materials Accomplishments that we're proud of: Disinfectant What we learned: Unity and save nature What's next for Natural mask: Educating public to prepare and implement in all homes. Built With hardware

https://devpost.com/software/drone-as-a-virus-detector

Inspiration: To save earth with innovations What it does: Virus detector How we built it: RC car Challenges we ran into: No human involved in it. purely automated. Accomplishments that we're proud of: Blood samples will be collected without person to person contact What we learned: Challenges What's next for Drone as a Virus Detector: Implement using drone Built With hardware

https://devpost.com/software/n-a-i-t-r-a

This shows how the image data is stored for logging all the files This shows how different images are stored in their respective post code folder Inspiration N.A.I.T.R.A as it means "eyes" in regional Hindi language , we wanted our app to help the society by providing important information about the global pandemic. At the same time to help the police department in enforcing the law with the help of responsible citizens. What it does It makes the user aware about important knowledge like general information , symptoms prevention etc. of COVID-19 / coronavirus 2.Allows the user to know whether his current location lies in a containment zone or not and gives a covid tracker map about the containment zones for detailed information The current situation in India is to avoid infection spreading due to mass gathering. So naitra enables the citizens to report any mass gathering events by uploading a picture of such events to our application website. The site processes the image for metadata and sends the image file to the nearest police station which makes the local police force more aware about the areas which are left in there blind spot. ( To mimic the sending of files to different servers the app creates different folders with post code as folder name (resembling different area police servers ) and store the image image file according to its post code in respective folder ) N.A.I.T.R.A is an application which is deployed on google assistant and hence does not require any external installation How I built it The 2nd and 3rd module mentioned above are created using Python and deployed as API on a server. The Google assistant is developed using Google Dialogflow and trained to respond the queries generated in the 1st use case. The agent utilizes the API hosted for successful execution of the use case scenarios. Challenges I ran into Exploring image analysis and metadata extraction from image. Data generation for the containment zones use case. Accomplishments that I'm proud of Overcoming my challenges. Learning new technology stack and integrating them through out the development process. What I learned Image Analysis using python. API creations in python. While doing the background study for this application we came to know the seriousness for the global pandemic situation and understood that this solution could help our society in curbing this spread of infection. What's next for N.A.I.T.R.A Currently N.A.I.T.R.A can be deployed on only android smartphones. We plan to further make it cross platform available through deployment on other user voice AI such as Siri NAITRA helps the people to report the violation of one of the law i.e. Mass Gathering . We plan to cover a wider scope of complaints to be registered from the citizens and make the people more vigilant about the situation. Built With dialogflow folium html imageai node.js python

https://devpost.com/software/yourthreconnect

login Dashboard Inspiration Uganda has the highest level of youth unemployment in Africa. Of the 700,000 youth that complete formal education and join the job market every year, only 17% find something to do hence 83% of Ugandan graduates cannot find jobs. In addition, a number of people will lose their jobs after COVID-19 pandemic since the financial burden will necessitate a number of companies to reduce the number of expenses. Not only the educated people but even a number of casual workers will lose their jobs. Furthermore, a lot of Ugandans have been involved in Electronics and Textile Business with the highest importations coming from China. After the COVID-19 pandemic, a lot of this type of business will not boom as it was previously doing. Again despite the fact that the lockdown is being uplifted, some guidelines like public cars to always carry half of the full capacity will limit business prosperity. This means that the youth not only in Uganda need to get digitally connected and execute tasks/ business as teams. What it does YouthReconnect is an Intelligent Digital Platform to Empower Youth after COVID-19 lockdowns with access to potential employers, business partners, tailored training, and form innovation hubs to solve the challenges in their own communities. YouthReconnect specifically performs 4 major functions. Job finding – The platform helps the youth find job opportunities. These job opportunities could be permanent or temporary job hiring’s which could be professional or casual jobs like looking for a freelance programmer for 1 month, looking for a compound designer for 1 day. Business Partnerships – It’s time for the youth to stop setting up un necessary business competitions. The platform will empower those seeking to join others to form business partnerships like identifying a potential supplier in China (abroad) and buy goods in one shipment, whilst sending one representative, coming together to bid for bigger government or private contracts, forming saving groups like SACCOs or cooperatives and have shared access to financial support. The platform will also help local suppliers get connected to potential suppliers or contacts in other countries. Training and Mentorships – Provide technical and soft skills to the youth to increase their level of employability or self-made entrepreneurs. The platform also links the youth to some mentors from within the community for one to one mentorship sessions. Innovations – Lastly the platform provides an innovative Digital Hub, where the youth are provided skills to how to change their social challenges into opportunities, and how they can access funds through grants writing. How I built it YouthReconnect has been developed using a design thinking approach where the end users are part and central to the design process. After developing the framework of which we have validated with the potential end-user, we have now embarked on implementing the platform using the Django framework. Challenges I ran into The project seemed simple and small in the initial phase. However, on starting the developing of the project, it has actually seemed to be more broad with a number of stakeholders that we did not anticipate. The project also needs maximum publicity so that the youth can know more about it. Accomplishments that I'm proud of We are so happy that the platform has received positive feedback from the potential end users. We have validated our framework and embarked on developing the platform. What I learned The problem of unemployment in Uganda is going to be far beyond what even the authorities expect. We need to empower the youth to be innovative and turn these challenges into opportunities. We also need to embrace the power of team work. What's next for YourthReconnect Our next step is to implement and host YouthReconnect on Amazon and run Media Adverts Built With django python

https://devpost.com/software/telemedml

TeleMedML Logo TeleMedML System Architecture Deep Neural Network Diagram TensorFlow Machine Learning Shell Output iOS App Login Screen iOS App Patient Welcome Screen iOS App Historical Transactions iOS App Report New Symptoms iOS App Results Page With Start Call Option Website Transaction View Inspiration With the recent COVID-19 pandemic, the healthcare industry has been subject to unprecedented amounts of strain. Hospitals worldwide have been filled beyond capacity, and numerous medical professionals are being worked to exhaustion. As a result, any innovation that has the potential to save time, reduce exposure to the virus, and secure personal medical data in the process has the potential to save countless lives. What it does TeleMedML provides a basic disease diagnosis for a user given a list of their symptoms. The user first selects which symptoms they are experiencing from a predefined menu. This information is then passed into a deep neural network, which analyzes the given data using a trained model, and returns the diagnosed disease as well as a confidence score. The user can also enter a short list of phrases describing their symptoms, which are sent to the server and analyzed using natural language processing, returning a diagnosis. Each data transaction is added to a series of pending transactions, which are subsequently verified using a proof-of-work algorithm and annexed to a block in the blockchain. How we built it App The iOS app begins with a secure login and signup page for users. Patients are able to view the entire history of previous transactions encrypted with SHA-256 hashes and secured on a decentralized blockchain network. A user is also able to fill out a symptoms form and write additional symptoms, which is encrypted and sent to the server for analysis. If the returned values indicate a potentially significant diagnosis, a doctor and patient are connected for real time communication, ensuring that a doctor’s valuable time is spent on those who need them the most. Server The flask-based server handles secured requests from clients and encodes all data points into blocks for storage in the blockchain network. Every time a client-side transaction occurs, the data is given a unique hash, encrypted, and linked to a previous block, chaining the data set together. A recursive algorithm was developed to work backwards through the blocks and decrypt the transaction data to securely access the full data set. Alongside the server, a novel TensorFlow-based deep neural network machine learning model was also built and trained on a relevant data set. The data is reshaped on a 0 to 1 scale, regularized, and sent through 4 layers of decreasing node counts with relu and sigmoid activation functions to predict disease diagnoses based on inputted symptoms. This prediction was combined with Amazon Comprehend Natural Language Processing algorithms to analyze the connotation of written symptoms to quantify the severity of the diagnosis. Website A website was built as a healthcare portal to view all transactions made by clients. After a secure login, doctors are able to view a table containing full transaction data accessed and decrypted from the server using the recursive data access function. Challenges we ran into One of the issues we encountered early on was establishing the infrastructure for the blockchain. Most of our group had relatively little experience with blockchain prior to the project, so figuring out how to implement each block, compute its hash, and connect it to the overall blockchain with a proof-of-work validation algorithm was challenging. Another difficulty we ran into was with sending requests to the server. We received internal server errors since the server we were hosting on was outdated and insufficiently large for the TensorFlow modules that our program incorporated, so we updated the server’s Python environment and upgraded its storage capacity. Accomplishments that we’re proud of We are extremely proud of being able to successfully configure and train a deep neural network with an expansive dataset. This allows us to more accurately tailor the user’s diagnosis to his or her individual symptoms, creating a more personalized experience. We are also proud of managing to create a decentralized blockchain network using Python and encoding each transaction through a cryptographic hash function based on the current data and previous hash. The chaining functionality and the proof-of-work algorithm were also difficult to implement, so it was rewarding to be able to do so. What we learned Given the current circumstances with the pandemic forcing us to work remotely, we had to learn how to communicate effectively and collaborate virtually in order to produce the desired end result. We also learned about the workings of blockchain technology, including the hashing and validation algorithm involved to ensure the security of the chain. What's next for TeleMedML There are several future options that we can pursue with TeleMedML. Among these is the creation of a convolutional neural network that can analyze user images. The addition of this feature would be useful in diagnosing diseases with physical symptoms, broadening the abilities of our detection software. We could also integrate the project with certain hardware components, such as sensors that would measure the user’s heart rate, respiratory rate, and other vital signs to improve diagnosis accuracy. Built With ai-applied-sentiment-analysis amazon-ec2 amazon-web-services blockchain flask keras machine-learning python sashido swift tensorflow Try it out github.com telemedml.macrotechsolutions.us

https://devpost.com/software/covid-19-marketplace

Admin adding marketplaces List of marketplaces Book a marketplace After sucessful booking Scan QR QR Validator Live Analytics Inspiration What made us build this application is that, we often hear news about lockdown announcements and what people do first when they hear this is bombing the stores (panic buying) to have more essential items in hand. As a result, the spot becomes over crowded where there is a risk of virus spreading. What it does Our application is built to make users pre-book their slot for market they wish to go. Before that, the administrators / the shop owners could add the availability of their shops, maximum number of people per time slot and few related stuffs. On booking, the user would receive an QR code in the application which they have to show when they are visiting the shop on entry and exit. By this scanning, we get real time updates on how much people inside the shop currently, and many more insights in a form of dashboard. How I built it Tech stack includes Angular, React, HTML, CSS, Javascript, NodeJS, PostgreSQL, Firebase, Heroku, AWS. Challenges I ran into Dealing with conflicts was one of the challenge during development :p Accomplishments that I'm proud of What feels proud is that, this is our very first hackathon and this project gave as a courage and will power to beleive in ourself that we can built something on our own. We managed to complete these whole modules in 4 days with a 4 - 6 member team. What I learned Managing multiple services, repositories, deployment, version control, project management. Improved our skills in what all technologies we have been using. What's next for Covid-19 Marketplace Feel free to check the current version in: https://covid19-marketplace.web.app First release the web app version, and later if it goes well, thinking of converting them to mobile app :) Built With amazon-web-services angular.js bootstrap firebase heroku html5 javascript node.js postgresql react Try it out covid19-marketplace.web.app marketplace-administrator.web.app marketplace-app.web.app marketplace-scanner.web.app marketplace-dashboard.web.app

https://devpost.com/software/covid-tracker-frjgi5

Inspiration During this pandemic, most people are quarantining at home trying to stay safe. But what about the people that don't have a home? During this time many police forces are removing homeless camps across cities, with many having now where to go and the government sometimes does not provide or expand it's alternative housing spaces. At the same time, hotel and housing properties listed on airbnb and other media are sitting without any occupancy as travel has become extremely limited. We felt that these rooms/homes with no one using them can be put to better use to help out the community and also possibly have a hand in helping flatten the curve. Another problem in this ongoing situation is that tons of farmers are forced to throw away their products as there has been less buying. What it does Homely.space is a web app designed to be easily accessible by everyone and provide all the facilities needed for the user to fulfill their purpose. There are two different people that would use the application. One is someone who wants to list their property on the database for homeless people to use. Another is someone who is seeking a temporary place to stay. People who want to enlist their housing can do so by signing up and providing the home address which will then be added to our database. The person who is seeking a home can also sign up and click the "locate me" button which will get their address and find the nearest available home for them. Once a home has been found, the two people will be put in contact with each other via phone or email. Another feature that is available in the application is a Request Food option. As farmers are throwing away they produces, we though that we can save some of this waste and connect a consumer straight to a farmer. In this part, a person can sign up as a volunteer that helps get food from a farm to a purchaser, which would help reduce good products going to waste. There are other small features such as a chat bot in which one can diagnose themselves and also get the latest updated data for covid. How we built it We built the application using JavaScript web framework, Express.js which is a part of Node.js. Simple endpoints were created to the login and registration, and a database was created that hold a users information. The database also stores the address for housing that people are offering to the people in need. When a house provider login in, he/she is asked to add the address of the house they want to give temporarily, which is then sent to the data base. When a shelter seeker uses the app, he/she enters their first and last name and click a button which allows for us to get the lat and long coordinates of their current location. Through an algorithm,using googles geolocation api and google distance matrix api, we find the house closest to their current location and provide them with the owners contact info. This logic is also used for when requesting food. The farmers would register their address, and the purchaser would enter their address. The purchaser then is connected to a volunteer that would be able to get the fruits and vegetables from the farmer to the buyer. Challenges we ran into We initially struggles to create a layout of the whole application, but were able to figure that out with some rough drawings. Another challenge was that the team members are all from different time zones, so communication with very difficult. Another challenge we ran into was understand database and getting it to work how we wanted it to. Since this was the first time some of us used firebase and google apis, we had to read documentations to understand everything about the two. Accomplishments that we're proud of There are a couple of things that we are proud of. One of them is that eventually we were all able to work together and understand what everyone was doing despite the time difference. We are also proud of the fact that throughout the project we were able to learn to use new features such as apis and databases that we did not know before the hackathon started. One important accomplishment is that we were able to overcome a huge time constraint and come up with a prototype of an idea that has potential to change people's lives. What we learned We learned how to set-up and use Google's geolocation and distance matrix apis, create a database and extract from it and using a new framework to built the website on. What's next for Homly.space The next steps for Homly.space is to create additional features such as having a donation tab where, people who are seeking shelter can donate whatever they feel like to the host (as anything helps). Another feature that can be added is that instead of having a web-page we could make some sort of chat bot that people can use to find nearly housing and also add housing. In addition, we can also have some sort of rating function, where the host can rate the people who stayed at their listing so future hosts can know how the people are treating their properties. Built With firebase gcp google-maps html5 node.js php Try it out github.com

https://devpost.com/software/zesti

Elevator Pitch Billions of dollars are being lost every day as social distancing measures remain in effect. Most restaurants have expressed that they cannot solely survive on takeout or delivery orders. Major staff layoffs and furloughs have already occurred throughout the country and people are struggling to support their families. With almost 10% of the US workforce employed in the restaurant industry, our team knew we had to help. That’s where Zesti comes in. With Zesti, customers can order MealKits from their favorite local spot and cook live with the chef and friends. In the consumer app they will get a curated page of dishes to cook based on their preferences. MealKits include all necessary easy ingredients for the recipe, along with a live or on-demand video session of how to cook. Our live cooking class is a great interactive way to get expert help on cooking while chatting with friends and having a good time. To enable this easy to use experience on the customer side, we knew the restaurant app had to be easy to use. So we developed a simple yet thorough app for restaurants. Restaurants can sign up for Zesti and start selling right away. They can choose their own prices, add live sessions, manage pre-recorded sessions, and see orders they need to fulfill. With the live dashboard chefs and owners can host a live session with ease. They are able to see what step each participant is at, give advice through video, and view the chat for any questions. This helps create a strong community bond between restaurant owners and customers. 78% of the restaurants we surveyed said they are looking into creating new revenue streams for their businesses, and Zesti gives them the tools and power to do this. We can't wait to help restaurants with our product to deliver high-quality experiences in these tough times. We truly believe both customers and restaurants will love Zesti. Inspiration Restaurants have lost a large portion of their revenue due to the pandemic, and are some of the most important businesses in the economy. With such strict social distancing policies, the restaurant experience will be greatly affected. For in-person dining, restaurants will no longer be able to fit in as many customers as they did pre-COVID. When the pandemic ends there will be a new normal, and in that new normal it seems almost certain that restaurants will not be able to operate at full occupancy. This will have a profound impact on businesses that rely on the in-person dining over delivery and takeout options. At Zesti, we are lovers of food and entrepreneurs. After seeing that some of our favorite restaurants were closing we knew an important problem needed to be solved. We respect these small business’ hustle and creativity and wanted to craft something for them. In countless engineering classes we were taught to “pivot”, and Zesti will create a tool that will allow them to “pivot” their business in these tough times. What it does Our platform Zesti aims to help restaurants replace the revenue streams that they lost because of the virus, provide a virtual experience for customers looking for a different eating experience, and help restaurants sustain their vital role in the economy. The competition for our platform is services such as Blue Apron, Hello Fresh, MasterClass, and The Table Less Traveled. We believe that our platform will be a valuable addition to the market because it has features that no other platform in the market has. Our platform provides our customers with access to personalized ingredient kits from their favorite restaurants and access to instruction from restaurant chefs. Zesti enables consumers to eat dishes from their favorite restaurants as well as picking up a new skill. Unlike the other food box services Zesti incorporates local restaurants in the equation for same day pickup or delivery. Consumers will be able to register for a class from any restaurant offering classes. The registration includes a tailored kit of ingredients prepared by the restaurant, and access to a live class with a chef. The live classroom is highly interactive on both the consumer side and the instructor side. The classroom is also highly secure since only users who are registered to the class will be allowed into the class. During the class participants will be able to follow along with the Chef, and notify the chef if they are having trouble. After the class has ended it will automatically become available for users to watch on-demand at any time. This allows restaurants to still sell MealKits with a video, without having to do a live class. Ten minutes before the class is scheduled to start, the chef can begin the class from their device. Once the chef begins the class participants will get a notification that the class has started. The chef will have their own tailored dashboard where they can see the recipe instructions, the status of how the participants are doing with the current step, a preview of a classroom group chat, and finally a preview of a participant livestream. While the chef is performing each step they will be able to see how the participants are progressing with each respective step. If the chef sees that a lot of customers are having trouble with a specific step then the chef can spend more time on that step. This highly interactive and personal classroom will keep customers coming back, and more importantly give them a valuable cooking education from restaurants in their community. How we built it Zesti was built on a technology platform primarily using Amazon Web Services. In order to ensure secure user authentication, we are using Amazon Cognito. Within Cognito, we use Amplify CLI, which allows us to integrate and manage our AWS services, to create a user pool group for consumers and one for the businesses. Additionally, we are utilizing DynamoDB databases in order to store user account information and S3 as a cloud backup for all of our data. Finally, we make use of Amazon Personalize to tailor our recommendation engine. The frontend of the project will be built using React Native. This will allow us to easily develop for multiple devices for a quicker launch and broader customer reach. When implementing a video conference platform we have to consider the ITU (International Telecommunication Union) standards. The ITU has three standards for video conferencing. They are ITU H.320 which is a standard that is a recommendation on what protocol suites to use, ITU H.264 which is the compression algorithm used to achieve highly error-free video streams over a regular IP network, and ITU V.80 which is a standard for video conferencing over POTS (Plain Old Telephone System). It was important for the team to follow industry standards in order to enable widespread adoption and use of the platform. Challenges we ran into The team realized that none of us have experience owning or operating a restaurant so figuring out exactly what should and should not be included in our platform was challenging. In order to combat this challenge, we sent a survey out to many businesses in order to get their opinions on specific features and a general willingness for participation. Next, figuring exactly what our app’s function should be was tricky at first and we had a lot of ideas such as a learning platform or social media platform but did not have a true specialty area. To solve this, we spoke with a mentor in order to really narrow down our idea and have a true vision for what we want our final product to be. Lastly, creating a script and video that perfectly captured the service that we were trying to provide was a tough challenge. After a lot of tutorials and trial-by-error we were able to use Adobe After Effects and Affinity Designer to create digital assets that we could animate to convey our company. Accomplishments that we're proud of There are several accomplishments that we are proud of in this project. The first is the fact that our product helps to tie our communities together. During this pandemic, we have become more isolated through social distancing. This app will help keep close-knit communities together and support local businesses. Since restaurants can serve as the meeting places and backbones of our community - this is an important role for our app to fill. Further, we are proud that within a week we were able to develop a functional wireframe. This will allow a walkthrough to potential customers both from restaurant owners as well as users. Based on our use of Adobe XD, a link can be placed on any web page to show a preview of our design. Going further, this will also allow for a more seamless construction of the app, as the functionality and flow is completely defined. Finally, we are proud of the data and connections that we made with restaurant owners and chefs. We envisioned a lean startup for our business. Establishing what our target community wants from our product (and establishing that they want it in the first place) is a key step in a lean business model. The data from our survey allowed us to tailor the product we are presenting to what the restaurant industry most wants in a post-COVID world. Thus, we can make a solution that best suits the need. What we learned The team learned a bunch of new skills and programs like AdobeXD, AWS, React, and more. More importantly, we really learned how to create a product that was focused and detailed enough to be viable in the real world. Another thing we learned was balancing the needs of various stakeholders in a product. We had many discussions on what features needed to be prioritized for restaurants and consumers. For example, we knew we had to dedicate a lot of time to developing a great live host experience for chefs, so we made sure it was detailed and as easy to use as possible. What's next for Zesti So what is next for Zesti?! The team is currently in the process of surveying restaurant owners across the country to help mold the app to their needs. For Zesti to succeed, businesses need to love how simple and easy it is to offer MealKits and lessons to customers. On the business end, Zesti is planning to partner with local businesses to advertise to customers. This will give free advertisements to both small restaurants that need our help, and will help the adoption of our app. We are also working on videos and documentation to onboard restaurants and prepare them for hosting live classes. We will be a resource to help them produce high-quality experiences. Lastly, on the development side of things the team is looking to build out our platform on both iOS and Android devices. Built With adobe amazon-dynamodb amazon-web-services amplify cognito livestream react reactnative s3

https://devpost.com/software/covhelper-jb6nku

Inspiration All over the world, the spread of the pandemic is a persisting problem. As we saw people of all ages are affected by the problem specially older people, and people with pre-existing medical conditions (such as asthma, diabetes, heart disease). In addition, governments have to deter the spread of fake news that is making it harder to flatten the curve. That's why the best solution until now is tracking the virus, keeping the citizens aware by updating them about the current situation and finally improving their behaviour to respect social distancing . What it does CovHelper is a mobile application (implemented on both Android & iOs) with 2 versions one for citizens and the other for medical establishments . The application will help the government to improve citizen’s behaviour, keep the user updated and safe by tracking of the user status ( by adding daily symptoms: his symptoms will be available only for hospitals so we can contact to have a test if needed ) and his contacts (who is infected and who was in contact with the victim) and last but not least allows the user to consult a list of nearest hospitals and donate to organisations and funds raised to defend COVID-19 outbreak . For the version designed for medical establishments a medical assistant will be given an account to sign in and update positive tested cases. For citizens they have the ability to register and sign in. When registering, the patient answers a collection of questions (the list can be modified dynamically). The answers of each patient will be saved in the database and an algorithm will automatically order the list of patients from most critical or urgent to least critical. This algorithm will be defined with a CORONA specialist. The responses will also allow us to have a list of the people the patient has contacted and their family members. The questions differ depending on the case, whether you come from abroad or not . Once connected, you can consult the Dashboard, where you can check: • Your status and Old Symptoms ( these symptoms will be available only for hospitals so we can contact to have a test if needed ) • Add new symptoms • Volunteering (helping around) • Make a donation • Quarantine counter • News: Just display news related to Coronavirus (title contain Corona) => depending on your localisation country and the language you have chosen these news will be dynamically updated The api we have used to get news is https://newsapi.org/ because it provides verified news • Trackpad: The user ca check his status if he’s infected by the virus or not who infected who and who encountered an infected How we built it The application will be ready to launch within two weeks so that we can catch up and track the virus all over the world. The application is available with English, French and I'll soon add Arabic to ensure everyone can connect within the app. CovHelper is developed with react native to make sure we get the application as soon as possible on both android and iOs devices. We used material design for modern UI framework. Apis will be developed using Firebase , we thought this will be the fastest way to do it. We used different APIs to get data such as NewsAPI and Postman apis. Updating a patient status is only entered by the medical establishments, this will approve the authenticity of the app and prevent false positives or self-reporting, which might lead to falsification of records. Checkout app presentation with different views here Challenges we ran into • Add Location Check coronavirus victims’ position : For iOs it is possible to get a notification when the location did change, this will be enough for us. When location did change, we will start a call to the API telling the server that our position did change. For android, if we keep a notification of our application no dismiss-able, we can keep asking for location. This does fix the problem too. One last problem for iOs, if our device restart, the user need to restart the application to make sure we are requesting location again. We don’t have this problem for android because we can use on Reboot broadcast receiver to make sure we restart our service every time we restart the device. Accomplishments that we're proud of We are mostly proud to contribute in the developing a solution that will reduce the spread of the virus throughout the country while finding a vaccine to cure the pandemic with the tracking method. It will improve awareness and help medical stuff at the frontline in order to keep everyone healthy. We specially appreciate the wide range of offered resources, the freedom in making your work plan and the overall friendly atmosphere . We are able today to apprehend projects with a good perspective and to propose adequate solutions to the issues addressed and we are really thankful of that. This project was on top 3 finalists in HackTheVirus Hackathon organized by GoMyCode in Tunisia. This Hackathon allowed us to get in touch with great minds that's why we decided that everyone still can contribute to this project: designers, developers, idea holders… we will provide open source code for developers just to make sure we all are making a difference. What we learned We should mention we were able to encounter great minds from all over the world that really care about this crisis. We had the chance to exchange ideas, motivate each other ,learn from one another and make great friends through slack workspace . Briefly, This experience helped me sharpen the spirit of initiative and even more boost my taste for challenge and leadership . What's next for CovHelper We plan to get the app deployed as soon as possible for that we'll need : • Ensuring a sustainable cost of running such an app in the cloud storage • Government entity or public health organisation commission to track data. • Medical system contribution to update the status of patients. We also plan to add these features : • Location : Consult list of nearest Hospitals : Localise hospitals nearby so that the user can contact them in case of urgency Notification : we send a notification to the user: o When he enters a new building o When the distance between the user and a Corona case is < to 100 meters This application will guide us through this period and even after quarantine just to ensure everyone of us gets back to his normal lifestyle and why not have a better lifestyle. The app will remain a great tool to donate, volunteer to hospitals and charity organisations and we will allow people in need to post their problems. It will be a platform to give and get Help. Built With android firebase ios javascript machine-learning react-native Try it out github.com drive.google.com

https://devpost.com/software/the-virtual-medic-fwbdr1

LOGO Disease Prediction Example Disease Prediction Example Disease Prediction Example Barcode Scanner backend Medicine Reminder Medicine Reminder Setup Inspiration While access to healthcare and hospitals remain very delicate in these times, we are developing a full AI based model that can be easily used and deployed to automate the process of patient hospitalization. What it does As the initial part of the project we have developed the health application serves several purposes. To begin with, the app has a Disease Predictor, which takes symptoms as the user input and predicts the disease based on the same. The application also implements a Barcode Scanner that scans the barcodes on different medicines via the camera and displays the details about the same like usage, effectiveness and side effects. The app also lets the user input their daily medication including the number of doses and their timings. On adding, the app would send the user a notification at every dosage time. How do we aim to automate hospital interface with the same ? Through the disease prediction model, i further aim to deploy a consultation mechanism that based upon the user symptoms connects us with the related doctor who specializes in the same field, for e.g orthopaedics, psychiatrists, general surgeons etc. Deployed in a hospital, the same can be used to assist patients with database management as well consultation management. How I built it The app is completely based on python with android being used as the front end framework. Accomplishments that I'm proud of The accuracy of the model and its ability to predict upto 41 diseases based upon the 132 different symptoms provides evidence of the advancements that can be made in this field. What I learned Being a machine learning enthusiast, i had never used android for deploying a front end to my application, hence android is the very main thing that i acquired from the project What's next for The Virtual Medic I plan to work on the UI of the application as well as plan to integrate a virtual video conferencing tool that can connect the user to nearest doctor for health consultation. Built With android flask keras machine-learning python Try it out github.com

https://devpost.com/software/what-should-you-do-today-during-quarintine

We wanted to create a project that could benefit people staying at home in the wake of the COVID-19 pandemic. As boredom is setting in, people are looking for things to do to stay busy and entertained. Our program selects a specific and personalized activity for the user based on their interests. The program begins with a short quiz that selects a category from TV entertainment, baking, nature, and music. The user is prompted with more questions to select the exact activity for the user such as a specific movie or tv show based on genre, streaming service and type of media and even provides a reelgood.com link to make things even easier. The program can also find you a recipe based on the amount of servings that you want to make. If you want to listen to new music, the program finds a personalized music recommendation based on each answer you choose. It can also find a nature-related activity based on your desired level of activity. The program is built using c++. It uses input and output redirection, file i/o, node structs, linked lists and inheritance. A challenge that we faced was the time constraint. We were not used to having to do a whole project in such a short time frame, so we had to choose a project that we could do in one day. We also have never made a project from scratch before. We normally work with starter files, so starting ourselves this time was a challenge. We are proud of the fact that we overcame these challenges to make a functioning program. There are many potential future improvements for this project, as there are so many possible activities. We could add more categories to include things like art and exercise. We also want to make a user-friendly interface that is visually appealing and easy to use. With this, we hope people are reminded how fun it can be to stay safe and inside. Built With c++ Try it out github.com

https://devpost.com/software/pneumoscan-an-ai-radiology-tool-for-covid-19-pandemics

Fig. 1: Map of Covid19 cases around the world (as of 4/30/2020) Fig 2: Top 10 countries with most COVID-19 deaths Fig 3: Current chest X-ray diagnosis vs. noval process with CovidScan.ai Chart of wait-time reduction of AI radiology tool (data from a simulation stud reported in Mauro et al., 2019). Fig. 5: Process of CovidScan development Demo of web-app: https://www.cv19scan.site/ (Please use Internet Explorer, or Firefox, our web-app currently doesn't support Chrome) Dataset: For the data analytics of COVID-19 pandemics, we used data collected by the Johns Hopkins University Center for Systems Science and Engineering updated on 4/30/2020. For the chest X-ray detection models, we used combined 2 sources of dataset: The first source is the RSNA Pneumonia Detection Challenge dataset available on Kaggle contains several deidentified CXRs with 2 class labels of pneumonia and normal. The COVID-19 image data collection repository on GitHub is a growing collection of deidentified CXRs from COVID-19 cases internationally. The data is collected by Joseph Paul Cohen and his fellow collaborators at the University of Montreal Eventually, our dataset consists of 5433 training data points, 624 validation data points and 16 test data points. Inspiration What will be working situation for medical staff in hospitals during and after the COVID-19 pandemic? How can the medical staff quickly and securely log in and perform PPE safety check while dealing with a huge influx of patients in critical conditions? How can we automate the process of COVID-19 diagnosis so precious time can be saved for both medical doctors and the patients? How can our solution for hospital later be scaled and implemented to be a essential tool for automating the daily operation at hospital even after the COVID-19 pandemics is over? To answer these core questions, we did some background research to identify the main challenges in order to develop the best solutions around those: COVID-19 Pandemic: Fig. 1: Map of Covid19 cases around the world (as of 4/30/2020). Our team created the map based on data collected by the Johns Hopkins University Center for Systems Science and Engineering. As we see from the map above and the pie chart below, COVID-19, previously known as the novel Coronavirus, has killed more than 63,860 people and infected over 1,067,061 people in the United States alone, topping all other countries around the world. This number is continuing to grow every day. Fig. 2: Top 10 countries with most COVID-19 deaths. The 3 main problems occur in the healthcare system during the pandemics are: 1. Confidentiality: As you may see on the news, hospitals all over the U.S. (New York, Chicago,California…) and other countries (Italy, Spain…) are flooded with a huge influx of patients with critical conditions. With the increasing workload for the medical staff, patients’ confidential information may be put at risk if unauthorized personels can hack into the electronic medical record system. Thus, there is a need for a fast and secured method for medical staff to log in to the electronic medical record platform, so that the staff can move quickly with patients’ information inputting and still remain compliant with HIPPAA (Health Insurance Portability and Accountability Act). Badge scanning will be highly secured solution for this problem. 2. PPE Safety Check: According to CDC, during COVID-19 pandemics, all healthcare workers should follow strict guidlines and protocols from OSHA regarding wearing PPE. All of the PPE prevents contact with the infectious agent, or body fluid that may contain the infectious agent, by creating a barrier between the worker and the infectious material. Gloves, protect the hands, gowns or aprons protect the skin and/or clothing, masks and respirators protect the mouth and nose, goggles protect the eyes, and face shields protect the entire face. N95 masks are the PPE most often used to control exposures to infections transmitted via the airborne route. Therefore, checking medical staff’s PPE safety protocol is especially crucial during this pandemics. 3. Long wait time for COVID-19 chest X-ray result: Fig 3: Current chest X-ray diagnosis vs. novel process with CovidScan.ai Patients can first be screened for flu-like symptoms using nasal swap to confirm their COVID-19 status. After 14 days of quarantine for confirmed cases, the hospital draws the patient’s blood and takes the patient’s chest X-ray. Chest X-ray is a golden standard for physicians and radiologists to check for the infection caused by the virus. An x-ray imaging will allow your doctor to see your lungs, heart and blood vessels to help determine if you have pneumonia. When interpreting the x-ray, the radiologist will look for white spots in the lungs (called infiltrates) that identify an infection. This exam, together with other vital signs such as temperature, or flu-like symptoms, will also help doctors determine whether a patient is infected with COVID-19 or other pneumonia-related diseases. The standard procedure of pneumonia diagnosis involves a radiologist reviewing chest x-ray images and send the result report to a patient’s primary care physician (PCP), who then will discuss the results with the patient. _Fig 4: Chart of wait-time reduction of AI radiology tool (data from a simulation stud reported in Mauro et al., 2019). _ A survey by the University of Michigan shows that patients usually expect the result came back after 2-3 days a chest X-ray test for pneumonia. (Crist, 2017) However, the average wait time for the patients is 11 days (2 weeks). This long delay happens because radiologists usually need at least 20 minutes to review the X-ray while the number of images keeps stacking up after each operation day of the clinic. New research has found that an artificial intelligence (AI) radiology platform such as our CovidScan.ai can dramatically reduce the patient’s wait time significantly, cutting the average delay from 11 days to less than 3 days for abnormal radiographs with critical findings. (Mauro et al., 2019) With this wait-tine reduction, patients I critical cases will receive their results faster, and receive appropriate care sooner. What it does Using the power of pretrained machine learning models from open source, CovidScan.ai is created as a full-scaled AI tool for radiology clinics and hospitals. It can automate the process of security log-in, PPE safety check for medical staff and assist radiologists determine sign of COVID-19 on chest X-ray images with high accuracy indicates pneumonia. This tool of cutting edge technology can be used to reduce the workload for clinicians, and speed up patients’ wait time for pneumonia lab results in this critical time of the COVID-19 pandemic. Fig 5: Deployment process of pretrained ML model to the web-app As explained in the figure above, the CovidScan web-app includes 3 main AI components: 1. ID Badge Scanner: For security purpose, only authorized personel can access to the web-app, which contains patients’ confidential health information (name, date of birth, chest X-ray, medical history…). Hence, the web-app will use pretrained scan the medical’s badge to grant them access to the software. 2. PPE Safety Check: Due to hospitals/clinics’ strict guidelines in PPE usage, especially during this COVID-19 ourbreak, the web-app will ask the medical staff if he/she is in direct contact with patients for chest X-ray taking. If yes, then the web-app witll use AWS pretrained to check for medical staff’s PPE to see if the staff follow the safety protocols to minimize any exposures to the disease. If the medical staff passed both the secured check and safety, he/she can move on the the next step. 3. COVID-19 Chest X-ray Testing: In the last step, the medical staff take patients’ chest X-ray images using the specialized machine and then upload the taken images to the database of web-app for testing for sign of COVID-19 infection or bacterial pneumonia. It is due to the fact that an AI system can review, highlight the pneumonia sign and classify each X-ray image all in less than 10 seconds (comparing the radiologist’s 20 minutes that we mentioned earlier), and it can do that same task effortlessly for 24 hours without taking a break. This time cut is especially critical in the time amid the pandemic of COVID-19. With this spreading rate, it will be overwhelming for radiologists to review a massive number of chest X-ray images of potential COVID-19 infected patients. With the assistance of CovidScan.ai, it can automatically highlight the suspected signs of pneumonia for the radiologists and speed up the process of chest X-ray review. Therefore, more COVID-19 positive-tested patients will get their result back faster and receive appropriate care sooner to prevent the spread of the virus. How we built it Employee Badge Scanner: We developed this feature using the open-source python library Pyzbar. We have written the script in the JQuery which sends the snapshots from the live camera feed to the inference model at the backend. It can read one-dimensional barcodes and QR codes present on the employee’s ID badge. We implemented this feature to work with a snapshot of employees’ ID badge. Link: https://pypi.org/project/pyzbar/ PPE Safety Check: We developed this feature using the open-source TensorFlow model for face mask detection. The backbone network only has 8 Conv layers and the total model has only 24 layers with the location and classification layers counted. The dataset is composed of WIDER Face and MAFA datasets. We have written the script in the JQuery which sends the snapshots from the live camera feed to the inference model at the backend. It works with live footage from any sort of cameras and detects people not wearing a face mask. Link: https://github.com/AIZOOTech/FaceMaskDetection Chest X-ray Classification: For this feature, we developed a Pytorch model. This project’s goal is to draw class activation heatmaps on suspected signs of pneumonia and then classify chest x-ray images as “Pneumonia” or “Normal”. For this project, we are going to use a dataset available at Kaggle consisting of 5433 training data points, 624 validation data points and 16 test data points. C. For the model, we load the pre-trained Resnet-152 available from Torchvision for transfer learning. ResNet-152 provides the state-of-art feature extraction since it is trained on a big dataset of ImageNet. ResNet-152, as the name sounds, consists of 152 convolutional layers. Due to its very deep network, the layers are arranged in a series of Residual blocks. These Residual blocks skip connections to help prevent the vanishing gradients which are a common problem with networks with deep architecture like ours. Resnet also supports Global Average Pooling Layer which is essential for our attention layer later on. For the attention layer to draw the heatmap, we use the global average pooling layer proposed in Zhou et al. Global average pooling layer explicitly enables the convolutional neural network (CNN) to have remarkable localization ability. We achieve 97% accuracy on the training dataset and 80% on the testing dataset. Web development: The trained weights of the deep learning models are deployed in a form of Django backend web app CovidScan.ai. While the minimal front-end of this web app is done using HTML, CSS, Jquery, Bootstrap. In our latter stage, the web-app will then be deployed and hosted on Debian server. Technical Requirements: The packages required for this project are as follows: Torch (torch.nn, torch.optim, torchvision, torchvision.transforms) Django Numpy Matplotlib Scipy PIL Tensorflow jQuery Challenges we ran into This hackathon project was a very different experience for us which challenged us throughout this project with the AWS sagemaker. This is the first time we all were working with AWS sagemaker and creating endpoints of the pre-trained TensorFlow model. Also, understanding curated models and determining their accuracy was a little bit challenging for us. Even after successfully deploying the model’s endpoints, calling Amazon SageMaker model endpoints using Amazon API Gateway and AWS Lambda gave us a very hard time. Accomplishments that we're proud of We manage to finish the project in such a limited time of 2 weeks in our free time from school and work. We still keep striving to submit on time while learning and developing at the same time. We are really satisfied and proud of our final product for the hackathon. What we learned Through this project, we learn to implement a complicated image-recognition deep learning models from AWS marketplace. We also learn the process of developing a mini data science project from finding dataset to training the deep learning model and finally deploy & integrate it into a web-app. This project can’t be done without the efforts and collaboration from a team with such diverse backgrounds in technical skills. What's next for CovidScan: In the next 2 months, our plan is: We will raise fund to invest more into the R&D process. We will partner with research lab to collect more dataset and find hospitals to test our solution. One of our memeber has published his newly collected dataset on this open-source github: https://github.com/nihalnihalani/COVID19-Detection-using-X-ray-images-/ Regarding our R&D, we plan on improving the performance of the platform, preferably by reading more scientific literature on state-of-art deep learning models implemented for radiology. We also plan to add the bound box around the suspected area of infection on top of the heatmap to make the output image more interpretable for the radiologists. We are working to implament the multilabeling model of COVID-CXR on our dataset to improve our application. This model is published by The Artificial Intelligence Research and Innovation Lab at the City of London's Information Technology Services division and has accuracy 0.92, precision 0.5, recall 0.875, auc 0.96. In many pieces of literature, they mentioned developing the NLP model on radiology report with other structured variables such as age, race, gender, temperature... and integrating it with the computer vision model of chest X-ray to give the expert radiologist’s level of diagnosis. (Irvin et al., 2019; Mauro et al., 2019) We may try to implement that as we move further with the project in the future. With the improved results, we will publish these findings and methodologies in a user-interface journal so that it can be reviewed by expert computer scientists and radiologists in the field. Eventually, we will expand our classes to include more pneumonia-related diseases such as atelectasis, cardiomegaly, effusion, infiltration, etc. so that this platform can be widely used by the radiologists for general diagnosis even after the COVID-19 pandemics is over. Our end goal is to make this tool a scalable that can be used in all the radiology clinic across the globe, even in the rural area with limited access to the internet like those in Southeast Asia or Africa. References: Crist, C. (2017, November 30). Radiologists want patients to get test results faster. Retrieved from https://www.reuters.com/article/us-radiology-results-timeliness/radiologists-want-patients-to-get-test-results-faster-idUSKBN1DH2R6 Irvin, Jeremy & Rajpurkar, Pranav & Ko, Michael & Yu, Yifan & Ciurea-Ilcus, Silviana & Chute, Chris & Marklund, Henrik & Haghgoo, Behzad & Ball, Robyn & Shpanskaya, Katie & Seekins, Jayne & Mong, David & Halabi, Safwan & Sandberg, Jesse & Jones, Ricky & Larson, David & Langlotz, Curtis & Patel, Bhavik & Lungren, Matthew & Ng, Andrew. (2019). CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison. Kent, J. (2019, September 30). Artificial Intelligence System Analyzes Chest X-Rays in 10 Seconds. Retrieved from https://healthitanalytics.com/news/artificial-intelligence-system-analyzes-chest-x-rays-in-10-seconds Lambert, J. (2020, March 11). What WHO calling the coronavirus outbreak a pandemic means. Retrieved from https://www.sciencenews.org/article/coronavirus-outbreak-who-pandemic Mauro Annarumma, Samuel J. Withey, Robert J. Bakewell, Emanuele Pesce, Vicky Goh, Giovanni Montana. (2019). Automated Triaging of Adult Chest Radiographs with Deep Artificial Neural Networks. Radiology; 180921 DOI: 10.1148/radiol.2018180921 Wang, L., & Wong, A. (2020, March 30). COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest Radiography Images. Retrieved from https://arxiv.org/abs/2003.09871 Built With matplotlib numpy pil pytorch1.0.1 torchvision0.2.2 Try it out gitlab.com www.cv19scan.site

https://devpost.com/software/corona-hangman

Home Screen New Game. The Player is Shown a Hint Win Alert. Player is Shown How Many Guesses They Used Lose Alert. Player is Shown the Correct Answer Inspiration As we are currently in the midst of a pandemic, we wanted to create an application which would be fun, yet intellectually stimulating for children as they find themselves experiencing this new reality while living with the threat of COVID-19. Corona Hangman seeks to teach children interesting and educational facts about COVID-19 so they will be better prepared in their day-to-day lives. What it does Corona Hangman is an educational game which allows the player to complete the given COVID-19 fact by guessing the letters which make up the missing word(s). If they do not guess within a certain number of allowable attempts, then the man unfortunately gets hanged in the game and they lose. The more they use this app, the greater amount of knowledge they will digest, which will assist them in their everyday lives as they try to stay safe against COVID-19. How we built it The game was built entirely in Swift using the UIKit framework. No third party libraries were used. For the UI, we wanted it to look like actual drawings on a whiteboard so we drew all the visuals by hand. For the words, we created two text files, one that holds the words, and one that holds the hints. These are randomly picked and the beginning of each round. We made it so that the user gets 7 incorrect guesses before they lose. They select letters from a grid of buttons placed at the bottom of the screen. If they guess the word correctly, they are told they have won and how many guesses they took. Challenges we ran into Due to the hackathon being forced to be online, it was hard to communicate with other team members as it was more restricting than when members are able to communicate face-to-face. Another major challenge that we faced was strategically dividing tasks amongst the team members in accordance with each individuals' expertise. With time, we were able to assess each others' skills and divide work accordingly to achieve our goal. Accomplishments that we're proud of Despite the circumstances caused by the current pandemic, we were able to work cooperatively and finish the project on time. Moreover, each of us made sure to work with a tool/technology which we had never used before, so that the learning experience was maximized. Furthermore, we are very proud that we managed to efficiently work together, even though we were miles away from each other. What we learned This project was indeed challenging, however, this forced us to grasp a better understanding of app development. Finally, we learned that regardless of the hurdles, we are able to accomplish anything if we put our minds to it. What's next for Corona Hangman We aspire to expand our horizons and have Corona Hangman ready for any future pandemics or viral outbreaks, so it will better prepare children against what is to come. For instance, as per the Centers for Disease Control and Prevention, approximately 540 children died from H1N1 flu within the first six months of the viral outbreak. If only those children were somewhat better prepared, they may have had a better chance in survival against this kind of a deadly outbreak. At the end of the day, we want to save the lives of as many children as possible. Furthermore, we wish to arrange appointments with educational institutions to display and demonstrate our application to the students directly, and have troubleshooting and Q&A sessions every week just in case the children do not know how to utilize our product as intended. Domain Name Our domain.com registered domain name is http://LetsHangCorona.online Built With python swift Try it out github.com

https://devpost.com/software/an-innovative-and-improved-approach-to-prevent-treat-covid

AutoCAD design with sensor Inspiration Our goal and inspiration was to improve our idea as more of a at home solution and having a more confident drug delivery when approaching COVID-19 patients. What it does The approach is a treatment plan for mild COVID-19 cases and serve as a therapeutic approach. We used a nebulizer with sensors so the patient can be confident the drug will get to the lungs so it can heal faster and decrease the inflammation. How I built it Improved Aerosolized Drug Delivery Treatment and Therapy Plan Grace Miguel, Olivia Poplawski, Tara Ravoli, Kelly DiResto, Ava Tartaglia Proposed Improvements The team has moved away from liposomal delivery of a corticosteroid because the steroid puts strain on the body and causes fever-like symptoms. Rather than using a steroid, the team has implemented the use of an anti-inflammatory drug called colchicine. Furthermore, the preferred method of the antiviral drug that battles COVID-19 is in the pill form because it will be dispersed in the bloodstream faster than it would in an aerosolized form. Our improvements should be used for mild COVID-19 cases and serve as a therapeutic approach. Fluid Mechanics - Does Liposome work? Liposome will get to the lung and alevoli Liposome can localize the action of inhaled drugs in the lung, improving the therapeutic outcome. Use mesh nebulizer for most efficiency[least loss of drug]- large mesh apertures are less disruptive to liposomes than jet nebulizers, especially when the vesicle size is small before entering nebulization. Inhaled drug particles should be ‘fine particle fraction’(FPF) “particles should be smaller than 5 or 6 µm, with particles smaller than 2 µm being the most suitable for deposition in the alveolar region”(Rudokas). After COVID the lungs of patients are being damaged.and it would be hard to fully get the correct amount of drug to the patient Researched Drugs Hydroxychloroquine - Ava & Kelly Immunosuppressive drug and anti-parasite Traditionally treats/prevents malaria, as well as arthritis and lupus- its a positive that it has already been used in humans Trump claims to be taking daily doses of it “Hydroxychloroquine is being used to try and stop coronavirus from spreading inside your body. It is not yet known if hydroxychloroquine is a safe and effective treatment for COVID-19, and this use is still experimental.” Researchers have been interested in chloroquines as an anti-viral agent for some time A study in Virology Journal in 2005 found that chloroquine inhibited the closely related Sars virus in primate cells in lab conditions chloroquine could quell the spread of SARS-CoV when applied to infected human cells in culture Chloroquine disrupts the ability of the SARS-CoV virus to enter and replicate in human cells, Live Science previously reported The cell culture studies of SARS-CoV-2 revealed that the drug and its derivative hydroxychloroquine undermine the novel virus' replication in a similar way Many varying answers of result stories International Society of Antimicrobial Chemotherapy found that “hydroxychloroquine treatment is significantly associated with viral load reduction/disappearance in COVID-19 patients,” and the effect was “reinforced by azithromycin,” the antibiotic better known as a Z-pack Conducted at U.S. Veterans Health Administration medical centers found that COVID-19 patients who took hydroxychloroquine were more likely to die than those who did not A study looked at the combination of hydroxychloroquine, the antibiotic azithromycin and zinc supplements. Showed that patients who received the three-drug combination vs the two-drug combination of hydroxychloroquine and azithromycin were 44% less likely to die than the second group The FDA has authorized emergency use in adults and adolescents hospitalized with COVID-19, despite not knowing its effectiveness If we were to use this, recommended dose seems to be ~400 mg/d “Hydroxychloroquine effectiveness profile, its ability to inhibit lung viral replication for a 10-day period after only a 5- day cycle of therapy, and the large amounts of knowledge in term of safety deriving from its use for malaria prophylaxis and rheumatologic diseases permit to recommend its pre-exposure or post-exposure use for those performing procedures at high risk of viral diffusion in patients with COVID-19 pneumonia” \ Antiviral EIDD-2801 - Grace, Tara EIDD = Emory Institute for Drug Development EIDD-2801 is an oral ribonucleoside analog that inhibits the replication of multiple RNA viruses, including respiratory syncytial virus, influenza, chikungunya, Ebola, Venezuelan equine encephalitis virus, and Eastern equine encephalitis viruses. It is important that antivirals are active against a broad range of viruses so we can build a supply for a future pandemic.(Dennis C. Liotta, director of EIDD). “Our studies in the Journal of Virology show potent activity of the EIDD-2801 parent compound against multiple coronaviruses including SARS and MERS,” says Mark Denison, MD, the Stahlman Professor of Pediatrics and director of pediatric infectious diseases at Vanderbilt University School of Medicine. “It also has a strong genetic barrier to development of viral resistance, and its oral bioavailability makes it a candidate for use during an outbreak.” Must be used in early stages of contraction, would not be useful in later stages of the disease (Juliet Morrison, a virologist at UC Riverside). “Once you demonstrate its safety and efficacy, you’d like to build up a big supply of it so that when the next pandemic comes along, you have something you can potentially try with people, and if it works, you can stop that viral pandemic in its tracks.”- Dennis C. Liotta Director of EIDD EIDD-2801 works similarly to Gilead Sciences’ remdesivir, an unapproved drug that was developed for the Ebola virus and is being studied in five Phase III trials against COVID-19. Both molecules are nucleoside analogs that metabolize into an active form that blocks RNA polymerase, an essential component of viral replication. Other effects: improve pulmonary function, decrease body weight loss, and reduce amount of virus in the lungs. Positive compared to remdesivir: But remdesivir can only be given intravenously, meaning it would be difficult to deploy widely. In contrast, EIDD-2801 can be taken in pill form, says Mark Denison, a coronavirus expert and director of the infectious diseases division at Vanderbilt Medical School. Positive compared to remdesivir: He also notes that while remdesivir and EIDD-2801 both block RNA polymerase, they appear to do it in different ways, meaning they could be complementary. Negative compared to remdesivir: Unlike remdesivir, EIDD-2801 lacks human safety data. Ridgeback founder and CEO Wendy Holman says she expects the US Food and Drug Administration to give the green light for a Phase I study in COVID-19 infections within “weeks, not months.” Human trials began on April 10 in the UK- clinical trials are still underway. Japan Drug-Olivia The antiviral drug, called favipiravir or Avigan, has been used in Japan to treat influenza, and last month, the drug was approved as an experimental treatment for COVID-19 infections, Pharmaceutical Technology reported. "There are currently no data showing that Avigan has high efficacy," said Daisuke Tamura, an associate professor at Jichi Medical University specializing in pediatric infectious disease. Chinese researchers say it was “clearly effective” It has been sent out to 42 countries Japanese Prime Minister Shinzo Abe said Monday he wants favipiravir approved for Covid-19 in May, as Japan moves to fast-track approval for remdesivir as well. In sample size of 80 it shortened the length of illness from 11 days to 4 days Also slight improvements later on in CT scan of chest https://www.sciencedirect.com/science/article/pii/S2095809920300631#f0005 Favipiravir versus Arbidol for COVID-19: A Randomized Clinical Trial It was found not to be as effective as favipiravir. But study also says The Chinese government also has a reputation of manipulating research data to suit their needs. Researched Sensors All different types of Sensors: volume, weight, flow https://www.sstsensing.com/7-main-types-of-level-sensors/ Optical level switches Better for small amounts of liquid Flow Sensors- Used to measure the flow of the drug. Calculations need to be done to show when the liquid is done and how long it flows Want to use the autoclavable(reusable) Technical documentation of sensorion mass flow meter SFM 3300 Flow Sensor should be placed on the intake channel valve. See this diagram. Good info above on sensor use in nebulizers^ Anti-Inflammatory Colchicine is a non-steroid anti-inflammatory that comes in liquid form. It is a specialized pro-resolving mediator(SPM) that represents a portion of the omega-3 fatty acid spectrum that has a powerful effect on reducing inflammation. Use in aerosolized form in nebulizer Works Cited “Treatments for COVID-19: Drugs Being Tested against the Coronavirus.” LiveScience, Purch, 9 Apr. 2020, www.livescience.com/coronavirus-covid-19-treatments.html . “Instrumentation.” Pulsar PM, www.pulsar-pm.com/Instrumentation/Product-Types/Level-Volume/Continuous . Duke194715. “Omega Engineering.” lv10, 16 Apr. 2018, www.omega.com/en-us/process-switches/level-switches/float-switches/lv10/p/LV-10?&lid=92700048661953921&ds_s_kwgid=58700005355260684&ds_e_product_group_id=778816890462&ds_e_product_store_id=&ds_e_ad_type=pla&ds_s_inventory_feed_id=97700000007301780&gclid=EAIaIQobChMI-uKgmdy-6QIVhK7ICh2e5ApUEAYYASABEgItz_D_BwE&gclsrc=aw.ds . DeVilbiss Pulmo Aide Compressor Nebulizer Owners Patient Guide, www.americanallergy.com/pulmoaide-nebulizer/devilbiss-pulmoaide-patient-guide.htm . “Global Coronavirus COVID-19 Clinical Trial Tracker.” covid19, www.covid19-trials.com/ . Ksiazek, et al. “Chloroquine Is a Potent Inhibitor of SARS Coronavirus Infection and Spread.” Virology Journal, BioMed Central, 1 Jan. 1970, virologyj.biomedcentral.com/articles/10.1186/1743-422X-2-69. Lanese, Nicoletta. “Could the Anti-Malarial Drug Chloroquine Treat COVID-19?” LiveScience, Purch, 20 Mar. 2020, www.livescience.com/chloroquine-coronavirus-treatment.html . NHS Choices, NHS, www.nhs.uk/medicines/azithromycin/ . “Hydroxychloroquine Uses, Dosage & Side Effects.” Drugs.com, www.drugs.com/hydroxychloroquine.html . Halford, Bethany. “An emerging antiviral takes aim at COVID-19.” 2020, https://cen.acs.org/pharmaceuticals/drug-development/emerging-antiviral-takes-aim-COVID-19/98/web/2020/05 .“EIDD 2801.” New Drug Approvals, 28 Mar. 2020, newdrugapprovals.org/2020/03/28/eidd-2801/. “FDA: Human Trials Can Begin for Emory COVID-19 Antiviral.” Emory University | Atlanta, GA, 7 Apr. 2020, news.emory.edu/stories/2020/04/covid_eidd2801_fda/index.html. “EIDD-2801: Coronaviruses Inhibitor: MedChemExpress.” MedchemExpress.com, www.medchemexpress.com/eidd-2801.html . Cai, Qingxian, et al. “Experimental Treatment with Favipiravir for COVID-19: An Open-Label Control Study.” Engineering, Elsevier, 18 Mar. 2020, www.sciencedirect.com/science/article/pii/S2095809920300631#f0005 . “7 Main Types of Level Sensing Methods – How Do They Differ?” SST Sensing, 4 Mar. 2020, www.sstsensing.com/7-main-types-of-level-sensors/ . “SFM3300 - Mass Flow Meter.” Sensirion AG Switzerland, www.sensirion.com/en/flow-sensors/mass-flow-meters-for-high-precise-measurement-of-gases/proximal-flow-sensors-sfm3300-autoclavable-washable-or-single-use/ . Sensirion. “Single-Use Proximal Flow Sensors.” Medical Design and Outsourcing, 15 May 2017, www.medicaldesignandoutsourcing.com/single-use-proximal-flow-sensors/ . “US8333190B2 - Nebulizer Having Flow Meter Function.” Google Patents, Google, patents.google.com/patent/US8333190B2/en. Rudokas, Mindaugas, et al. “Liposome Delivery Systems for Inhalation: A Critical Review Highlighting Formulation Issues and Anticancer Applications.” Medical Principles and Practice : International Journal of the Kuwait University, Health Science Centre, S. Karger AG, 2016, www.ncbi.nlm.nih.gov/pmc/articles/PMC5588529/ . Cox, David. “Some Patients Who Survive COVID-19 May Suffer Lasting Lung Damage.” Science News, 6 May 2020, www.sciencenews.org/article/coronavirus-covid-19-some-patients-may-suffer-lasting-lung-damage . Puckey, Melisa. “Can Colchicine Be Used to Treat COVID-19 (Coronavirus)?” Drugs.com, www.drugs.com/medical-answers/colchicine-treat-covid-19-coronavirus-3535211/ . Kunzmann, Kevin. “FDA Approves Liquid Colchicine Formulation for Gout.” HCPLive®, 26 Feb. 2019, www.mdmag.com/medical-news/fda-approves-liquid-colchicine-formulation-for-gout . Silverman, Robert G. “Specialized pro-Resolving Mediators: A New Tool for Resolving Inflammation.” Official Media Integrative Practitioner, www.integrativepractitioner.com/about/integrative-healthcare-symposium/specialized-pro-resolving-mediators-new-tool-resolving-inflammation . Ruzer, Lev S, and Naomi H Harley. “Aerosols Handbook.” Google Books, Google, books.google.com/books?id=Sn0hT9jlj9AC&pg=PA249&lpg=PA249&dq=anti-inflammatories%2Bin%2Baerosol%2Bform&source=bl&ots=9Bu0GNMd-h&sig=ACfU3U3nM7_rVQpv5T06PfipLHi5O5WtlQ&hl=en&sa=X&ved=2ahUKEwjrpZSK7MPpAhVZgXIEHQtCDakQ6AEwBnoECAoQAQ#v=onepage&q=anti-inflammatories%20in%20aerosol%20form&f=false. Accomplishments that I'm proud of I am proud of the new innovations to our first hackathon project What's next for An Innovative and Improved Approach to Prevent & Treat COVID new sensors and clinical trials Built With autocad

https://devpost.com/software/trace-hpx8fb

Slide 1 Slide 2 Slide 3 Slide 4 Slide 5 Slide 6 Slide 7 Login Screen Population Density Heat Map Destination Map Single Destination Statistics Activity Log Menu Inspiration COVID-19 is presenting a challenge in how societies can reopen the economy in a safe manner. Our team was inspired by the technological efficiency shown by other countries, such as South Korea, that has provided mechanisms to preserve a lifestyle that more closely resembles pre-pandemic life. Our app strives to provide a data-driven solution that can be easily implemented in daily life to ensure safety and free mobility in the presence of a pandemic. What it does Our app provides solutions for the issue of mobility in the presence of an infectious virus: A solution to avoid crowded areas and a means to de-densify crowds. Users can use the heatmap function to discover crowded areas. These places would be avoided, reducing interaction and preventing rapid spread of the virus. Users can search for places (i.e. grocery stores, pharmacies, etc.) nearby and check the popularity by hour. If a location currently exhibits high popularity, users can choose to go at a less popular time. A solution to assess personal risk for infection. Users will be alerted if they have come into contact with someone who has COVID-19. By checking their activity log, users can check if they crossed paths with a person with COVID-19 (1st-degree interaction) or if they crossed paths with someone who had a 1st-degree interaction. Note: All interactions within the past 14 days of a self-reported infection will be notified. A solution to assess virus-related trends and predictions Users will have access to statistics on total infections, changes in infections, and changes in local mobility. By representing time-series data in a graphical fashion, users can see how infections and mobility has changed over the past week and month. Our machine learning algorithm can effectively predict into the future the number of infections over the course of a week up to a month, giving users tools to make well-informed decisions regarding their safety. How we built it Contact Tracing The contact tracing feature of our application is based not only on location data, but also on Bluetooth connectivity between Trace users. This enables our application to track user activity and user interaction on a granular scale while preserving user privacy. User contact and distance of interaction can be determined by Bluetooth signaling, and as these signal strengths will be determined in the back-end of the application, Bluetooth signals will remain anonymous to Trace users. Although contact tracing is necessary to help keep communities safe from the spread of viruses, we also believe that it is important to preserve user privacy, and this methodology helps us achieve this function. Statistical Analysis Using data gathered by our application and open-source data, we are able to apply a number of statistical methods and models to provide an in-depth, yet digestible, analysis. Currently, we apply machine learning on Google mobility data to model population movement on a county scale, enabling us to analyze how transit trends directly affect infection rates. By implementing user data, we are able to track and analyze trends in communities on a refined scale. In doing so, Trace is able to provide robust models that understand how populations respond to coronavirus and public policies, providing insight on the effectiveness of social distancing. Furthermore, we apply parametric and nonparametric regressions to predict future cases on a local, state, and national scale using transit trends, assisting the development of public policies and helping users assess the risks involved. Crowd Tracking Our map will be implemented using MapBox as our main graphical interface and Google Maps API for search and backend location functions. Using a combination of Google Popular Times data and our own location data generated through the app, we can inform users how many people are populating any searchable location and the best (least popular) times at which to visit. By using our own data, we can direct groups of users to different locations in an effort to minimize crowds at a singular place of interest. Challenges we ran into We ran into a number of challenges when creating our machine learning models. The Google data associated with mobility trends for each county had many missing values, with many missing values occurring in blocks. To remedy this, we assumed a linear trend between the start and the end of each missing datapoint block, and interpolated these values accordingly. In addition, matching this county level data with confirmed cases was surprisingly a challenge. We used the New York Times open source data, and cleaned both datasets to correspond with one another. In addition, we tested various models, which was quite computationally expensive; this was due to applying time series cross validation techniques, such as nested cross validation and rolling windows. In the end, we were able to build a more robust and accurate model which could not only predict cases in the future, but model various changes in mobility and how these modifications in social distancing affect cases of coronavirus. We also experienced challenges in gathering Google popular times data, which was not available through the Google Maps API. Our solution meant writing a web scraper which could process large queries. Accomplishments that we’re proud of As a team, we brought to the table different skill sets and experiences, as each team member contributed their strengths to the project. We are proud of our collaborative efforts to create an application that emphasizes and fulfills the multidisciplinary nature that a solution for COVID-19 requires. Through the span of this project, we were exposed to various challenges as a result of working with real-time data. However, our ability to work with missing values and to validate the datasets allowed us to create a more robust application that is less dependent on user error and incomplete data. What we learned We learned that using Bluetooth to detect close interactions is more accurate than GPS especially when users are inside or in the presence of skyscrapers where GPS location estimates can have a margin of error of around 20 meters. Bluetooth, on the other hand, has an accuracy level on the order of feet. While Google’s Popular Time data provides useful insights into a location's popularity over the course of the day, their figures have yet to take into account massive changes in behavior resulting from the pandemic. We believe that with enough users, our own data will give us a more accurate picture of how many people are frequenting specific locations during the pandemic. We also learned how to develop and test accurate generative machine learning models using various regression methods and cross validation techniques. We learned how to use cross validation techniques and regression metrics to ensure our models were not overfitting, and used ensemble learning to build a robust and scalable model using our unique datasets. What’s next for Trace We would like to finetune our bluetooth technology such that we improve our accuracy for calculating interaction distance. In addition, we would like to refine our statistical analysis and machine learning models to achieve higher efficiency. We hope to build a robust backend and remove the need to scrape any public data, as well as build a scalable system for many users to operate on. Our goal is to upload the app to the Apple App Store and Google Play Store to allow all mobile users access to this analysis. Additional Links Tableau https://public.tableau.com/profile/alexander.liebeskind#!/ Github https://github.com/thomasundo2/trace_ml Sources Google Mobility Data: https://www.google.com/covid19/mobility/ Johns Hopkins Coronavirus Data: https://github.com/CSSEGISandData/COVID-19 The New York Times Coronavirus Data: https://github.com/nytimes/covid-19-data Built With data google johns-hopkins-university-hub machine-learning mapbox new-york-times numpy pandas python python-package-index scipy sigma sklearn swift tableau Try it out public.tableau.com github.com

https://devpost.com/software/taku

User Experience Landing Page Profile Dashboard Inspiration Takuo Aoyagi's mathematical formula to reduce noise in pulse oximetry testing. We wanted to do something similar by reducing the noise a patient or caregiver encounters trying to navigate the complexities of screening and diagnostics. What it does Taku is an app/website that allows patients and their caregivers to create a profile and discover the benefits, insights, accessibility, usage, and education around screening and diagnostic products. COVID-19 has brought to light the glory of telemedicine, however it hasn't done much to make it easier for patients to understand. Taku allows users to indicate what stage they are at in the healthcare journey and Taku curates the experience to benefit them from day one. It prioritizes accessibility so it can help patients navigate direct to consumer testing as well as patients under and /or non-insured to discover what resources are available within their community. Once accessibility is navigated then Taku allows patients and their caregivers to record, monitor, and escalate their screening and diagnostic records. How we built it We built the stack by prioritizing data science and comprehension of the user journey. Primary work was leveraging existing stack of google sheets, python libraries, data scrapers, google data studio, bubble.is, react, R, and adobe indesign/ premeire/cloud. Challenges we ran into We needed to produce a complete environment to support the global user journey and design an experience that would allow us to grow beyond the diagnostics/devices we prioritized (pulse oximeters, qt-pcr, antigen, antibody, etc). Lung was the initial organ for our target product profile but by having a comprehensive user journey we are able to scale our environment since the user journey accessing and navigating testing and diagnostics is consistent throughout all of health indications. Accomplishments that we're proud of A team of strangers coming together and over 5 days producing this effort. We are also pretty proud of the UX since none of us are designers, developers, etc. What we learned Change management, project management, collaboration, design thinking, patient centricity, and a little about each other. What's next for Taku We will add more robust functionality to support the complete healthcare journey of users and flesh out the caregiving module we barely scratched the surface on. Drive with all of our assets: https://drive.google.com/open?id=1vyrSBLiqWgwboD6xZNYzVyXmtqOr6Qt_ Built With bubble.is google google-genomic-api google-healthcare-api indesign premeir python r react ruby sheets Try it out takudx.bubbleapps.io

https://devpost.com/software/solocoin

Home Page Social-distancing timer and Challenges Detailed Rewards Rewards and Coupons Detailed Leaderboards Leaderboards, Milestones, Badges The Inspiration COVID-19 has severely affected the livelihoods of the people around the globe. With people getting infected by COVID each passing day, Consumers have learned to stay home, preserve the money they have, and consume less. However, this affects the economy. Similarly, local businesses have experienced unprecedented losses. For those that have survived this period the possibilities for re-opening, recovery, and growth are limited and possibly bleak. SMBs don't have a sustainable solution through which they can grow their businesses again and recover their losses. Traditional ad-tech channels are broken and without significant investment, any business can't get RoI. But, with inbuilt game mechanics, we can motivate people to purchase and help SMBs advertise their product without any upfront investment. So, the perfect way to help both sides of the community SMBs and making it fun for people suffering to help the SMBs is gamification. I’m a co-founder of a Blockchain gaming company. I (Arbob) have a lot of experience in implementing game mechanics inside consumer apps. So, I thought, why not apply the same gamification techniques I implement in blockchain into a consumer app to encourage people to do a task based on their location, spend more and help SMBs in economic recovery. So I started to scout for members in hackathon channels and got an amazing team to build this idea. What it does SoloCoin is an app that rewards users in virtual coins based on their location. Currently, to engage in social-distancing, based on their location to their home. It's basically an app that rewards users according to their proximity/location. (using the tech of GPS, Geofencing, and Accelerometer - to track whether the phone is put on idle or not - awards will be rewarded only when the user is using the phone). If their smartphone is within a certain radius (~20m) to a reward hotspot (Geofencing reward location), then the app will reward them with virtual coins that they can later redeem for "Partner Coupons". These partners can be SMBs, Local businesses, and any online B2C businesses from E-commerce, Entertainment, Lifestyle, Health, etc. Our app rewards, nudges, and drives beneficial consumer behavior. This will help post-COVID to accelerate economic recovery in local communities. They can also compete with nearby players for achievements and badges which they can later share with their friends. The global ads market is $600B+ with digital advertising accounting for $220B+. But there is a niche in hyperlocal digital-ads where specifically no-one has targeted their solution. Just in India, $650B is the size of traditional retail shops. Simple and Engaging Advertising needs of such a big segment of the market will create an ad-tech boom in the hyperlocal sector in India. We can be at the forefront of this market in the next 5-7 years. How we built it? When Arbob had the idea, he started building it on Python's Beeware toolkit which ports python code to a native mobile app. Then, he started to scout for members across hackathons. Since the idea was innovative and exciting, many amazing people joined his team. then the team decided to make it on native android and iOS directly for better usability and support. We have a group of open-source collaborators from around the world including startup founders & CXOs, people from IITs, BITS, Stanford, Microsoft, Uber, Github, Neuro-Researchers and more among our community, with expertise in Frontend (android-studio, Java, Kotlin), Backend (rails+postgresql | RDS) mobile development, Marketing, Product and Design (Adobe xd), etc. AWS is the cloud service provider with authentication from Firebase and Maps from google. The product is built 100% remotely. Challenges we ran into The first challenge was finding good team members with relevant expertise. But, we got through with it thanks to our hard work and to the volunteers joining because of the innovative nature of the product. Management of tasks. To tackle this issue, we created a Trello and GitHub task board for better collaboration. * One thing I've noticed while building our product is the founder's vision for the product is very important. When I first pitched the idea of SoloCoin, I was alone. But the idea was innovative and has never been done before. The vision I put to gamify social-distancing resonated with people and that helped us in getting amazing people with great skills from all over the world to voluntarily work on my idea without any financial incentive. People were and still are excited every day they wake up to build and scale the product. And, that's how from an idea it became an MVP and then a working product. * Accomplishments that we're proud of The clarity in our concept. Innovative approach towards social-cause using gamification. 1000+ sign-ups for the app launch. 5000+ user visits since the website launch. The prototype was done in 3 days. Beta Launched in Play Store. Positive feedback and support from across the community, both tech and non-tech. Influencers asking to promote our app for FREE. Many top-level government officials agreed to promote our product in their network. Partnerships for reward coupons. Partnerships with multiple influencers. An amazing team of 20+ open-source collaborators. 100% remote. Tackling a greater cause to eradicate COVID-19 from the face of the earth through gamified social-distancing. Won India’s largest COVID Hackathon - CODE19. Won World's largest COVID Hackathon - EUvsVirus. Incubated in European Innovation Council's business accelerator and Central European University's Innovation Lab. What we learned Clear documentation from both product and development perspective for faster user onboarding. The idea of making a difference motivates a person more than money. Distribute department leads early on to avoid clashes among members. We were lucky that we did it early on. Single design philosophy to avoid misalignment of colors, content that is being pushed on the internet for promotion and visibility. Don't let negative people come anywhere near your extremely positive and passionate team. Take care of your team. Regular motivation and clear communication are very important when managing a remote team. Just like you can’t expect 9 women to give birth to a baby in 1 month, you shouldn’t expect 10 developers to build a product of a global scale in a day. Ideas are the most valuable asset to any startup. That's why we have a dedicated #ideas channel our discord for people to post ideas that can help improve our product. Till now we have received 20+ ideas since the project's inception. Planned Revenue Model Brands pay us for promoting their deals via Rewards. Sponsors will pay us to get their rewards listed on our app. Like if a new e-commerce startup wants better visibility of their product, they can pay us some fee and get their brand coupon listed on our app, which users can redeem for coins and purchase stuff from their website. Sponsored badges and goals. For e.g.When someone redeems the coins for Amazon Coupons they’ll get an “Amazon Badge of Honor” which they can share in their social media. Sponsored Daily/Weekly/Monthly Rewards via Challenges Location-based targeted ads for grocery, medicine, and other necessities. Later we can open it for a broader audience and sponsors. Subscription model for faster coin generation. Impact of SoloCoin SoloCoin will have a massive impact on the reduction of COVID-19 transmission and on society as a whole. Some of them are: Impact on the society - It is a “simple way” for citizens to do their part, practices social distancing, and get real economic rewards and esteem awards to show they stood up to the challenge! They can be proud of themselves. Impact on Public Health Officials: Public Health Agencies can get access to anonymized data insights from our app to help form better messaging to inform/educate the public. ‘ Impact on Partners-Sponsors: Coins can be exchanged for exciting "Partner coupons". These partners can be SMBs, Local businesses, and any online B2C businesses. Our app rewards, nudges, and drives beneficial consumer behavior. This will help post-COVID to accelerate economic recovery in local communities and help get their businesses on track. Impact on People-driven Health and Wellness: having an all-access platform for behavioral change with people from all around the world will help support post-COVID measures, promoting healthier physical, mental, and social behaviors. What's next for SoloCoin? Making this a global app with partner support. Rewarding for good habits like washing hands, timely self-isolation, Yoga, etc. Determining efficient/less crowded routes for commuting and avoiding people. Give users the possibility to chat with nearby quarantined people. Map list of nearby available essential stores for groceries, medicines, etc. Adding an anonymous user authentication system. Give users the possibility to add a mask to their profile picture to tell people they are practicing social-distancing. What after COVID ends? We have identified many ideas on what we can do with our tech post-COVID. Some of them are: Our app can be used for concerts/stores, basically to gather people. The more they stay the more they earn. That way sponsors will get better revenue as well. Chat with friends, hang out, and earn rewards as you have a good time! Real-time location tracking automatically detects when you and friends are out and about, so you can passively earn points all day. Use group messaging and location sharing to stay in touch with your friends at any time. Emergency contact features let you get in touch with your circle whenever you need a helping hand because friends watch out for each other! At the current stage, the app is used as a Social-distancing app with "Home geo-fence". After COVID, we can increase the geo-fence to multiple locations like "rewarding concerts, malls, local stores, etc." Our app can be used for concerts/stores, basically to gather people. The more they stay the more they earn. That way sponsors will get better revenue as well. Our app rewards, nudges, and drives beneficial consumer behavior. This will help post-COVID to accelerate economic recovery in local communities. Now if you think about it we're venturing into not a consumer app space but rather "Ad-tech" space. Our app can now be at the forefront of "Hyperlocal based targeted ads", basically directly competing with Google's and Facebook's Pay Per Click. Shopping is fun in real life. You can go with friends, treasure hunt for bargains, discover new products, better understand a brand’s vibe, ask store reps questions, and also touch and feel items so you have more confidence you’re going to love it. The shopping revolution we bring will COMBINE ecommerce and entertainment, where both are equal in importance. Toss in gamification and boom. We may see waves of new brands and more pricing transparency for everything... products and services, alike. We can gamify people’s entire lives, everything they do, with the tech and 20+ sensors present in smartphones. Our vision is for a healthier, happier, COVID-19-free world and we can't wait to launch this app in the global market and help make the world a better place. You can also look at our Product Roadmap for the present and the future to get an idea of where we are headed. App Demo Video can be found here Built With amazon-web-services android-studio firebase geo-fencing google-cloud google-maps java postgresql ruby-on-rails Try it out xd.adobe.com www.solocoin.app github.com drive.google.com docs.google.com play.google.com

https://devpost.com/software/remote-learning

Inspiration Due to the coronavirus pandemic, most schools have closed and moved to online learning. This led to many challenges such as difficulty engaging and providing materials. Students are more used to in-classroom learning and they can lose motivation to do school work. For this reason, we have built a platform that allows teachers to quiz, test and engage with students in a new way. What it does Users can create private rooms and invite others via a shareable link. No sign-up is required, the user simply enters their full name to join a room. Everyone in the room can communicate in real-time, the room creator can create challenges for others to participate in. Challenges range from questions, multiple choice, whiteboarding and sketching. Once the timer has ended, all students are able to see the correct answer, everyone's answer and how they did. You can use RemoteLearning with anyone, co-workers/students/friends etc. It benefits any group of people who are looking to learn and collaborate together. How I built it Websockets was used as the core bone behind the application, it supports messaging, challenges and syncing data. Challenges I ran into At the start, the idea was integrate a video chat similar to Zoom, however due to some technical challenges we decided to put it aside and develop an MVP with the core features (challenges). Accomplishments that I'm proud of We have implemented the application, deployed to production and is ready to use. The real-time syncing works pretty well when creating challenges and interacting with other users, however this has only been tested on devices on the same network. There could be issues when using it across the global, we will be on it when that happens. What I learned Integrating real-time data using Websockets and WebRTC. What's next for Remote Learning Continue adding features and improving the platform, send it to users, schools and share it around. Built With node.js react webrtc websockets Try it out remotelearning.space

https://devpost.com/software/the-odor-of-covid

Inspiration The virus is an invisible enemy. Anyone can be the source of other people's infection. We need to cut that chain of spread by making the virus visible and prepare ourselves. THE SCENT OF COVID19 wants to detect the presence of the virus through the analysis of people's breath. () We will defeat the virus by making it visible. While the Covid-19 widespread is plateauing in some countries, governments are actively looking for solutions for the so-called "phase 2" to lower the lockdown. This is a critical moment, where measures to avoid a new burst are necessary. In light of this, we have concentrated our effort into designing a solution to detect the COVID19 through a sensor that is accessible and easy to deploy. What it does The aim of the Project is to define the breathprint characterizing COVID19 at different stages of the pathology (healthy people VS without clear symptoms VS with symptoms) in order to use the data collected for the development of a fast, reliable and sensitive diagnostic method. This aim can be achieved with the analysis of VOCs in people's breath through a DIY sensor. Practically it would be accomplished through: A low-cost DIY kit consisting of a VOC sensor array, a controller card and a mobile application. A platform to share this kit, with financial resources so that companies can build it themselves and provide to the distribution. An open database that concentrates all these data, anonymized and standardized. A neural network that analyses these data, contrasting the VOCs of the breath and your health status, to determine the respiratory footprint of the COVID19 at different stages of the infection. With this kind of information it will be possible to use the DIY as a diagnostic instrument: according to its breathprint, in fact each person performing the test will be assigned to a predefined category. In this way It will be possible to rapidly distinguish healthy subjects from asymptomatic ones. How we build it The biomarker of COVID19 in respiratory air is not known. Through a campaign of testing of people with and without the symptoms of the pathology, carried out through the Kit that detects VOCs from expired air, it is possible to generate an open database. Analyzed through Artificial Intelligence algorithms, perfected through the KAGGLE platform, the aim is to search for the virus' footprint at different infective stages. This will lead to the determination of the parameters that will be used for non-invasive diagnosis of the population. Challenges Identify the VOCs (volatile organic compounds) that the body generates when it is infected with COVID19 Develop a device capable of detecting this VOC Develop the DIY kit (array of VOC sensors) Find volunteers who want to make the kit, test it and send the data Generate a quick iteration of the solution -where needed- according to initial test results Finding a means of financing, to facilitate the manufacture of the kits Develop an AI algorithm that finds the virus' VOC breathprint in exhaled air Train the AI model as quickly as possible in order to start generating reliable predictions. Looking at the economic crisis caused by the coronavirus, a business model that allows a way of constraining the price of the solution is needed so that people without the means to buy the DIY kit could have access to it. Need for quick and reliable distribution. Accomplishments that I'm proud of THE SCENT OF COVID19 Achieving a fast, cheap and simple methodology that can detect the virus in asymptomatic patients, to anyone and anywhere. Being able to build an effective approach that is accessible, as well as easy to distribute, making it available to as much people as possible so that we can make a positive difference in this Covid19 crisis. What I learned We have seen the amount of dispersed and disconnected information about the COVID. We have learned about VOC biomarkers from people's breathing air and the sensors to detect them. That the only way to know and beat this virus is through collaborative knowledge, the one we have had and the volunteers who test the kit and the optimizers of the algorithm. What's next for Developing the kit Testing Building partnerships and implementing a commercialisation strategy: Via funding or sponsorship of the DIY kits with public authorities as well as private organisations (which are actively looking to collaborate in CSR plans). Via crowdfunding: buy one-donate one campaign Via partnership: similar to sponsorship but in this case joining forces with hardware providers to launch a constraint price quickly Dissemination Developing marketing channels: website, social media... Connecting with the +800 NGOs, foundations, associations, and civil society groups, universities and public authorities linked to the panEU hackathon Distribution kickoff Built With algorithms.io hardware kit machine-learning open sensor share-online web Try it out 1drv.ms www.smasp.org www.youtube.com

https://devpost.com/software/covid-health-tracker

Inspiration The COVID FRONTLINERS What it does A System that Tracks down person in contact with COVID positive How I built it It is a tracker system for tracing person who are in contact with positive COVID cases Challenges I ran into Knowledge, skills and Teamwork Accomplishments that I'm proud of What I learned What's next for COVID HEALTH TRACKER A system that can be used in the future health care Built With covid health

https://devpost.com/software/healing-frequencies-mix

Electromagnetic frequency healing for coronavirus(covid-19) Inspiration Audio frequencies mixing What it does Helps healing of Covid-19. How I built it Mixing audio frequencies using Mozilla and audacity to record. Challenges I ran into Choosing the correct frequencies. Accomplishments that I'm proud of The mix is high quality and all the frequencies can be heard. . What I learned How to record in high quality sound without distortion of frequencies. What's next for Healing frequencies mix I hope many people will find it useful to fight the infection. Built With audacity mozilla Try it out audiomack.com

https://devpost.com/software/covidprob

Homepage Low Risk Score Moderate Risk Score High Risk Score Inspiration COVID 19 was discovered in December, last year in Wuhan. It has already been months but no vaccine or drug to fight against COVID-19 has been discovered. In these tough times, if we can even detect the disease beforehand, it could help a person contact the medical officials in time and diagnose and get treated in time. What it does It gives you an estimate of the probability of how much is a person infected with COVID-19. The parameters for the prediction is the list of symptoms. How we built it Technology Stack Front-end 1. HTML 2. MaterializeCSS 3. JavaScript Back-end 1. Django web framework **UI-Kit** * Figma Challenges we ran into Gathering the dataset according to symptoms was the toughest part. As the raw dataset which we obtained had to be cleaned, we had to deal with missing data, too. Accomplishments that we're proud of Building this web app in a short amount of time really made learnt a lot of things. What we learned How to use various algorithms of Scikit-learn library. Getting hands-on with the Django framework. What's next for COVIDprob To gather more data to increase the accuracy of our model Built for the Innovative Website 2020 Competition. This website was built by Sagar Banik and Sumit Banik Built With django figma materialize-css scikit-learn Try it out covidpred.herokuapp.com github.com

https://devpost.com/software/virtual-health-checkup-modelling-of-coronavirus-technoband

Technoband Software Modelling of Future conditions of CoronaVirus Inspiration Daily surge in cases, health conditions of citizens pushed me to work hard What it does It predicts the curve of future conditions of any country w.r.t. data set available How I built it I built it through software, that have been mentioned. Challenges I ran into Lots of challenges, but overcomes and got the results as expected Accomplishments that I'm proud of That I did something, which satisfies and help at least one citizen, then the chain will follow up. What I learned I learned new softwares, skills What's next for Virtual Health Checkup|Modelling of CoronaVirus|Technoband If got success, wanna make it open source. Built With arduino c++ embedded matlab python webex

https://devpost.com/software/covidseek

Inspiration Since the beginning of this pandemic, many people globally are in a state of confusion and panic. Many healthcare systems need a way to allocate resources properly based on the density of the pandemic. Furthermore, many people do not know when this virus will keep spreading. We built COVIDSeek to answer these problems through providing an accurate visualization and predictions/forecasts of the pandemic. What it does COVIDSeek is a web application that connects people and healtchare systems through accurate information, and predictive analytics. Users enter their location to see a density heatmap of the virus on an international scale, which is also useful for medical practitioners and the healthcare system. They also will see the specific number of cases and deaths in their respective area on a given day. Finally, they are provided with a forecast of what cases might rise/lower to in the next 1-2 months. How we built it On the front end, we used html, css, and javascript through the bootstrap web framework. On the backend, we first use the google-maps api in python (through gmaps) to visualize the heatmap, and we passed this into an html file. Furthermore, we used Flask to serve the json data of the cases and deaths (across the world) to our front end, and SQLAlchemy as a way of storing data schema in our database. We use the FBProphet library to statistically forecast time-series data and future cases through Bayesian analysis, logistical growth, and predictive analytics, by factoring in trend shifts as well. Challenges we ran into We ran into challenges regarding the visualization of the heatmap, as well as the creation of our forecasting algorithm, as we didn't have much experience with these areas. Furthermore, serving some parts of the data to the front-end from Flask had some errors at first. It also took time to assemble data into a consolidated file for analysis, which was a bit hard in terms of finding the right content and sources Accomplishments that we're proud of We are proud of how much progress we've made considering how new we were to libraries such as FBProphet and Flask, and the unique, special, and effective way we learned how to implement it. We learned how to create opportunities to benefit different areas across the world through data analytics, which is something that we're very proud of doing. What we learned In terms of skills, Aryan learnt how to develop his front-end skills with Bootstrap and using different ways of styling. Shreyas also developed his front-end skills while working with Aryan to structure the front-end, as well as finding new skills in learning Flask and the Gmaps API. We learnt that there are numerous ways that an individual can help the world around them through computer science. What's next for COVIDSeek In the future, we want to add a user-interactive search bar that places a marker on their location and zooms into the map, as well as a way for users to report symptoms/cases on the map. We also want to add more features, such as nearby testing sites, hospitals, as well as nearby stores with a certain amount of resources that they might need. Overall, we want to make this web app more scalable worldwide. Built With bootstrap css3 fbprophet flask google-maps html5 javascript matplotlib numpy pandas python sqlalchemy Try it out github.com

https://devpost.com/software/patient-health-history-record-system-f8iyxt

Screens Maps Control of epidemics - Patient Control - Control of Vaccination Campaigns - Expert needs control by location - More reliable and secure data according to the new personal data protection law - More objective targeting of public health policy - Faster reaction to public health emergencies - Doctors with access to all health history and with more accurate patient information including emergency care - Patients with an updated and accessible health history when they need medical care - Public authorities using mathematical models to make projections with greater reliability - Patients using mathematical models to make projections and personalized predictions - Access to vulnerable population to technologies given only to people with private health insurance - Access to information of people using private health insurance by the government - People who have a private health plan and switch to the public health system without losing data - More accessible and reliable data than in DATA SUS - Data held by patients - Data released only for those patients who wish to access - Health History x Digital Health Record - Simplification of the database used today using data lake methodology Built With datalake flutter ionic react Try it out github.com

https://devpost.com/software/crowd-management-system-cms-hgfbdi

homepage login page shopkeeper interface customer feed page Inspiration This idea first came into my mind when one day i went to nearby grocery shop during lockdown and found crowd of people there and then i thought about managing this crowd and maintaining social distancing among the people at public places,shops,etc. by means of an online system. What it does In this system there are 2 types of users 1->customer 2->shopkeeper A customer can follow the shop through shop id and get the information of number of customers present at that shop and whether the shop is open or closed in its feed. Then the customer can make a decision depending upon on the number of people present at that shop before going to that shop. On the shopkeeper's side, a shopkeeper has to update the number of customers present at shop by clicking increase or decrease buttton , and shop status(open or close) by clicking a button.This change will reflect at customer's page each time customer logs in or refresh the page. How we built it We have built it using php and somewhat javascript as a back-end language and for front-end we have used html5,css and bootstrap. SQL is used for database management. Challenges we ran into As this is our first hackathon so implementing the idea into the code keeping ease of using the system by end users in mind is a bit challenging for us. Also we have faced some technical issues during deployment of system online from localhost(offline) Accomplishments that we're proud of We are gladful that during this situation of COVID-19 pandemic throughout the world we have developed a system which can help the society in fighting with the problems which arised in the society due to the corona virus outbreak. What we learned As this is our first hackathon project so we have learned a lot while developing this system both in field of coding and implementation of idea through coding. What's next for Crowd Management System (CMS) Currently we are thinking to keep maintaining the project by adding new features to it such as otp verification on customer or shop registration, location based recommendation system for customers which recommends nearby shops,banks,grocery and medical shops, railway stations, airport ,etc. also making it more simple and more informative for the users in terms of its ease of usage. Built With ajax bootstrap css3 html5 javascript jquery php Try it out newnormal-cms.atwebpages.com github.com

https://devpost.com/software/home-health-care-patients-tracking-application

Home Health Care Mobile Home Health Care Sample Decision Support System COVID-19 Risk Prediction Tool Salesforce The follow-up of Home Health Care and elderly patients is not made digitally and home health data is not processed data. This makes it difficult for the elderly patient to follow the situation. Healthcare professionals are obliged to learn the examinations, drugs and patient status previously applied to the patient during the patient visits. With the current COVID-19 outbreak, patient visits have decreased considerably. Since the patients in this group are in the highest risk groups of COVID-19, hygiene requirements during the visits complicate the maintenance procedures. In addition to this situation; Symptom monitoring of home care patients, people in the geriatric class (65 years and older) and potential / recovering COVID-19 patients should be done remotely. First of all, the information necessary for the follow-up of home health care patients was prepared for information entry in the Android environment. Improvement was made in the Salesforce environment to retain the data. A website was prepared in RStudio environment by developing an AI based model for monitoring the health status of home health care patients. For the COVID-19 symptom follow-up, the data of 22,000+ COVID-19 patients were processed all over the world, and an website was prepared in RStudio environment. The biggest challenge we face is to find anonymous data that we will use for decision support systems and to clean and make the data available. In the later stages of the project, video speech, voice recognition and sensor and smart watch (Apple Watch) integration will be supported. Built With android api css flutter html java r rstudio salesforce Try it out dveshealth.com twitter.com www.linkedin.com www.instagram.com dveshealthai.shinyapps.io dveshealthai.shinyapps.io drive.google.com

https://devpost.com/software/my-journal-for-web

My Journal Input Screen COVID-19 Case Report (Pain & Fatigue) COVID-19 Case Report (Temp & Sp02) COVID-19 Case Report (Cough) Health Log User Login / Registration ( Tip: If you do not wish to register, use Username: demo Password: demodemo ) Inspiration I have a condition called Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) . I discovered that tracking my biometric data on paper or on existing applications was very difficult, so I wrote My Journal . I soon realized with simple modifications, My Journal could be used to help people with other illnesses, such as COVID-19. To learn more about ME/CFS , please read my blog: https://wisdom4.me Is there anything you find extraordinary about the project? For people with complex chronic illnesses like myself, My Journal can be life changing. It empowers the user to take charge of their health by making collaboration with healthcare professionals safer and much more efficient. I imported two years of my collected data into My Journal and I immediately gained valuable insight into my health. What it does I created My Journal to help people to track day to day symptoms and vital signs. My Journal's reports can show the historical trends of an individual's health condition over time. This information can easily be shared with doctors to help with (onsite or remote) screening and diagnosis. How I built it The frontend is implemented using HTML and Javascript utilizing jQuery and Google Chart. The backend is written in PHP on the LAMP stack running on the AWS cloud. Challenges I ran into I had to do quite a bit of research to learn the APIs required to build my web application. Accomplishments that I'm proud of I have created an application that I believe will be able to help people like myself that have health conditions that make them vulnerable to infection. Developing My Journal for different platforms has been a rewarding experience. What I learned I learned about the nuances of chronic illness by speaking with doctors and patients. I expanded my skill set by learning new APIs. What's next for My Journal for Web I hope to continue development of My Journal and ultimately share it with people all over the world. It has been a very useful tool for me and the management of my health. Built With amazon-web-services google-chart javascript jquery mysql php Try it out wisdom4.me

https://devpost.com/software/myfacemaskapp

Prototype model 1 "Dany" pink opaque Prototype model 1 "Dany" white opaque AiRFace.it (App) A new customizable, economic and ecological mask tailored to you Millions of disposable masks are thrown out every day, which in addition to having a significant environmental impact on nature also have a high monetary expenditure. To meet all these needs, the AiRFace.it App team has developed a project that allows the customization of the mask or the creation of transparent masks that can adapt to the features and therefore customizable by scanning the face in 3D. This is AiRFace.it App , a mobile application that can be downloaded free on IOS and Android devices. The scanning process is quick and easy: it happens through the use of the mobile phone camera. In addition, the material used in the production of the masks, biodegradable and hypoallergenic allows a repeated use, being able to sterilize the washing at high temperatures . The mask is therefore ergonomic and environmentally friendly, because you just need to change the filters. The 3D model can also be printed from the comfort of the house without leaving. The advantage is that, being custom-built, the signs released by normal masks after hours of use will be reduced. Considering the difficult and delicate situation we are experiencing, AiRFace.it App would ensure protection and prevention with zero impact on the environment and would meet individual needs. It would be an optimal solution, without going out to buy it if you already have a 3D printer or otherwise we print and deliver directly to your home! The App is free as well as the availability of the various basic 3D models. Ergonomic My face mask with its 3D scanning process, allows you to create ergonomic masks suitable for every feature of your face. This custom adaptation will allow you to reduce the marks released by normal masks after hours of use. 3d Printer The realization of the 3D masks allows anyone to create them independently. In fact, a 3D printer and a mobile phone are enough to quickly create personalized templates based on the desired quantity. Ecological The material of these masks is absolutely ecological, a very important feature if you consider high consumption daily, especially in some sectors. In fact, these masks can be reused several times later washing at high temperatures which allows sterilization. Trasparent One of the main features of AiRFace.it is transparency. The idea of ​​making these masks with a transparent material was born mainly from the awareness of the importance of lip reading for deaf people. Privacy For us your privacy comes first, that's why AiRFace.it complies with all Gdpr ( https://gdpr.eu ) regulations and no personal data will be transmitted. The problem solved by the project With AiRFace.it App we want to find the solution to the problem of the availability of personal protection devices for everyone, in fact thanks to this app anyone can print his mask, following our guidelines for the use of safe and biodegradable materials, with their own 3D printer,only if you are certificated member of our network to ensure the quality and safety of the mask produced according to all applicable regulations, so that you have a mask for you and your family that can last for all this complicated period that we are living. The solution you bring to the table AiRFace.it is installable for free on all iOS and Android devices that have compatibility requirements and in a simple automated way and can create your own 3D mask and send it directly to the 3d printer certificated The impact of the solution on the crisis The idea behind this project is to create a safe, cost-effective product that respects nature for us and future generations The needs to continue the project This project needs funds in order to create the best mask with the best materials and for this a significant investment in research and development in addition to wanting to make and print masks to those who do not have the opportunity to have their own 3D printer The value of your post-crisis solutions We believe a lot in this project because it is a valuable help to anyone who does not have the opportunity to always have a disposable mask and this mask can be reused even after this crisis (hopefully it ends as soon as possible) in any sector that needs personal protection devices The AiR net blockchain We are creating a network of certified makers to be able to print masks for doctors and nurses for free to thank them for their valuable help. We are working with other startups to create a network of certified makers using the Ethereum blockchain to create smart contracts in order to be able to transparently verify the entire network. We are creating a decentralized system that is based on blockchain eos to ensure the total transparency of certification of the materials used to print the masks. Currently our team also collaborates in the creation of protective equipment for doctors and nurses to thank them for their difficult work. Built With blockchain c# html5 java javascript kotlin objective-c python swift Try it out airface.it bitbucket.org

https://devpost.com/software/masked-ai-masks-detection-and-recognition

Platform Snapshot Input Video Model Processing Model Processing Output Video Saved Output Video Snapshot Output Video Snapshot Output Video Snapshot Output Video Snapshot Output Video Snapshot Output Video Snapshot Inspiration The total number of Coronavirus cases is 5,104,902 worldwide (Source: World o Meters). The cases are increasing day by day and the curve is not ready to flatten, that’s really sad!! Right now the virus is in the community-transmission stage and taking preventive measures is the only option to flatten the curve. Face Masks Are Crucial Now in the Battle Against COVID-19 to stop community-based transmission. But we are humans and lazy by nature. We are not used to wear masks when we go out in public places. One of the biggest challenges is “People not wearing masks at public places and violating the order issued by the government or local administration.” That is the main reason, we built this solution to monitor people in public places by Drones, CCTVs, IP cameras, etc, and detect people with or without face masks. Police and officials are working day and night but manual surveillance is not enough to identify people who are violating rules & regulations. Our objective was to create a solution that provides less human-based surveillance to detect people who are not using masks in public places. An automated AI system can reduce the manual investigations. What it does Masked AI is a real-time video analytics solution for human surveillance and face mask identification. Our main feature is to identify people with masks that are advised by the government. Our solution is easy to deploy in Drones and CCTVs to “see that really matters” in this pandemic situation of the Novel Coronavirus. It has the following features: 1. Human Detection 2. Face Masks Identification (N95, Surgical, and Cloth-based Masks) 3. Identify human with or without mask in real-time 4. Count people each second of the frame 5. Generate alarm to the local authority if not using a mask (Soon in video demo) It runs entirely on the cloud and does detection in real-time with analysis using graphs. How we built it Our solution is built using the following major technologies: 1. Deep Learning and Computer Vision 2. Cloud Services (Azure in this case) 3. Microservices (Flask in this case) 4. JavaScript for the frontend features 5. Embedded technologies I will be breaking the complete solution into the following steps: 1. Data Preparation: We collected more than 1000 good quality images of multiple classes of face masks (N95, Surgical, Clothe-based masks). We then performed data-preprocessing and labeled all the images using labeling tools and generated PASCAL VOC and JSON after the labeling. 2. Model Preparation: We used one of the famous deep learning-based object detection algorithm “YOLO V-3” for our task. Using darknet and Yolo v-3, we trained the model from scratch on 16GB RAM and Tesla K80 powered GPU machine. It took 10 hours to train the model. We saved the model for deploying our solution to the various platforms. 3. Deployment: After training the model, we built the frontend which is totally client-based using JavaScript and microservice “Flask”. Rather than saving the input videos to our server, we are sending our AI to the client’s place and using Microsoft Azure for the deployment. We are having on-premise and cloud solutions prepared. At the moment, we are on a trail so we can’t provide the link URL. After building the AI part and frontend, We integrated our solution to the IP and CCTV cameras available in our house and checked the performance of our solution. Our solution works in real-time on video footage with very good accuracy and performance. Challenges we ran into There are always a few challenges when you innovate something new. The biggest challenge is “The Novel Coronavirus” itself. For that reason, we can’t go outside the home for the hardware and embedded parts. We are working virtually to build innovative solutions but as of now, we are having very limited resources. We can’t go outside to buy hardware components or IP & CCTV cameras. One more challenge we faced was that we were not able to validate our solution with drones in the early days due to the lockdown but after taking permission from the officials that problem was not a deal anymore. Accomplishments that we're proud of Good work brings the appreciation and recognition. We have submitted our research paper in several conferences and international journals (Waiting for the publication). After developing the basic proof-of-concept, We went on to the local government officials and submitted our proposal for a trial to check our solution for better surveillance because the lockdown is near to be lifted. Our team is also participating in several hackathons and tech event virtually to showcase our work. What we learned Learning is a continuous process. We mainly work with the AI domain and not with the Drones. The most important thing about this project was “Learning new things”. We learned how to integrate “Masked AI” into Drones and deploy our solution to the cloud. We added embedded skills in our profile and now exploring more features on that part. The other learning part was to take our proof of concept to the local administration for trails. All these “Government Procedures” like writing Research Proposal, Meeting with the Officials, etc was for the first time and we learned several protocols to work with the government. What's next for Masked AI: Masks Detection and Recognition We are looking forward to collaborating with local administrative and the government to integrate our solution for drone-based surveillance (that’s currently in trend to monitor internal areas of the cities). Parallel, The improvement of model is the main priority and we are adding “Action Recognition” and “Object Detection” features in our existing solution for even robust and better solution so decision-makers can make ethical decisions as because surveillance using Deep Learning algorithms are always risky (bias and error in judgments). Built With azure darknet flask google-cloud javascript nvidia opencv python tensorflow twilio yolo

https://devpost.com/software/covidcentral-u21txv

Landing Page Landing Page Landing Page Landing Page - Contact Us Section Signup Page Login Page Content Summarizer Comparison of 4 Types of Content Summarizer Text Insights Preprocessing Inspiration This year has been really cruel to humanity. Australia is being ravaged by the worst wildfires seen in decades, Kobe Bryant’s passing , and now this pandemic due to the Novel Coronavirus originated from the Hubei province (Wuhan) of China. Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. More than 3 million people are affected by this deadly virus across the globe (Source: World O Meters). There have been around 249,014 deaths already and it’s counting. 100+ countries are affected by this virus so far. This is the biggest health crisis in the last many years. Artificial Intelligence has proved its usefulness in this time of crisis. The technology is one of the greatest soldiers the world could ever get in the fight against coronavirus. AI along with its subsets (Machine Learning) is leveraging significant innovation across several sectors and others as well to win against the pandemic. After Anacode releases “The Covid-10 Public Media Dataset” , we took this as an opportunity to use Natural Language Processing on those data composed of Articles. According to Anacode “It is a resource of over 40,000 online articles with full texts which were scraped from online media in the timespan since January 2020, focussed mainly on the non-medical aspects of COVID-19. The data will be updated weekly”. Anacode further says “We are sharing this dataset to help the data community explore the non-medical impacts of Covid-19, especially in terms of the social, political, economic, and technological dimensions. We also hope that this dataset will encourage more work on information-related issues such as disinformation, rumors, and fake news that shape the global response to the situation.” Our team leveraged the power of NLP and Deep Learning and built “CovidCentral” , a PaaS (Platform as a Service) . We believe our solution can help media people, researchers, content creators, and everyone else who is reading and writing articles or any kind of content related to the COVID-19. What it does Our tagline says “Stay central with NLP powered text analytics for COVID-19”. CovidCentral is one of its kind NLP driven platform for fast and accurate insights. It generates a summary and provides analytics of large amounts of social and editorial content related to COVID-19. STAY CENTRAL INSHORTS. It does three things: 1. CovidCentral platform can help to understand large contexts related to COVID-19 in a matter of minutes. Through the platform, Get actionable insights from hundreds of thousands of lines of texts in minutes. It generates an automated summary of large contents and provides word-by-word analytics of the texts from total word count to the meaning of each word. The user can either enter an URL to summarize and getting insights or enter the complete content directly into the platform. 2. The large content of text data is hard to analyze. It is very difficult to analyze the large content of texts. CovidCentral can help people to get insights within minutes. Manual analysis of texts leads to a number of hours. Media people, researchers, or anyone who is having the internet can access our platform and get the insights related to the COVID-19. 3. Humans are lazy in nature and people want to save time. This platform can generate content’s summary within minutes via a single URL. CovidCentral uses NLP and Deep Learning technologies to provide an automated summary of texts. Very helpful for getting short facts related to the COVID-19. Why Use CovidCentral? 1. Fast 2. Ease of Use (User-friendly) 3. High Accuracy 4. Secure (No content or data will be saved in the server rather we are sending NLP to you at the frontend.) How we built it We built CovidCentral using AI technologies, Cloud technologies, and web technologies. This platform uses NLP as a major technique and leverages several other tools and techniques. The major technologies are: a. Core concept: NLP (Spacy, Sumy, Gensim, NLTK) b. Programming Languages: Python and JavaScript c. Web Technologies: HTML, CSS, Bootstrap, jQuery ( JS) d. Database and related tools: SQLITE3 and Firebase (Google's mobile platform) e. Cloud: AWS Below are the steps that will give you a high-level overview of the solution: 1. Data Collection and Preparation: CovidCentral is built on mainly using “Covid-19 Public Media Dataset” by Anacode. A dataset for exploring the non-medical impacts of Covid-19. It is a resource of over 40,000 online articles with full texts related to COVID-19. The heart of this dataset are online articles in text form. The data is continuously scraped from a range of more than 20 high-impact blogs and news websites. There are 5 topic areas - general, business, finance, tech, and science. Once we got the data, the next step is obviously “Text Preprocessing”. There are 3 main components of text preprocessing: (a) Tokenization (b) Normalization (c) Noise Removal. Tokenization is a step that splits longer strings of text into smaller pieces, or tokens. Larger chunks of text can be tokenized into sentences, sentences can be tokenized into words, etc. Further processing is generally performed after a piece of text has been appropriately tokenized. After tokenization, we performed “Normalization” because, before further processing, the text needs to be normalized. Normalization generally refers to a series of related tasks meant to put all text on a level playing field: converting all text to the same case (upper or lower), removing punctuation, converting numbers to their word equivalents, and so on. Normalization puts all words on equal footing and allows processing to proceed uniformly. In the last step of our Text preprocessing, we performed “Noise Removal” . Noise removal is about removing characters digits and pieces of text that can interfere with your text analysis. Noise removal is one of the most essential text preprocessing steps. 2. Model Development: We have used several NLP libraries and frameworks like Spacy, Sumy, Gensim, and NLTK. Apart from having a custom model, we are also using pre-trained models for the tasks. The basic workflow of creating our COVID related NLP based summarizer or analytics engine is like this: Text Preprocessing (remove stopwords, punctuation). Frequency table of words/Word Frequency Distribution – how many times each word appears in the document Score each sentence depending on the words it contains and the frequency table. Build a summary or text analytics engine by joining every sentence above a certain score limit. 3. Interface: CovidCentral is a responsive platform that supports both i.e. Mobile and web. The frontend is built using web technologies like HTML, CSS, Bootstrap, JavaScript (TypeScript, and jQuery in this case). We have used a few libraries for validation and authentication. On the backend part, it uses python microservice “Flask” for integrating the NLP models, SQLITE3 for handling the database, and Firebase for authentication and keeping records from the User forms. 4. Deployment: After successfully integrating backend and frontend into a platform, we deployed CovidCentral on the cloud. It runs 24*7 on the cloud. We deployed our solution on Amazon Web Services (AWS) and use an EC-2 instance as a system configuration. Challenges we ran into Right now, the biggest challenge is “The Novel Coronavirus”. We are taking this as a challenge and not as an opportunity. Our team is working on several verticles whether it is medical imaging, surveillance, bioinformatics and CovidCentral to fight with this virus. There were a few major challenges: Time constraint was a big challenge because we had very little time to develop this but we still pulled CovidCentral in this short span of time. The data which has more than 40K articles are pretty much messy, so we got difficulties dealing with messy data in the beginning but after learning how to handle that kind of data, we eliminated that challenge to some extent. We also got challenges while deploying our solution to the cloud but managed somehow to do that and still testing our platform and making it robust. Accomplishments that we're proud of Propelled by the modern technological innovations, data is to this century what oil was to the previous one. Today, our world is parachuted by the gathering and dissemination of huge amounts of data. In fact, the International Data Corporation (IDC) projects that the total amount of digital data circulating annually around the world would sprout from 4.4 zettabytes in 2013 to hit 180 zettabytes in 2025. That’s a lot of data! With such a big amount of data circulating in the digital space, there is a need to develop machine learning algorithms that can automatically shorten longer texts and deliver accurate summaries that can fluently pass the intended messages. Furthermore, applying text summarization reduces reading time, accelerates the process of researching for information, and increases the amount of information that can fit in an area. We are proud of the development of CovidCentral and to make it Open Source so anyone can use it for free on any kind of device to get important facts related only to COVID-19. What we learned Learning is a continuous process of life, the pinnacle of the attitude and vision of the universe. I tell my young and dynamic team (Sneha and Supriya) to keep on learning every day. In this lockdown situation, we are not able to meet each other but we learned how to work virtually in this kind of situation. Online meeting tools like Zoom in our case, GitHub, Slack, etc helped all of us in our team to collaborate and share our codes with each other. We also strengthen our skills in NLP (BERT, Spacy, NLTK, etc) and how to integrate our models to the front-end for end-users. We spent a lot of time on the interface so people can use it and don’t get bored. From design to deployment, there were many things that helped us improve our skills technically. We learn many things around us day by day. Since we are born, we learn many things, and going forward, we will add more relevant features by learning new concepts in our platform. What's next for CovidCentral We are adding features like “Fake News Detector” to spam fake news related to the COVID-19 very soon on our platform. CovidCentral’s aim is to help content creators, media people, researchers, etc to only read that matters the most in a quick time. APIs to be released soon so anyone who wants to add these features in their existing workflow or website can do it so they won’t need to use our platform rather they can just use our APIs. We are also in discussion with some text analytics companies to collaborate and bring an even more feasible, robust, and accessible solution. In the near future, we will make CovidCentral an NLP powered text analytics platform in general for all kinds of text analytics for anyone, free to use from anywhere on any kind of devices (Mobile, Web, Tablet, etc). Built With amazon-web-services bootstrap css firebase flask html javascript natural-language-processing nltk python sqlite Try it out covidcentral.herokuapp.com

https://devpost.com/software/covnatic-covid-19-ai-diagnosis-platform

Landing Page Login Page Segmentation of Infected Areas in a CT Scan Check Suspects using Unique Identification Number (New Suspect) Check Suspects using Unique Identification Number (Old Suspect) Suspect Data Entry COVID-19 Suspect Detector Upload Chest X-ray Result: COVID-19 Negative Upload CT Scan Result: Suspected COVID-19 Realtime Dashboard Realtime Dashboard Realtime Dashboard View all the Suspects (Keep and track the progress of suspects) Suspect Details View Automated Segmentation of the infected areas inside CT Scans caused by Novel Coronavirus Process flow of locating the affected areas U-net (VGG weights) architecture for locating the affected areas Segmentation Results Detected COVID-19 Positive Detected Normal Detected COVID-19 Positive Detected COVID-19 Positive GIF Located infected areas inside lungs caused by the Novel Coronavirus Endorsement from Govt. Of Telengana, Hyderabad, India Endorsement from Govt. Of Telengana, Hyderabad, India Generate Report: COVID-19 Possibility Generate Report: Normal Case Generated PDF Report Inspiration The total number of Coronavirus cases is 2,661,506 worldwide (Source: World o Meters). The cases are increasing day by day and the curve is not ready to flatten, that’s really sad!! Right now the virus is in the community-transmission stage and rapid testing is the only option to battle with the virus. McMarvin took this opportunity as a challenge and built AI Solution to provide a tool to our doctors. McMarvin is a DeepTech startup in medical artificial intelligence using AI technologies to develop tools for better patient care, quality control, health management, and scientific research. There is a current epidemic in the world due to the Novel Coronavirus and here there are limited testing kits for RT-PCR and Lab testing . There have been reports that kits are showing variations in their results and false positives are heavily increasing. Early detection using Chest CT can be an alternative to detect the COVID-19 suspects. For this reason, our team worked day and night to develop an application which can help radiologist and doctors by automatically detect and locate the infected areas inside the lungs using medical scan i.e. chest CT scans. The inspirations are as below: 1. Limited kit-based testings due to limited resources 2. RT-PCR is not as much as accurate in many countries (recently in India) 3. RT-PCR test can’t exactly locate the infections inside the lungs AI-based medical imaging screening assessment is seen as one of the promising techniques that might lift some of the heavyweights of the doctors’ shoulders. What it does Our COVID-19 AI diagnosis platform is a fully secured cloud based application to detect COVID-19 patients using chest X-ray and CT Scans. Our solution has a centralized Database (like a mini-EHR) for Corona suspects and patients. Each and every record will be saved in the database (hospital wise). Following are the features of our product: Artificial Intelligence to screen suspects using CT Scans and Chest X-Rays. AI-based detection and segmentation & localization of infected areas inside the lungs in chest CT. Smart Analytics Dashboard (Hospital Wise) to view all the updated screening details. Centralized database (only for COVID-19 suspects) to keep the record of suspects and track their progress after every time they get screened. PDF Reports, DICOM Supports , Guidelines, Documentation, Customer Support, etc. Fully secured platform (Both On-Premise and Cloud) with the privacy policy under healthcare data guidelines. Get Report within Seconds Our main objective is to provide a research-oriented tool to alleviate the pressure from doctors and assist them using AI-enabled smart analytics platform so they can “SAVE TIME” and “SAVE LIVES” in the critical stages (Stage-3 or 4). Followings are the benefits: 1. Real-world data on risks and benefits: The use of routinely collected data from suspect/patient allows assessment of the benefits and risks of different medical treatments, as well as the relative effectiveness of medicines in the real world. 2. Studies can be carried out quickly: Studies based on real-world data (RWD) are faster to conduct than randomized controlled trials (RCTs). The Novel Coronavirus infected patients’ data will help in the research and upcoming such outbreak in the future. 3. Speed and Time: One of the major advantages of the AI-system is speed. More conventional methods can take longer to process due to the increase in demand. However, with the AI application, radiologists can identify and prioritize the suspects. How we built it Our solution is built using the following major technologies: 1. Deep Learning and Computer Vision 2. Cloud Services (Azure in this case) 3. Microservices (Flask in this case) 4. DESKTOP GUIs like Tkinter 5. Docker and Kubernetes 6. JavaScript for the frontend features 7. DICOM APIs I will be breaking the complete solution into the following steps: 1. Data Preparation: We collected more than 2000 medical scans i.e. chest CT and X-rays of 500+ COVID-19 suspects around the European countries and from open source radiology data platform. We then performed validation and labeling of CT findings with the help of advisors and domain experts who are doctors with 20+ experience. You can get more information in team section on our site. After carefully data-preprocessing and labeling, we moved to model preparation. 2. Model Development: We built several algorithms for testing our model. We started with CNN for classifier and checked the score in different metrics because creating a COVID-19 classifier is not an easy task because of variations that can cause bias while giving the results. We then used U-net for segmentation and got a very impressive accuracy and got a good IoU metrics score. For the detection of COVID-19 suspects, we have used a CNN architecture and for segmentation we have used U-net architecture. We have achieved 94% accuracy on training dataset and 89.4% on test data. For false positive and other metrics, please go through our files. 3. Deployment: After training the model and validating with our doctors, we prepared our solutions in two different formats i.e. cloud-based solution and on-premise solution. We are using EC-2 instance on AWS for our cloud-based solution. Our platform will only help and not replace the healthcare professionals so they can make quick decisions in critical situations. Challenges we ran into There are always a few challenges when you innovate something new. The biggest challenge is “The Novel Coronavirus” itself. One of the challenge is “Validated data” from different demographics and CT machines. Due to the lockdown in the country, we are not able to meet and discuss it with several other radiologists. We are working virtually to build innovative solutions but as of now, we are having very limited resources. Accomplishments that we're proud of We are in regular touch with the State Government (Telangana, Hyderabad Government). Our team presented the project to the Health Minister Office and helping them in stage-3 and 4. Following accomplishments we are proud of: 1. 1 Patent (IP) filled 2. 2 research paper 3. Partnership with several startups 4. In touch with several doctors who are working with COVID-19 patients. Also discussing with Research Institutes for R&D What we learned Learning is a continuous process. Our team learnt "the art of working in lockdown" . We worked virtually to develop this application to help our government and people. The other learning part was to take our proof of concept to the local administration for trails. All these “Government Procedures” like writing Research Proposal, Meeting with the Officials, etc was for the first time and we learned several protocols to work with the government. What's next for M-VIC19: McMarvin Vision Imaging for COVID19 Our research is still going on and our solution is now endorsed by the Health Ministry of Telangana . We have presented our project to the government of Telangana for a clinical trail . So the next thing is that we are looking for trail with hospitals and research Institutes. On the solution side, we are adding more labeled data under the supervision of Doctors who are working with COVID-19 patients in India. Features like Bio-metric verification, Trigger mechanism to send notification to patients and command room , etc are under consideration. There is always scope of improvement and AI is the technology which learns on top of data. Overall, we are dedicated to take this solution into real world production for our doctors or CT and X-rays manufacturers so they can use it to fight with the deadly virus. Built With amazon-web-services flask google-cloud javascript keras nvidia opencv python sqlite tensorflow Try it out m-vic19.com

https://devpost.com/software/papure-2tpv60

paPURE Setup - Angeled View - Utilizing Snorkeling Mask paPURE Setup - Front View - Utilizing Snorkeling Mask paPURE Setup - Side View - Utilizing Snorkeling Mask paPURE Setup - Back View - Utilizing Snorkeling Mask Original Prototype of paPURE Design View paPURE Base - Top View - Inserted Compressor Fan and Fan Shroud paPURE Base - Top View - Empty Abstract: The Filtrexa paPURE is an affordable, 3D printed powered air-purifying respirator (PAPR) that provides our healthcare providers with better protection than even N95s, especially in high-risk and confined environments (E.g. ICUs, ERs). It incorporates readily available components and can be easily manufactured locally. We can thus increase accessibility of PAPR technology by enabling hospitals to produce and purchase it as per their need, optimizing the 3D-print to produce it at a cost that is over ten times cheaper than PAPRs currently offered on the market, and using exchanging highly specific components for readily available and affordable components. The Filtrexa paPURE also has made design changes to improve comfort, ease of use, and longevity of PAPR technology. Introduction One of the most immediate and impactful effects of the COVID-19 pandemic are global shortages of proper personal protective equipment (PPE), forcing healthcare providers (HCPs) to consistently work in high-risk environments and unnecessarily place their own lives at risk. Our product is a powered air-purifying respirator (PAPR) that creates a positive pressure field with filtered air to protect frontline healthcare workers from airborne threats such as SARS, TB, measles, influenza, meningitis, and most immediately COVID-19. This technology improves upon current PAPR devices in terms of cost-efficacy, ease of access, and ease of implementability. Our solution not only serves to combat general PAPR shortages across the country, but also eases PPE shortages that arise from COVID-19 and future patient surges through an on-demand 3D printing process. Value Proposition Powered, air-purifying respirators (PAPRs) are currently the gold standard in medicine when treating patients diagnosed with COVID-19 and other highly infectious respiratory diseases[1] due to their positive pressure system. This system filters air extremely effectively before it reaches the airway. However, this technology package is costly, often totaling over $1800[2] and requires highly specific components which are currently in short supply. Both well-established hospitals such as the Mayo Clinic (with a ratio of 4500 physicians to 200 PAPRs)[2] and smaller county hospitals such as the Hunterdon Medical Center (where not a single PAPR is available to physicians) are facing critical shortages of personal protective equipment (PPE). Evidently, the aforementioned barriers render PAPR technology inaccessible to most frontline HCPs, leaving them far more vulnerable to infection. Alternatives to PAPR technology include N95s, surgical masks, and currently, homemade masks due to a worldwide shortage of PPE. Although they provide a barrier against aerosols, standard and surgical N95s are easily compromised with an improper fit and have an assigned protection factor (APF) of ten[4], while PAPRs have an APF of 25 to 1000, rendering PAPRs far more effective at protecting HCPs. Additionally, physicians tend to prefer PAPRs over N95s because PAPRs are reusable, easier to breathe through, do not require fit testing, and make them feel safer[1][5]. Our Solution In order to provide purified air to those in the most high-risk environments, we have developed a novel, inexpensive, and accessible PAPR device that is both lightweight and 3D-printable within 24 hours. Printed using readily-available filaments (e.g. PLA, ABS), paPURE is mounted to the user’s hip and assembled via on-hand motors and batteries. (See Appendix 2.5). Through PAPR technology, HCPs are given access to filtered positive pressure air systems (in which airflow serves to seal any gaps in masks, as well as reduce respiratory fatigue in HCPs), drastically decreasing infection risk in areas such as ICUs and ERs. Our device’s customizability allows for interoperability with existing masks, filters, and hosing (See Appendix 3.1), enabling hospitals, or possibly surrounding hobbyists/machinists (regulatory dependent), to produce PAPRs for their physicians and nurses. For images and procedures: See Appendix 1 and 2. The system features a dual battery set-up that allows HCPs to utilize one or both batteries independently, as well as swap out batteries while the device is in use (such as during an extended patient procedure that a physician cannot leave from). Additionally the belt system, with the fan/chassis on you lumbar and 2 battery on ports on both hips gives a better weight distribution for improved comfort in extended usages (such as a surgeon leaning in an awkward position during the operation). The use of an inline filter means that air is pushed into a filter at the end of the device, as opposed to regular PAPRs that pull air through filters. This setup means that the risk of an imperfect seal compromising air quality is virtually nullified as no negative pressure system exists after air filtration in our device. Additionally, the aforementioned inline filters are better at filtering biological particles without disturbing airflow than standard P100s and are already used extensively in anesthesiology and respiratory care departments of hospitals across the country. After printing the device’s chassis and shroud, integration with an inline bacterial/viral filter, housing, and masks will be followed by on-site fit and efficacy testing to ensure proper device assembly.[6] Then, an HCP would don their mask, clipping the paPURE chassis and two smart power tool batteries to a provided utility belt, and connecting to the mask via a hose. At most, we expect equipping paPURE to add 1-3 minutes to a medical professional’s routine and greatly improve safety and comfort. An Improvement from Traditional PAPRs Our technology eliminates the need for a middle-man manufacturer. Because the only required components are readily available to hospitals and clinics, hospitals can produce the device as per their need. We anticipate working with local 3D-printing facilities to produce and assemble the product, then to distribute the Filtrexa PAPR to hospitals. Physicians and NIOSH officials (most notably Richard Metzler, the first Director of the National Personal Protective Technology Laboratory at NIOSH), have already given us promising feedback regarding the need for this technology, and we are looking into potential partnerships with PPE developers and/or motor manufacturers. Some hospital purchasing experts have additionally communicated a need for affordable PAPRs. Our solution is over 10 times cheaper than current PAPR technologies ($155; see Appendix 2, Figure 2), increasing likelihood of adoption. To allow smaller hospitals to easily obtain our technology, we plan to raise awareness of our business through phone calls and emails to hospitals throughout the country. Implementation Plan paPURE’s solution is implementable almost immediately. The main barrier between our tested prototype and implementation is FDA/NIOSH approval (FDA EUA Sec II/IV Approve NIOSH Certified Respirators). We have also identified conditions that will allow us to expedite the regulation and roll-out of the production (such as the IDE and 501(k) pathways suggested to us by regulatory experts).[15] Because our device is based on existing PAPR technology, this predicate nature in combination with existing precedents for 3D-printed medical technology, can help expedite its deployment.[16] Our technology minimizes the need for a middle-men. We are partnering with regional additive manufacturers to allow for quick, standardized, yet still decentralized production of the device. The only required components are readily available to hospitals and clinics, allowing HCPs to produce the device as per their need. Additionally, if regulatory approval permits, we may utilize local schools/universities/hospitals with on-site 3D printers in order to allow for fully decentralized manufacturing. After NIOSH Approval, our device (and depending on regulatory guidelines, possibly our CAD file) will be sent to those with 3D printers available, who could print and assemble the device (See Appendix 3.1). Players involved in the production of this technology would be hospital assembly workers, but the design is easily assembled by anyone (the only limitation being that assembly be done under a fume hood to prevent contamination). Physicians we’ve already talked to have given us promising feedback regarding the need for this technology. We are currently looking into potential partnerships with PPE developers (See Appendix 3.2) and/or motor manufacturers. Our solution is over ten times cheaper than current PAPR technologies (See Appendix 3.3), increasing the likelihood of adoption. Due especially to the length of this health crisis, hospitals are facing dire shortages of PPE. This has accelerated our timeline, but we are confident that it is feasible given the current state of emergency (See Appendix 3.4). Since this product has yet to be implemented in hospitals, we are writing to you today to gauge your interest in paPURE. Additionally, any feedback you have relating to our product or interest in helping us with laboratory testing of paPURE would be greatly appreciated. We anticipate our project to reach full fruition within 6-12 months. Our timeline is as follows. Our second iteration of prototyping for clinician testing will conclude in 2-3 weeks, followed by initial clinical testing, which will finish in around 1.5 months. As soon as clinical testing is finished and the product is validated, we will submit our product officially to NIOSH for regulatory approval. We anticipate receipt of regulatory approval within 1.5 months from submission. After approval is obtained, we will also apply for either a provisional patent or copyright, depending on legal advice. Within 1-2 months after regulatory approval, we plan to roll out our product to hospitals via centralized 3D-printing. During the next 1-2 months, we will continue to iterate and optimize the product. Official hospital rollout, with multiple 3D-printing partners and company partnerships, will occur around a month later. This will be around 6-7 months from now. As seen, our timeline is aggressive as we wish to equip healthcare providers with PPE as soon as possible. The prior goals mentioned in our timeline are our key goals and objectives for the project at this time. Current Testing and Partnerships Technical Testing is being carried out at Filrexa's primary residence and at Johns Hopkins University and includes analysis of airflow data, battery life, and filtration efficacy. For clinical testing, we already have established connections for clinical testing with both Johns Hopkins Medical Institute and Stanford University. In regards to business-focused assistance, we have also partnered with FastForwardU for advising regarding intellectual property protection, strategic marketing, and clinical networking. Planned Partnerships We plan to designate one 3D-printing company (current candidates include Xometry, Protolabs, Cowtown, and Health3D) as our manufacturer during our initial launch into the market, but will continue to partner with additional 3D-printing companies as our business grows. Due to our unique manufacturing approach, all hospitals, regardless of their size, will be able to order and quickly receive PAPRs, lowering the impact of the current shortage. In order to supply the auxiliary materials such as motors, batteries, and more, we plan to initiate company partnerships with large corporations such as 3M, Dyson, Black and Decker, GE, Cuisinart, Hitachi, Makita, Shop Vac, Hoover, Bissell, Shark, iRobot, and Bosch. Additional Video https://youtu.be/iFMtzt52BEQ Appendix and Citations Click here! Website paPURE Website Built With 3dprinting cad cpap p100

https://devpost.com/software/smarttracker-covid19

Inspiration : Now a days whole world facing the novel Corona Virus, to track the spread of novel Corona Virus country-wise, details of confirmed cases, deaths and Recovered, awareness regarding COVID-19. This Android app was created to spread awareness about the covid -19 virus. What it does : The Android app named as ‘SmartTracker-Covid-19’ created to spread awareness about the COVID -19 virus. App includes following functionalities: CoronaEx Section - This section having following sub components: • News tab: Having latest new updates. Fake news seems to be spreading just as fast as the virus but as we have integrated from official sources so everyone will be aware from fake news. • World Statistic tab: Real-time Dashboard that tracks the recent cases of covid-19 across the world. • India Statistic tab: Coronavirus cases across different states in India with relevant death and recovered cases. • Prevention tab: Some Prevention to be carried out in order to defeat corona. CoronaQuiz section - quiz that will help people know about the Corona virus and its effects on human body. It chooses random questions and show the correct answer for the questions and at the end user will get to know their highest score. Helpline Section - As this application particularly made for Indian citizen to use, all state helpline number of India included. Chatbot Section - A self-assisted bot made for the people navigate corona virus situation. Common Questions: Start screening,what is COVID-19? , What are the symptoms? How we built it : We built with using Android studio. For the quiz section we have used sqlite database and live news data we have integrated from the News API. For the coronavirus statistic we have collected data from worldometer and coronameter. Challenges we ran into : At time of integrating the chatbot in application. Accomplishments that we're proud of : Though , It was the first attempt to create chatbot.we have tried to up our level at some extent. What's next for SmartTracker-COVID19 : For the better conversation we will be looking to work more on chatbot. Built With android-studio chatbot java news quiz sqlite Try it out github.com

https://devpost.com/software/virtualcovid

GamePlayVeiw03 GamePlay View 04 GamePlay View 01 GamePlay View 02 Virtual Gaming: CoviFitness [Virtual Covid Game] This is an extension to the Covid Raccoon that I developed in extension to Covid Raccoon Game. Good news is that you can play it virtually! Kindly Refer to my Github repo or Youtube Video for better documentation as some images are missing here. CoviFitness is a 2D fun, interactive and awaring game made for kids and individuals to play the game with real time moves. Are you also getting bored and lazy this covid? Do you have a habbit of skippinig morning walks? Is your exercise getting rescheduled due to your sleep cycle? Do you also want flexible timing for work-out? Well in that case, CoviFitness is a must try! Installation Instructions Open Terminal and type the following command: pip install -r requirements.txt Once all the dependencies are installed, open the terminal and type the command: python3 CoronaIntegrated.py Calibrations When you run the code, the following text will appear on your screen: Don't move during this process, it tries to detect the face and accordingly do the calibration. Note that most of the movements are defined based on the facial orientation. Once the Calibration is successful, you will see this window: This will end by popping a cv2 window which will proceed to calibration, this is for calibrating the bending height, make sure your camera is positioned in such a way that your chin must be above this blue line. These lines are added with time delay so that they won't get changed quickly and allow for reaction time. In case you want to bring down the height even more you can modify this line of code in CoronaIntegrated.py . The popup screen looks like this: Move your right hand to the top-right box to lower the line, move your left hand to the top-left box to raise the height, once you're satisfied, move both of the hands to complete the calibration process. Once the calibration is complete the following screen pops up: Now enjoy the game, jump to make your character jump and crouch to make it crouch. Note that currently these controls are calibrated and the other control (like boxing gesture is in test mode). Project Components Computer Vision (OpenCV python) Pygame (For building intutive 2D game) Inspiration I have always been curious about learning new things, whether it be related to stem or something else (though, I am always inclined towards STEM). Game Dev is a booming field and seems to have a promising future if correctly used. Video games are no more just a source of fun and entertainment, today we can use this virtual technology (especially in fields of AR and VR) to make use of this tech and create a real-life learning experience. From the very beginning, this has caught my attention to the field of gaming. This project is one such attempt to demonstrate how these things can actually change the way we live. Though I am well versed with other Development (App-Dev/ Web-Dev/ Designing) and Instrumentation Tech (IoT/ Robotics etc.) but Game-Dev was always something which I wanted to learn, and that's what turned me to try it here for the first time after creating a very basic 2D game covid raccoon . What it does? The game is a story about a boy (Here it's me) who is sanetizing entire city and needs to safely reach his home, which is located at the end of the city. Various types of viruses, infected hosts and bats are roaming around the city, which need to be dotched or sanetized without coming in contact with them. Here are some of the GamePlay Screenshots: It allows you to Roam around the city, which is apparently static (unless you add your custom background :-P) and look for the virus-infected people or viruses escape them till you reach your home, which is at the end of your city. In this adventure, you will see different types of viruses that will try to infect you! and you're on a mission to reach your home while sanetizing the city and without getting infected. To escape from the viruses, you have to ensure that you don't come in contact with them at any cost! Also, you need to keep a distance from those who are already infected. Unless you're not sanitizer protected, any incoming virus can infect you. If you catch a sanitizer (which always happens), you will be able to blow it three times before it ends, and then you have to protect yourself against them. For all the land viruses, you need to jump and skip them. On the other hand, for all the air viruses, you need to bend down and let them pass away. With your speed, it takes a fixed amount of time to reach the end of the city where your sanitization process is over, and you could safely keep yourself locked unless the pandemic ends! How I built it? The whole project is built in Python using OpenCV (cv2) and Pygame Library. After finishing my first project (Covid Raccoon), I started working on integrating it with Vision functionality. This entire game is solely built in python with opencv and pygame library. The characters (in the form of png images) are prepared in Microsoft PowerPoint. Purpose of this Project I have created this project mainly because of three reasons: Keeping the World Corona fit by involving in the fun activity. This game will help them exercise in a fun way even from the home. Getting Exposure of Game Development This project has pretty much helped me to take my first step towards Game development, slowly I would try to dive deeper and do more customizations and learn more. For the Beginners and Developers For the Beginners and Developers who want to learn PyGame, I am planning on converting this project into Video Tutorial Series. This will not just be there for them to get started with PyGame but also to use this project as the base template to do the modifications in their own project. For the Kids and Babies to Develop their Minds to Generate Awareness about Cleanness and Sanetization This game could led to a positive awareness among the mind of kids and create a good image of importance of sanitation and hygene in maintaining their health, I am not sure how nicely it will work, but expect it to have some positive impact. Built With computer-vision haar-cascades image-processing opencv pygame python Try it out github.com

https://devpost.com/software/covi_fight

Inspiration The virus has affected humanity in various ways, be it our economy, our freedom of movement, and the loss of loved ones. Then how do we live on, comfortably, and safely with this virus around? Even after the lockdown is over, there is a massive possibility that traces of the virus will remain, and it can spread again. We wanted to bring people back their mobility and keep them safe at the same time. We wanted people to know about their status while they leave their houses. What it does CoviFight alerts me about the risks of catching the virus if I have come in contact with an infected person within the past three weeks. It also informs the healthcare system accurately about the spread of infection. CoviFight also generates a map with hotspots for what places have virus traces , so that people can prevent travelling at these places and authorities can sterilize or lockdown these places efficiently rather than having a complete lockdown of a country. How we built it We develop a three-tier app: • A user's app • A provider's app • An official's portal. While utilizing Bluetooth and GPS of your phone, CoviFight makes sure that the confidentiality of every individual is secured and can not be compromised. Data is encrypted using a secret key, and no one can view it without your permission. It only traces the past data of positively tested patients. This way, CoviFight also meets the GDPR compliance. By using Geo-fencing and Machine Learning , we predict your chances of catching the infection so that you can take preventive measures. A provider's app for aggregation points like shops, restaurants, and public transport synchronizes with the nearby user app. This interface is the key to the detection of infection points, be it a stationary workplace or a moving vehicle . If McDonald's installed CoviFight and had an infected customer in the past 15 days, all the customers after the positive tested patient would get alerted, and hence the restaurant can be sterilized. Only the medical system may update a person's status over the official's portal, and the authenticity of the app is maintained hence preventing false positives or self-reporting, which might lead to falsification of records. So, with the help of our app, people can move around while being alerted about their status, stay away from the virus, and be free from the worry of their privacy maintenance at the same time. Take a look at our demo by clicking here Challenges we ran into To maintain the authenticity of the predictions and analysis, we were initially in a fix as to how to update a person's status as positive or negative. Then we decided to come up with a three-tier system, and we developed a Doc App or official's portal, which is only accessed by the medical system so that the authenticity is maintained. No one else can manipulate the data. Accomplishments that we're proud of • We have made sure that the privacy of every individual is maintained and can not be compromised. The encryption algorithms meet the standards of the leading social networking apps existing in the market. • CoviFight not only alerts people about their own risks but provides heatmaps of the traces of the virus too. CoviFight also shows what specific restaurant or public transport( like a bus or a train) may be infected precisely. • We do not need to compare data between people, thus making computation very cheap and exponentially faster and efficient. Our Journey So Far • Winners( Runner up) in the #EUvsVirus, a Pan-European Hackathon Organised by the European Innovation Council to counter COVID-19 pandemic with more than 9k participants and 2000 teams. We stood second in the Real time Communication and Prevention challenge. • Top 6 finalists of The Global Hack, by Garage48, April 2020 The Global Hack is a hackathon designed to share and rapidly develop ideas for urgently needed solutions in the face of the COVID-19 crisis, and to build resilience post-pandemic, with over 12k participants from 100+ countries. The team developed a mobile application solution for the containment and tracking of this virus. We were in the top 6 teams in the Crisis Response Track. • We were also in the Top 23 Student Innovators in COVID-19 SAMADHAN MHRD( Ministry of Human Resource Development, India) Mega Online Challenge What we learned It has been an enjoyable experience to work with people who have not even met each other before and still successfully develop this amazing app. We learned a lot through the hackathon, from interacting with the mentors and getting their guidance, to develop the app. What's next for CoviFight We plan to get this deployed at its earliest so that people may get their safe mobility back. We plan to deploy this on the Play Store and make a version for iOS as soon as we can. We are also in touch with the Indian Government and we might be able to save lives in India also. The necessities to continue the project: • Approval from government authorities to implement and track data. • Participation from Hospitals/government bodies to update the status of a patient so that system can generate realtime alerts and mark hotspots. • Cloud resources to scale up the project. Currently limited by the free tier of cloud infrastructure. The value of our solution after the crisis: • This application can be used for any contagious disease management. • It can be used in disaster management to understand the right victims and relief reaches all rightful beneficiaries( such as in the case of floods and storms). • It can be used by Providers such as McDonald's and Public transport systems to implement targeted location-based marketing complying with data collection practices. What we have done till now. • Implemented masked identities for users to comply with GDPR and privacy requirements. • Identification of hotspots in realtime based on the patient status update. • Fixed bugs in the flow and to make it work E2E. • Produced a product demo. New Technology introduces • Blockchain to manage user identification data(making it immutable), adding the security of ECC digital signature • Moving from NoSQL mogoDB to a hybrid of BlockChain and GraphDB for better analysis and prediction while keeping the user's id secrete on the Graph • Use of Kubernetes for creating multiple threads for gaining concurrency •Adding caching mechanism to mobile devices to handle any kind of network failure. Built With firebase google-directions har java machine-learning maps python Try it out github.com sidhantha.medium.com

https://devpost.com/software/teledoc

Product Roadmap Inspiration Have you ever had shortness of breath, a high temperature, and a really dry cough? Well, I am sure you might say you had COVID-19. In fact, 20% of these cases are asymptomatic. You might not know you are infected! What if there was a time where you never had to go to a doctor to get checked up, to find what you had? We would like to build the much needed medical tricorder of our time, to automatically diagnose and screen infectious diseases remotely without the patient's intervention. The problem our project solves COVID-19 has impacted the lives of literally everyone on the planet. As such we now live in a different world, and even beyond the COVID-19 effective preventative measures need to be put in place in all public settings including hospitals, airports, hotels, workplaces, and so on. Our vision is to build a screening machine that could be used readily for the screening of diseases. Our final product will look something like a conventional metal-detector chamber installed at airports, but will the capability to screen people for diseases and infections. For this to be possible, none of the existing methods, include X-Rays/CT/PET/MRI etc, can be used as they all involved the use of ionising radiation and hence cannot be used in public spaces. Not to mention these solutions are bulky and expensive in addition to having long scan times to produce their results. Our solution utilises harmless non-ionising RF radiation, with emission levels on par with cellphones, ensuring the complete safety of the public and the machine operator. We plan to initially focus on the airport screening application, and are hoping that our product will help open up the airports once again. After proving the effectiveness of our product on airports, we plan to scale up to other immediate verticals including hospitals and workplaces. In this way we are aiming for a huge global-scale impact through our products. What it does Our Solution is an AI-powered remote/non-invasive Telediagnostic detection and screening tool for diseases and infections, saving trillions of pounds and millions of lives to effectively diagnose late-stage COVID-19. Our software tells you the percentage chance of having COVID-19 as well as relay vital information to the primary care specialist for further diagnosis. Our key differentiator from other AI software is that our powerful software can successfully distinguish between bacterial and viral infections. In the hardware part, we plan to build a handheld portable microwave tomography system based on impulse radio ultrawideband (UWB) radar technology. Microwave tomography is the only non-ionising tomography technique which is not only safe for human beings but also is much more compact, cheap and fast. It generates images on par with CT scans to quickly image the internal human organs for on-the-spot decision making by health professionals, cutting the wait out of lengthy conventional tomography procedures using expensive equipment. How we built it We are using Imagenet to do transfer learning on 1000+ CT and X-Rays scans. With an API using Flast and Node.JS to serve data from our API to doctors/frontline staff via our Web App. In the hardware part, we plan to build an impulse radio ultrawideband (UWB) radar based handheld microwave tomography system. Microwave tomography is the only non-ionising tomography technique which is not only safe for human beings but also is much more compact and cheap. Challenges we ran into Getting contacts in the healthcare industry and space has been a challenge to validate our idea, which we have partially overcome by interviewing two doctors and one clinical pharmacist until now. Our further challenges include working with hospitals and the governments to guide the development of our product. Any contacts will be valuable. Getting approval from the medical boards and the legal compliance will be the key challenges to address. Accomplishments that we're proud of We believe we are the best people to build this tech, as Kashif has a PhD in Radar technology with 13 publications and pioneered Radar-based remote telemetry technology for pedestrian safety, for which he has won the British Engineering Excellence Award in 2015. Cyril has 5 years of experience in building startups. He worked Human-Computer Interaction Lab and built software for screening anxiety/depression and physical therapy that went on to get funding from the NSF and NIH. He has 3 patents issued with the design and software of Unmanned Aerial Vehicles. What's next for TeleDoc We are part of Entrepreneur First Accelerator and looking to take our product to market according to the following roadmap: Jun 2020: AI-powered COVID-19 triage tool MVP release Sep 2020: Radar-based remote pulse/heart-rate monitor prototype release. Also, AI triage tool final release. Dec 2020: Radar-based remote pulse/heart-rate monitor final release. Also, Radar-based remote blood pressure monitor prototype release Mar 2021: Radar-based remote blood pressure monitor final release. Also, Radar-based remote blood glucose monitor prototype release Jun 2021: Radar-based remote blood glucose monitor final release. Also, Radar-based remote chest wall dynamics monitor prototype release References J. Marimuthu, K. S. Bialkowski and A. M. Abbosh, "Software-Defined Radar for Medical Imaging," in IEEE Transactions on Microwave Theory and Techniques, vol. 64, no. 2, pp. 643-652, Feb. 2016. Paulson, C. N., Chang, J. T., Romero, C. E., Watson, J., Pearce, F. J., & Levin, N. (2005). Ultra-wideband radar methods and techniques of medical sensing and imaging. In B. M. Cullum, & J. C. Carter (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 6007). [60070L] [ https://doi.org/10.1117/12.630004 ] T. Lauteslager, M. Tømmer, T. S. Lande and T. G. Constandinou, "Coherent UWB Radar-on-Chip for In-Body Measurement of Cardiovascular Dynamics," in IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 5, pp. 814-824, Oct. 2019 Y. Han, T. Lauteslager, T. S. Lande and T. G. Constandinou, "UWB Radar for Non-contact Heart Rate Variability Monitoring and Mental State Classification," 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 6578-6582. Vejella, Sujitha. “A MEMS BASED MICROWAVE PIXEL FOR UWB RADAR BASED 3-D DIAGNOSTIC IMAGING.” (2017). Lee, Y., Park, J., Choi, Y. et al. A Novel Non-contact Heart Rate Monitor Using Impulse-Radio Ultra-Wideband (IR-UWB) Radar Technology. Sci Rep 8, 13053 (2018). https://doi.org/10.1038/s41598-018-31411-8 Semenov S. Microwave tomography: review of the progress towards clinical applications. Philos Trans A Math Phys Eng Sci. 2009;367(1900):3021–3042. doi:10.1098/rsta.2009.0092 Built With css3 flask html keras node.js pm2 python react tensorflow Try it out bit.ly

https://devpost.com/software/healthhack-7vxsrp

window.fbAsyncInit = function() { FB.init({ appId : 115745995110194, xfbml : true, version : 'v3.3' }); // Get Embedded Video Player API Instance FB.Event.subscribe('xfbml.ready', function(msg) { if (msg.type === 'video') { // force a resize of the carousel setTimeout( function() { $('[data-slick]').slick("setPosition") }, 2500 ) } }); }; (function (d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = "https://connect.facebook.net/en_US/sdk.js"; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); HealthHack Inspiration The Frontliner Emergency Response Team What it does It has Emergency Contacts directly for first aid and the future Health Care System How I built it A system for Medical, Emergency Disaster Relief Team Challenges I ran into Understanding and Communication Teamwork Accomplishments that I'm proud of Trainings and experience What I learned HEALTH HACK can be a useful system especially this time of emergency What's next for HealthHack First Aid Health Care Built With emergency google-contacts health health-and-human-services-syndication language science.gov Try it out www.covidhealthhack.com

https://devpost.com/software/things-to-do-during-covid-lockdown-which-will-really-help-u

This time is a time most people are never used to which will definitely create imbalance in some aspect of your life Am sure if you follow some of this steps it will really help. What's next for Things To Do During Covid Lock-down which will really help U. THINGS TO DO DURING LOCK-DOWN PERIOD 1. Watch a film Netflix and Amazon Prime aren’t your only options, and you don’t necessarily have to pay for a subscription to watch plenty of excellent films. 2. Watch a documentary If you’re in the mood for something a bit more cerebral, there are a few websites that give you access to free documentaries. Whether you’re into sharks, revolutions, or serial killers, you’ll find something interesting to watch during lock-down. Some great sites include “Documentary Tube, Top Documentary Films and Documentary Heaven”. 3. WRITE A NOVEL Is it time for you to create rather than consuming? If you’ve always wanted to write a novel but never found the time or inspiration, this is your chance. Apparently Shakespeare wrote King Lear in isolation during the plague, so maybe this lock-down is when you’ll write your opus. 4. WRITE A SONG If you have a musical persuasion, you could channel your current emotions into a song or even an entire album of them. 5. TRY A FITNESS CHALLENGE Missing the gym? There are plenty of fitness challenges you can try out from home, so you can emerge from lock-down fitter, leaner, or stronger. 6. COOK SOMETHING NEW One good thing about being home a lot is that you can finally spend time cooking things from scratch. You can find great recipes online, even if you’re on a limited budget. 7. PLAY A BOARD GAME Board game lovers will be pleased to know that there are ways to play your favorite games online, so you don’t have to wait for the lock-down to end to try out your new Scythe strategy or to finally play Terra-forming Mars with a friend. 8. LEARN A LANGUAGE Always wanted to speak different languages? Think that French will be useful for work, or perhaps German? Lock-down gives you plenty of time to dedicate to learning a new language, brushing up on vocabulary, and testing out pronunciation. 9. DEEP CLEAN YOUR HOUSE Between dusty skirting boards, dirty tiling, and stained carpets, your home can offer days of distraction if you feel like doing that deep clean you’ve been putting off. There are plenty of online cleaning guide if the task looks too big, and focusing on one room at a time will help you divide up the work. 10. RESET YOUR HOME Being stuck at home can make you rethink how much of your stuff you really need. Do you really wear all the clothes spilling out of your wardrobe? And do you think you’ll really re-read those GCSE essays sitting in a box upstairs? You can decide what to donate and what to throw out, ready for a full clear out when the lock-down is lifted. 11. SCARE YOURSELF IN A CREEPY LIBRARY If you’ve always been fascinated by the inspiration for Lovecraft, horror films, and far too many conspiracy theories, you can now read as many as possible books online. 12. STRETCH OUT WITH A YOGA CLASS If you’re trying to DE-stress and stay healthy during lock-down, you’ll be pleased to know that plenty of yoga studios are now streaming online classes for you to join in with. 13. GO TO THE THEATER When you can’t go to the theater, let the theater come to you. Recorded performances are nothing new, but some platforms like Marquee are offering free trials so that you can see whether it’s something you’d want to watch on a more regular basis. 14. HAVE A WORK OUT Keeping active will make a big difference to how you feel during lock-down – physical activity should help you sleep better and lift your mood, even if you’re stuck in the same room for most of the day. You don’t need any equipment for a good workout, and there are plenty of free online videos to take you through a routine. 15. START A BLOG This could be a great time to build your audience, especially if you have relatively cheap, indoor hobbies that you can share. Interest in pastimes like cooking and board games has shot up over recent weeks – if your hobbies are trending, why not set up a blog and share your knowledge? You can set up a WordPress account and blog for free, and take it from there. 16. LEARN FIRST AID It’s good to be prepared for an emergency, especially when urgent care centers are overwhelmed or you may not want to leave self-isolation for a relatively minor injury. You can basic first aid online for free. 17. DISCOVER YOUR ROOTS Wonder where your family was in the flu pandemic of 1918? Tracing your family tree can unearth lost memories or even distant relatives. Start by learning about genealogy online and you can discover more about yourself and your background. 18. UNDERSTAND NUTRITION Comfort eating during lock-down is understandable, but won’t help you enter summer happier and healthier. Understanding nutrition and how food affects your body, health, and mood, will help you make better decisions for your overall well-being and even better use of your current food cupboard. You can also search online for better understanding about nutrition. 19. MEDITATE Meditation and mindfulness doesn’t just help people stay calm – practitioners around the world rely on it to help them focus, remain present, and appreciate what they have. It’s a simple concept that can be hard to master, but you can start now at home, and see if it works for you. 20. PLAN A HOLIDAY If you’re lucky enough to have a job that lets you work from home for this time, you’ve probably saved money on your commute and buying lunch each day. Why not calculate how much you’ve saved through the lock down and put it towards a holiday? You can plan an excursion at home, catching up on all the things you’ve missed, or go further afield to experience something new. 21. HAVE A KITCHEN DANCE PARTY You can definitely have too much screen time. If workouts aren’t your thing or you just miss a good dance, put together a list of your favorite songs and dance around your kitchen. Don’t worry, nobody’s watching! 22. SEW A TEDDY BEAR Recreate a favorite childhood toy or just up cycle some old clothing by sewing your own teddy bear. As long as you have some fabric that you can use (perhaps some socks or an old t-shirt) and a small sewing kit, you can get started. 23. PRAY The last but not the least, always pray to God. Built With word

https://devpost.com/software/coval-2za3si

Going Back To Business COVAL is a community of businesses and customers that keeps each other safe by keeping the regulations together The Unmet Need Due to the Covid 19 pandemic, people across the globe are staying at home in quarantine, causing economic loss and social disruption. Naturally, this reality is not endurable in the long term. In the near future governmental restriction will gradually decrease, while the amount of infected people will increase. Therefore, keeping track of potentially infected individuals who are obligated in quarantine is of great importance. Navigating between the need for proper economical and cultural life under democratic doctrines, while maintaining discipline, regulations and sense of security among the people is one of the greatest challenges our society will face. Therefore, there’s a great need for a technological solution that will allow citizens and business owners to go back to normal routine in a responsible and controlled manner. In our perspective, this technological solution should include two components: Regulation infrastructure ensuring the enforcement of quarantine warrants, mainly keeping infected and potentially infected out of crowded places. Efficient epidemiologic research tool. This tool should allow a very accurate identification of people who were in the same places (supermarkets, restaurants, bars, etc) and at the same time as the confirmed covid-19 carriers, and alarm them. Our Vision In order to face this great challenge, a collective responsibility and discipline among the people must be formed. Our vision is to move democratic countries from a governmental based enforcement system, to a social based enforcement system. We believe that this approach will prove as a stronger tool than the orthodox governmental methodologies both in effectiveness and endurance, while preserving the citizens’ privacy. COVAL COVAL creates a controlled businesses’ entry mechanism. COVAL prevents covid-19 carriers / people who are obligated in quarantine from entering businesses using the platform. Furthermore, in the case that one of the users gets infected, COVAL updates immediately all the users who were in the same places at the same time with him in an anonymous manner. Businesses choosing to be part of the COVAL community gain an efficient and simple enforcement mechanism which assures them that all their customers are feeling good and are not obligated in quarentune warrant or are infected, while maintaining minimal friction. The only way to enter a business that is part of the COVAL community is by using the COVAL app. The process of verifying the people entering the business is done by a doorman that verifies each customer through the COVAL app by picture and ID number. Customers choosing to be part of the COVAL community gain the ability to enter places that are protected by the platform. The user will be able to see all the businesses working with the platform on a map relative to his position. The user can choose a business by clicking it on the map or by directly searching it on the search bar, much like google maps. When selecting a desired business, the user will see all the measures the desired business is using in order to keep customers safe as possible, as seen in the illustration. When arriving at the destination the user will be able to issue an entrance request, in order to enter the business, which in time the host\guard will have to approve. In addition the user will be asked to sign a declaration of good health and integrity, each time when entering a property. The registration to COVAL is done by scanning driver license/ID like in other apps. Everytime that the user opens the app, the app verifies that the user is not obligated in quarantine by connecting to a designated API of the local Ministry of Health. In case the user is obligated in quarantine by law at that moment, the app is locked and an explanation is shown on the screen. A log containing the times and places that the user has entered in the last 14 days is saved locally on the device. In the case that the user gets infected, his log will be transferred anonymously to all the users of the platform, so that each user will compare locally between his log and the anonymous log of the new covid-19 carrier - the comparison result will not be transferred to anyone. Then all users who have crossed paths with the new carrier will get an alarm, and a recommendation to report to the MoH. This way COVAL protects the businesses and the customers while preserving the customers’ privacy. COVAL is a creative, practical and long term endurable solution to get back to normal life and restore the economies of the world. Incentives Customers: reduce significantly the chance of getting infected in public spaces, maintaining a basic lifestyle, receiving a reliable indication in the case they should enter quarantine. Businesses: attracting customers by providing a “covid-19 free” environment, reduces the chance of having a covid-19 carrier in their business that could cause damage to their reputation and even a temporary shutdown in some cases. Base assumptions Large Scale - Assimilating the product among businesses and customers at deployment will be a great challenge. With the right marketing and cooperation we can incentivize businesses towards using the app. Ministry of Health API - our product is based on the existence of an API provided by the local MoH, that allows users to check their current status - obligated in quarantine / not obligated in quarantine. About us Ori Gil-ad: Bsc in electrical engineering and physics from the Technion. Currently a graduate student in electrical engineering at TAU. Shay Shimonov: Bsc in electrical engineering and physics. Currently completing a Msc in electrical engineering at the Technion. Harel Mendelman: Currently undergraduate student in the electrical engineering faculty of the Technion. Ron Gatenio: Bsc software engineering from the Technion. Roy Schory: Bsc software engineering from the Technion. Built With firebase flutter flutter-(user-app) react Try it out github.com

https://devpost.com/software/research-platform-9fvt73

Covid-19 The project is being developed in cooperation with the Crisis_Managment_Plattform This project is a new type of research and an unprecedented global project that connects scientists, researchers and inventors in a way that has never existed before. The data, which is crucial for research, is compiled internationally and is available to all researchers, scientists and inventors of this platform. However, this is not just an international scientific project, it also includes a sociological project. It is a triple scientific project that has a great future. Ask yourself the question of what progress we can make in all areas of research if, instead of 200 scientists, 50,000 scientists, researchers and inventors research the projects together. With an incredible range of knowledge and ideas Thum bundled on a platform for the benefit of all people. The planning and organizational measures result from the association of international scientists, researchers and inventors. With the help of this platform, they organize virtual meetings to conduct research. Data is analyzed by a team of experts and integrated into the platform, so that everyone on this platform is always up to date with the latest research. Users of this platform also have the opportunity To propose a certain page, for example a research institute, to our team and after an examination by a team and consultation with the operator of the page, this is intrigued, and research institutions can have your page integrated so that all users on the platform see the information on the page The good thing about this platform is that users can organize themselves, plan meetings and exchange information at any time. At the same time, users have the opportunity to publish their discoveries internationally with all users of the platform. Who is actually behind this whole campaign? My name is Michael Rhein, I managed the patent exploitation TIZ-NORD Wilhelmshaven Technical Innovation Center for Research and Patent Exploitation. When the pandemic started, I thought about the options for dealing with this crisis as quickly as possible. So in the beginning I looked for solutions on my own until I noticed that the solution can be found right here. Because of this, I thought about how I could bring as many people as possible together to find a solution together. However, it was clear to me from the beginning that this would only be possible with experts in the fields of science, research and the inventions or medical means of the inventors resulting therefrom and so I developed the project of the research platform. I was aware that this would and will present me with enormous challenges, but I will be able to master these together with everyone. What about the rights? I have long considered how to organize the legal part of this platform. Now I have found a solution for this too. All those who register on this platform simply agree that the rights to the research results made on the research platform, inventions for the benefit of mankind, to all users registered on the platform who are involved in the creation of this invention, solution or the research results are evenly distributed . This is an optimal solution for doing research together. To implement this regulation, users accept the general terms and conditions of the platform, in which all legal points are defined. What does it look like financially? Who finances the whole thing? This platform is not about making the greatest possible profit, rather it is about developing things together that can avoid such a situation as Coovid-19 or at least bring about a quick solution. I try to get political funding from the governments from which the scientists, inventors and researchers come, which are then distributed to the respective research institutes, scientists, researchers and inventors, for this I will put together a finance team. We are all human beings, we all live on this planet, let's develop technologies and opportunities together that we may not even be able to imagine today. This platform, like all of us, lives from constant change and adaptation. Together we all develop this platform, so we become part of it. Built With api audio google-analytics google-translate html5 java javascript php video Try it out forschungsplattform.com forschungsplattform.com

https://devpost.com/software/advertising-services

window.fbAsyncInit = function() { FB.init({ appId : 115745995110194, xfbml : true, version : 'v3.3' }); // Get Embedded Video Player API Instance FB.Event.subscribe('xfbml.ready', function(msg) { if (msg.type === 'video') { // force a resize of the carousel setTimeout( function() { $('[data-slick]').slick("setPosition") }, 2500 ) } }); }; (function (d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = "https://connect.facebook.net/en_US/sdk.js"; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); inspirasi wirausaha muda memberikan pengetahuan tentang kejadian dan inspirasi Built With facebook facebook-ads Try it out m.facebook.com

https://devpost.com/software/covid-analyst

Our User Interface shown on a Laptop Heat Map with Risk Assessment making use of US Census Data Set Our main screen showing the Heat Map, News, and Chatbot Inspiration Specific, region-targeted information surrounding COVID-19 is hard to come by. At best, a search on Google can get you the number of reported cases for your state along with countless news articles with questionable accuracy. We wanted to create an information hub for everything you need to know about COVID-19 in your region. What it does COVID Analyst uses machine learning and spatial data analytics with a combination of reliable data sources and research publications to give you an address-level risk heatmap of COVID-19 in your area. In addition, it scrapes credible news outlets to give you a feed of news in your area and an AI-powered chatbot will answer any questions you may have about COVID-19. Key Features: A risk heat map of your region created using published statistics from WHO and APM Research Lab and data from JHU and the US Census through spatial data analytics and machine learning. A web scraper that provides the user with relevant, credible COVID-19 news in their region. A chat bot that answers questions pertaining to the website and COVID-19 using live data and can conduct a symptom-based screening. What separates us: Our map provides information on an address-by-address level. We were the first ones to receive and work with a dataset including race/gender/age information for the US from AMP Research Lab (American Public Media Lab). How I built it Using socio-economic information from Census Tracts (data such as poverty rate, education, race-ethnicity, population pyramid, proximity to health care, and old age, we produced heatmaps to find communities that are at higher risk for COVID-19. Data is extracted and stored in a spatial data model, and we use machine learning to evaluate the risk factor based on published statistics as weights. Our web app is fully integrated with Google Cloud, running on App Engine, and using Places API and Dialogflow for the chat AI. We used React.js/Node.js for our web stack and conducted scraping with Node.js using Puppeteer. Challenges I ran into We were faced with hardware limitations (it took much more time than expected to process the data), so our app is currently limited to Wake County, North Carolina. What's next for COVID Analyst We started this as a sample for Wake County North Carolina (population about 1.1 million) but this work can be easily scaled to the entire US with the appropriate resources and time. We can also create a native mobile application along with the web app. Built With dialogflow google-cloud node.js places-api puppeteer react Try it out github.com covidanalyst.tech

https://devpost.com/software/balancever-your-balanced-daily-routine

Brand Our mission Problem Research Research Personas The solution Why? Platform Technology Team Inspiration For many weeks several million people are in home office to slow down the spreading of COVID-19 and avoid our medical system to collapse. COVID-19 is not only a question about life and death, it’s also about the functioning of our economy and our mental and social well-being. By moving our workplace from the offices to our homes, the boundary between work and life vanished. This can lead to long and lonely working hours and imbalanced life styles. We had to stop hobbies and social interactions, throwing us into a new life situation. Many people struggle to structure their day and stay motivated. By the end of the day we feel mentally drained, physically exhausted and socially isolated. What it does We created a platform that can help structuring a work day effectively, provide suggestions what to do during breaks and free time and display a work-life balance score. With Balancever you can generate a structure for your day, boost your efficiency and avoid long working hours.You can select diverse activities for your break and free time. Every users can also suggets ideas and share with their collegues and friends. Find your online Yoga class, connect with friends for a coffee or browse through fun events. Balancever is a one-stop shop that helps you to shape your new remote lifestyle. Stay home, stay healthy, stay energized, stay connected, stay balanced. How I built it Design Thinking, Adobe XD, Adobe Illustrator, Adobe Premiere, Adobe Photoshop, Dreamweaver, Android Studio, Flutter, Firebase and Github Challenges I ran into Creating a solution for people that works in remote mode. The solution’s impact to the crisis is creating more connections where there is social distance, the product helps against the stress at home, help the economic system Accomplishments that I'm proud of Creation of a platform customized for desktop and mobile, with a engaging user experience. Integration of apps needed for wellbeing and events/activities. What I learned To transform remote working in smart working, you need to think about human well-being. What's next for Balancever After build it we have to populate it, create the content, be in contact with the online content creators (and we help the economic system at the end) and provide a product that can be improved by every stakeholders. Live video share events for peer to peer connect, sleep monitoring. The value of our solution after the crisis It's a product that you can always use, because help you to be in balance, working at home, working in the office. It's helpful for companies that will have employee more relaxed, more productive and in balance, for every workers, for everyone. GitHub Repository https://github.com/balancever Prototype https://xd.adobe.com/view/d0df8f06-659f-44ab-9e45-f67787fd553a-858c/?fullscreen Mobile Platform User Experience Link to see the first user experience: https://youtu.be/-pULEcAUI2k Follow us https://balancever.eu Built With adobe-creative-suite adobe-illustrator adobexd amazon-web-services android android-studio design-thinking firebase photoshop react Try it out xd.adobe.com

https://devpost.com/software/eleutherios-alpha

Linear supply chain that scales or aggregates the service or supply chain Circular supply chain that scales or aggregates the request or conversation Aggregating, scaling or serializing a circular supply chain or process using a computer or Turing machine. Eleutherios Eleutherios ( https://eleutherios.org.nz ) is a platform that makes it easier for people or businesses to cooperate with one another or serve their customer's through a common forum or request. Problem The current human supply chain is linear or tries to scale the service or work that people or businesses are performing. For example, if a person was hungry and had $10 to buy food, they might order online and spend $5 on a pizza, $2 on a drink and $3 to have the items delivered to their house. In this scenario the person can only scale their request or conversation for food, three times. Once for pizza, a second time for a drink and a third time for a delivery service. The problem is the financial supply chain is forcing the food and logistic supply chain into a linear or one-to-one relationship with the service and the request. request = $5 (finance supply chain) for pizza (food supply chain) request = $2 (finance supply chain) for drink (food supply chain) request = $3 (finance supply chain) for delivery (logistic supply chain) Solution Serialize or circularize the supply chain by scaling the customer's forum, request or conversation that they are having with people or businesses, not the service or work that they are trying to perform. For example, if a person was hungry and isolated at home, they could register with Eleutherios and create a forum for some food. A food store owner could register as a service in the system and subscribe to the forum and ask the person what food they wanted? The food store owner could gather the food from their store and scale the forum by creating a sub-forum for a healthcare worker to help with the delivery of the food. The healthcare worker could scale the sub-forum again and create another sub-forum for a delivery service and accompany the delivery service and be the person that delivers the food to the isolated person. In this example, it is the forum or request that is being scaled, not the service or work that people or businesses are performing. By delegating the forum or request to services in this way, means that more than one service or supply chain (i.e. civilian, food, healthcare and logistics) can participate in the forum or request at the same time. Features: Forum in forum (sustainability/manageability). Tags for filtering forums or services (searchable). Alerts to keep users informed when new forums or services are created in the system (notifiable). Blocking to prevent unwanted services or users from serving in forums they have been asked not to serve in or for requesting services, they have been asked not to request (accountability). Service reviews (accountability). B2B or shared processing (scalability). AI (automatable). Eleutherios is built with an HTML/javascript (Angular) frontend and node.js (nosql/firebase) backend. https://eleutherios.org.nz Discuss or provide feedback. https://www.facebook.com/groups/2982366048442234/ Help fix bugs or resolve issues. https://github.com/aletheon/eleutherios-alpha/issues Make a donation to the Eleutherios open source project. https://opencollective.com/eleutherios Built With circular css html javascript supply-chain typescript Try it out eleutherios.org.nz github.com

https://devpost.com/software/medical-facility-tracking

Register Hospital Page Update Information Modal Home Page Inspiration- As we know the Corona virus outbreak is the biggest global issue right now. Currently COVID patients can only go to government hospitals for checkup, and private facilities are not allowed to consult such cases. However, it is only a matter of time before the public infrastructure gets overwhelmed and the government will need to work with various private hospitals for treatment of COVID patients. In that situation, government and people will need transparent information of the private medical facilities and infrastructure. What it Does- The web application provides a platform where hospitals and other health facilities which can provide treatment during COVID-19 or any other probable pandemic can register themselves. The hospitals will update the platform with information such as availability if beds, ICU beds and doctors. All this information will help the government monitor the condition of healthcare infrastructure of the country. The application will also display the nearest facilities that are currently providing treatment, hence potential patients seeking treatment can use this application to get to the right place at the right time. How I built It- The tech stack includes: Python, Flask framework, MongoDB, HTML, CSS, Javascript and jQuery. Challenges- I typically prefer LAMP stack for my projects. But for this, I decided to learn a new development stack that is, Python, Flask and Mongo. Learning a new stack and creating a project with it was challenging and fun at the same time. What I Learnt- I am proud that finally I learnt a new development stack that too in just a single day. I also learnt about how the healthcare industry operates and how availability of transparent information can help prevent outbreaks like this in future. Whats Next- If anonymous medical details of patients were available to all, COVID outbreak could've been anticipated a long time ago and the situation would not have become this big. Medical Facility Tracking application intends to store patient's medical history anonymously on public Blockchain. This will be like an unified platform used all over the world. Built With css flask html javascript jquery mongodb python Try it out github.com

https://devpost.com/software/fanspeage

window.fbAsyncInit = function() { FB.init({ appId : 115745995110194, xfbml : true, version : 'v3.3' }); // Get Embedded Video Player API Instance FB.Event.subscribe('xfbml.ready', function(msg) { if (msg.type === 'video') { // force a resize of the carousel setTimeout( function() { $('[data-slick]').slick("setPosition") }, 2500 ) } }); }; (function (d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = "https://connect.facebook.net/en_US/sdk.js"; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); There is nothing impossible Inspiration I see a lot of people don't understand using pages What it does So everyone knows what the page from the yard is How I built it Memberikan kelas pembelajaran tentang cara menggunakan dan fungsi halaman Challenges I ran into Lots of people who don't want to listen no matter they don't know how important a page is Accomplishments that I'm proud of Patience and trust that person is an achievement that I am proud of whether or not the success is important that we have tried What I learned I learned a lot where a page that can make a business grow in the market. Patient learning invites people to join must be trusted with trust What's next for Fanspeage Development, I want fanspeage to develop rapidly even though I know it takes time for that Built With libaries Try it out www.facebook.com

https://devpost.com/software/covaid-19

Splashscreen Covid_19 The problem is people's fear of corona disease, so a questionnaire has been done to find out whether the condition is sound or suspicious, and upon confirmation, an addiction panel appears to know the affected areas after their location is known through the map Built With dart firebase flutter kotlin objective-c Try it out github.com

https://devpost.com/software/beating-covid-19

super hearo's of today GIF Inspiration all the doctors and nurses that is super hero's who risk there life every day What it does How I built it one step at a time Challenges I ran into every day i deal with people from the tyson and other places that has tested positive Accomplishments that I'm proud of i have beaten the virus several times since april What I learned don't believe everything you hear on social media and the news What's next for beating covid-19 staying healthy Built With english

https://devpost.com/software/peeker-subr6c

Peeker Module with Rechargeable Battery Case Front and Back View Our Seekr Team has grown! The problem our project solves: My grandfather is visually impaired and depends on others to do everyday tasks. Given that he is reliant on touch, we are worried that he will be susceptible to COVID-19. This has led him to struggle with self-isolation because of having no companionship, also making him more prone to emotional distress during this period of self-isolation. This is the reality of 200 million people who are visually impaired around 188 countries. And research shows that the number is expected to triple within the next 4 decades. As social and emotional well-being is of the utmost importance for these marginalized people, the Peeker aims to provide life-long companionship and alleviate emotional distress. The solution we bring to the table: The Seekr is a personalized, interactive voice-assistive device with a bone-conducting earpiece. To use the Seekr, the user does not require any technical knowledge and can interact freely and independently. The user interface is designed in such a way to imitate the human interaction of able-bodied people. The bone-conducting earpiece does not block their natural senses and the rotating clip allows for convenient placement of the device There are two main features of the Peeker 1) Inbuilt thermal imaging sensors which alerts the visual impaired of other people with high body temperatures around them 2) Text and Object detection through which the Peeker will alleviate loneliness and allow the experience of live companionship during this period of self-quarantine. What we have done during the Hackathon: We have developed a working prototype of the Peeker with standard features such as object and text detection within the course of the hackathon. The working prototype also receives speech input from the user and responds using voice output, making it a complete interactive device. In addition, we have developed the 3D design of our proposed final product, keeping minimalistic design, user experience, and fashion in mind. To ensure that our features meet the needs of the visually impaired, we met some visually impaired workers in the front-line such as those working at restaurants, convenience stores, and NGOs to test our prototype and discuss which features would be most useful to them even after the COVID-19 pandemic. We have also conducted thorough market research to analyze our competitors and have realized that there is no product like the Seekr especially with its adaptable and customized features. According to research, there are many other devices within the assistive device market, however, 39.9% of differently-abled people do not like to wear such devices as it usually is very bulky and medical equipment like or is blocking some of their senses. Hence, our device offers quality services without blocking any of their natural senses. The solution’s impact on the crisis: Our solution is simple. The Peeker protects the visually impaired from people with high body temperatures who might be susceptible to COVID-19. This is to encourage social distancing and reduce the chances of getting COVID-19. Furthermore, the Seekr’s objective is to reduce reliance on touch so that the visually impaired are not in contact with the surfaces unnecessarily through its features. Finally, the interactive component of the device engaged the visually impaired to alleviate emotional distress by offering companionship and living independently. For instance, the Peeker allows the visually impaired to conduct activities such as reading a book, distinguishing between different objects, reading road signs, etc. which they otherwise could not do without a helping hand. The necessities to continue the project: Currently, our prototype is deployed on the Raspberry Pi. Going forward, we would like to design the integrated circuit of the final product ourselves, so the device is more compact and durable. In addition, our product will also have a silicone cover which is easily identified by the visually impaired. Our current solution is trained on the COCO-object detection dataset, restricting the number of total objects detected to 80. Going forward, we want to train the model with our dataset focusing on the common items that the visually-impaired person uses on a daily basis. Subsequently, we will partner up with manufacturing companies to mass-produce the Seekr. We are also looking to collaborate with NGOs, Governmental Organisations, Optometrists, and Eye Hospitals to develop more user-friendly features so that every Seekr is customized to the needs of the individual. The value of our solution after the crisis: The Seekr allows independence with ease to the visually impaired through Peeker. For example, they would be able to go grocery shopping with the help of text detection. They would be able to navigate where things are with the help of object detection. Other added features within the premium package such as different languages, haptic feedback accessories, heart rate, and blood pressure monitor, face recognition, and color detection ensures that the Peeker is a life-long companion that accommodates the visually impaired no matter which demographic they are from. Built With coco opencv pytesseract python pyttsx3 raspberry-pi speech-recognition yolo

https://devpost.com/software/spark-k6txdh

Inspiration - Needed a place to track and plan our projects. - Frustrated over apps that are specialized to do only one thing resulting in having to keep many tabs/apps open at the same time. - Saw a need for an all-in-one productivity app. - Believed it had the potential to increase the productivity of those affected by COVID-19. What it does - Features: Calendar, Tasks, Team Administration, Project Tracking, Messages, Meetings and Zoom Integration, Discussion Board - A cumulative productivity app that puts all the apps you need into one - Assists teams and organizations by improving productivity and tracking the progress of projects - Highlights team collaboration with SparkRooms to coordinate team members How we built it - Written in HTML/CSS/JS, Python - Written in Visual Studio Code - Utilized Travis for continuous deployment and autonomous configuration - Divide and Conquer - Frontend, Backend - Git, VSCode Live Share, and Discord Challenges we ran into - Responsiveness & Mobile compatibility - Rendering iframes on the dashboard - Saving arbitrary user data within Firestore - Git collisions: Committing changes to the same lines at the same time Accomplishments that we're proud of - Firebase for hosting, database, and authentication - Fully functional login system with Google Oauth 2.0 Authentication - Dashboard to render iframes to show lots of content in a single page - Travis CI/CD - Lots of backend and Javascript to process website What's next for Spark - Expand Spark for function enterprise and educational usage - Increase responsiveness of site to enable mobile usage - Create a way to send personal messages to team members - Create more tools for users eg. a personal File Storage Method Built With bootstrap css3 flask fullcalendar google-cloud html5 javascript jquery node.js python travis-ci Try it out sparkapp.cf github.com docs.google.com

https://devpost.com/software/findthecluster

High-level overview Analysis from actual data. Architecture (previously called "FindTheCluster") Inspiration Getting tested for COVID-19 can be challenging due to the limited availability of testing kits and overwhelming patient load on healthcare systems. Many individuals may only be mildly symptomatic, or asymptomatic - but they are often overlooked and deprioritized to undergo testing. What it does CheckIfCovid is a self-reporting survey for symptoms which calculates the probability of a COVID-19 infection based on the participant’s input. It works by training the data collected from other participants' responses and the data from confirmed COVID-19 cases to calculate the likelihood that the reported symptoms are associated with COVID-19. Features Instant assessment - Immediately know the probability that you have COVID-19 based on self-reported symptoms Geolocated symptoms - Plot out all symptoms in a map and identify clusters. Have you ever wondered if all occupants within the building you live in are also experiencing persistent cough? Privacy secured - No personally identifiable information will be stored. Third-party Integration - integrate with existing health systems through our API . If you own a product, we encourage to integrate (and anonymize) your data. How do we collect data Survey - Self-reported symptoms Scrapers - We get data of confirmed COVID-19 cases from CSSEGIS, ECDC, GISAID, KAGGLE. Benefits Provide data to the government to run more targeted testing on identified clusters. More information dissemination or resources can be deployed to the identified clusters. Provides awareness to occupants of the identified clusters. Predict the probable locations of the next outbreaks. Teams We are currently organized into 3 teams and have a corresponding team page: Survey App ( https://github.com/orgs/findthecluster/teams/survey-app ) API App ( https://github.com/orgs/findthecluster/teams/api-app ) Data Science ( https://github.com/orgs/findthecluster/teams/data-science ) Slack room: https://app.slack.com/client/T0103C6KMKM/C010RKNQ5QC Related solutions We found out there are similar solutions to our Survey app: https://covidnearyou.org/#!/ https://covid.joinzoe.com/ https://www.apple.com/covid19/ https://github.com/ch-covid-19/welcome https://fevermap.net/ https://flatten.ca/#home https://howwefeel.org/ What we want to achieve is a call to unify these data in a single location, standardize it, and apply machine learning. We will open the API and data to institutions that need them. Challenges Lack of dataset that had cases who reported symptoms and then tested negative. We mainly used unsupervised learning to determine whether the given symptoms of a case and it's proximity to one of the identified clusters will likely test positive Built With next node.js python react typescript Try it out github.com checkifcovid.com

https://devpost.com/software/covid-feel-good

The "Secret Garden" VR experience CNBC coverage of our work (25 April 2020) The home page of the web site The protocol page in the web site The logo of the project ## Inspiration Living in the time of the coronavirus means experiencing not only a global health emergency but also extreme psychological stress that puts a strain on our identity and our relationships. The coronavirus and the associated quarantine forces us to manage three different psychological dilemmas simultaneously : the stress of the disease, the disappearance of places, and the crisis of the sense of community. In fact, the coronavirus pandemic is having a significant effect on people’s mental health that requires urgent support . On one side, is currently difficult to find to any form of psychological support . The social isolation of the quarantine and the economic downturn are limiting the possiblity of accessing to mental health specialist with the risk of a rise in conditions like anxiety, depression and addictions. On the other side, one of the paradoxes of coronavirus is that despite being a problem, it can also be a unique opportunity . In fact, willingly or unwillingly, it forces us to change and manage new situations such as quarantine, close coexistence with children and spouse, lack of relationships, and so on. This process of change can be dramatically boosted by transformative experiences , forcing individuals to critically examine and eventually revise their core assumptions and beliefs. Unfortunately, most transformative experiences cannot be planned in advance, but happen suddenly in individuals’ lives, without a prior control on their contents and their effects. ## What it does This protocol uses the power of virtual reality to provide a transformative experience that can help individuals in two ways: By providing a digital place in which subjects can relax and reflect; By facilitating a process of critical examination and eventually revision of core assumptions and beliefs. In particular we used the rules defined for an effective design of Transformative Experiences, to develop the "Secret Garden" VR experience and its weekly protocol you can find in the Covid Feel Good web site . For a long time, the main barrier to a broad use of VR technology was its cost . However, now the simplest and cheapest form of VR comprises nothing but a pair of magnifying lenses and a sheet of cardboard or a plastic box. These headsets sell for 15–30 USD . and use a standard smartphone as a tracker and display to generate the three-dimensional (3D) environment. Mobile-based VR is particularly suited to a specific VR content that can be very useful to address the coronavirus stress: 360-degree videos . 360-Degree videos have the power to virtually transport users, immersing them in the video recording, allowing them to actively explore its content and experience the video from any angle. As recently demonstrated by Li et al. , these videos have the ability to induce specific emotions characterized by different levels of valence and arousal. More, as shown by Robertson and colleagues the neural representations of the part of the 360-degree video presented in VR (the scene within the current field of view) prime the associated representations of the full panoramic environment, facilitating subsequent perceptual judgments. In other words, 360-degree videos generate a dynamic interplay between memory and perception that can be used to improve the features of these cognitive processes and to update their contents. ## How we built it "The Secret Garden" Virtual Reality immersive experience has been developed through an integrated process involving psychologists, 3D artists, musicians, storytellers and designers. This immersive experience storyboard has been: written by wellbeing psychologists ; converted in a VR experience by 3D specialists using the Unreal engine technology (with complex post-production activity related to VR conversion); it has been sounded by musicians and then dubbed by a professional dubber . We used the Augmented Relaxation approach involving deactivating human threat protection system and activating soothing system (see "Emotion Regulation Systems" theory ; finally, the protocol has been designed by a team of clinical and cognitive psychologists . ## Challenges we ran into A significant challenge for any psychological intervention during the quarantine is the ratio between accessibility and efficacy . Our goal was not to provide a full structured psychological intervention, but to build the "surgical mask" of mental health support . Surgical Masks do NOT provide the wearer with a reliable level of protection against coronavirus (20%) versus the 95/99% of FFP2 and FFP3 masks. However, they are very effective in protecting others from the wearer’s respiratory emissions, and their use is significantly better than wearing a scarf. Here, we try to do the same. The goal of this VR protocol is not to solve complex mental health problems, but rather to reduce the burden of the quarantine by relieving anxiety and stress and improving interpersonal relationships. Additionally, by facilitating self-reflectiveness and constructive exchange with relevant others, it improves our ability to adapt to the challenges and take advantage of the opportunities offered by the Coronavirus. ## Accomplishments that we're proud of We have already completed the protocol and the VR experience in English, Italian, Spanish and Catalan . You can test it now in the Covid Feel Good web site . We are now working to produce the experience in other languages and with more contents. ## What we learned Creating easy tools for mental health is not easy . In particular it is difficult to balance the difficulty and the involvement required with the efficacy of the process . In this view, focusing on clear goals and simplifying as much as possible the technology needed improves the efficacy of the system. ## What's next for COVID Feel Good We want to start a multicentric controlled study to verify the efficacy of the presented approach . Our goal is to reach at least 240 subjects in three months. More, at the moment COVID Feel Good is a self-help VR experience. The next step is to add the clinicians in the process, by developing a set of easy VR tools to empower them . Built With unreal-engine Try it out www.covidfeelgood.com

https://devpost.com/software/wecare-5l9dgi

Home Screen of app, which allows you to report your symptoms, check the status of your circle, and get daily personalized tips. Map Screen of app, which allows you to see hotspots around you and your Care Circle. Care Circle screen of app, which allows you to health conditions of your loved ones. Web interface, which can be used to update the symptoms. It is synced with the app. New logo. Update with a key. Hotspots for countries. Options from the start. Questions about your health. Hot spots. App design As the outbreak of COVID-19 continues to spread throughout the entire world, more stringent containment measures from social distancing to city closure are being put into place, greatly stressing people we care about. To address the outbreak, there have been many ad hoc solutions for symptom tracking (e.g., UK app ), contact tracing (e.g., PPEP-PT ), and environmental risk dashboards ( covidmap ). However, these fragmented solutions may lead to false risk communication to citizens, while violating the privacy, adding extra layers of pressure to authorities and public health, and are not effective to follow the conditions of our cared ones. Unless being mandatory, we did not observe the large-scale adoption of these technologies by the crowd. Until now, there is no privacy-preserving platform in the world to 1) let us follow the health conditions of our cared ones, 2) use a statistically rigorous live hotspots mapping to visualize current potential risks around localities based on available and important factors (environment, contacts, and symptoms) so the community can stay safer while resuming their normal life, and 3) collect accurate information for policymakers to better plan their limited resources. Such a unified solution would help many families who are not able to see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. These urgent needs would remain for many months given that the quarantine conditions may be in place for the upcoming months, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and COVID-19 potential reappearance next year at a smaller scale (like seasonal flu). There is still uncertain information about immunity after being infected and recovered from COVID-19. Therefore, it is of paramount importance to address them using an easy-to-use and privacy-preserving solution that helps individuals, governments, and public health authorities. WeCare Solution WeCare is a cross-platform app that enables you to track the health status of your loved ones. Individuals can add their family members and friends to a Care Circle and track their health status and get personalized daily updates on best prevention practices. In particular, individuals can opt-in to fill a simple questionnaire, supervised by our epidemiologist team member, about their symptoms, comorbidities, and demographic information. The app then tracks their location and informs them of potential hotspots for them and for vulnerable populations over a live map, built using opt-in reports of individuals. Moreover, symptoms of individuals will be tracked frequently to enable sending a notification to the Care Circle and health authorities once the conditions get more severe. We have also designed a citizen point, where individuals get badges based on their contributions to solving pandemic by daily checkup, staying healthy, avoiding highly risky zones, protecting vulnerable groups, and sharing their anonymous data. WeCare includes a contact tracing module that follows the guidelines of Decentralized Pan-European Privacy-Preserving Proximity Tracing (PEPP-PT) . It is an international collaboration of top European universities and research institutes to ensure the safety and privacy of individuals. What we have done during the weekend Have been in contact with other channels in Brazil and Chile. We have updated the pitch (extended), app-design and backend connection of the app this week. New contacts with Chile and Singapore. We have also made some translation work with the app. Shared more on social media about the project and also connected to more people on slack and LinkedIn. We have also modified the concept of Care Circle and how to add/remove individuals. Now, the app is very easy-to-use with minimal input (less than a minute per day) from the user. We are proud of the achievements of our team, given the very limited time and all the challenges. Challenges we ran into The Hackathon brought together plenty of people of different expertise and skills. There were challenges that we faced that were very unique, as we faced a variety of communication platforms on top of open-source development tools. Online Slack workspaces and Zoom meetings and webinars presented challenges in forms of inactive team members, cross-communications, and information bombardment in several separate threads and channels in Slack and online meetings of strangers that are coordinated across different time zones. In developing the website and app for user input data, our next challenge was in preserving the privacy of user information. In the development of a live hotspot map, our biggest challenge here was to ensure we do not misrepresent risk and prediction into our live mapping models. Also for the testing of the iOS version, we ran to the new restriction of App Store for COVID-related apps, which should be backed up by some health authorities or governmental entities. The solution’s impact on the crisis We believe that WeCare would help many families who can see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. The ability to check up on their Care Circle and the hotspots around them substantially reduces the stress level and enables a much more effective and safer re-opening of the communities. Also, individuals can have a better understanding of the COVID-19 situation in their local neighbourhood, which is of paramount importance but not available today. The live hotspot map enables many people of at-risk groups to have their daily walk and exercise, which are essential to improve their immunity system, yet sadly almost impossible today in many countries. The concept of Care Circle motivates many people to invite a few others to monitor their symptoms on a daily basis (incentivized also through badges and notifications) and take more effective prevention practices. Thereby, WeCare enables everyone to make important contributions toward addressing the crisis. Moreover, data sharing would enable a better visual mapping model for public assessment, but also better data collection for the public health authorities and policymakers to make more informed decisions. The necessities to continue the project We plan to continue the project and fully develop the app. However, to realize the vision of WeCare we need the followings: Public support: a partnership with authorities and potentially being a part of government services to be able to deploy it on AppStore. It also makes WeCare more legitimate. This would increase the level of reporting and therefore having a better overview and control of the crisis. Social acceptance: though being confirmed using a small customer survey, we need more people to use the WeCare app and share their data, to build a better live risk map. We would also appreciate more fine-grained data from the health authorities, including the number of infected cases in small city zones and municipalities. Resources: So far, we are voluntarily (and happily) paying for the costs of the servers. Given that all the services of the app and website would be free, we may need some support to run the services in the long-run. The value of your solution(s) after the crisis The quarantine conditions and strict isolation policies may still be in place for upcoming months and year, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and possible COVID-19 reappearance next year at a smaller scale (like seasonal flu). Therefore, we believe that WeCare is a sustainable solution and remains very valuable after the current COVID-19 crisis. The URL to the prototype We believe in open science and open-source developments. You can find all the codes and documentation (so far) at our Website . Github repo . Pitch: https://youtu.be/7fMrVqxoPKY Pitch extended version: https://youtu.be/Vo0gs3WlptU Other channels. https://www.facebook.com/wecareteamsweden https://www.instagram.com/wecare_team https://www.linkedin.com/company/42699280 https://youtu.be/_4wAGCkwInw (new app demo 2020-05) Interview: https://www.ingenjoren.se/2020/04/29/de-jobbar-pa-fritiden-med-en-svensk-smittspridnings-app Built With node.js python react vue.js Try it out www.covidmap.se github.com

https://devpost.com/software/helps-to-use-less-examination-of-corona-virus-slices

window.fbAsyncInit = function() { FB.init({ appId : 115745995110194, xfbml : true, version : 'v3.3' }); // Get Embedded Video Player API Instance FB.Event.subscribe('xfbml.ready', function(msg) { if (msg.type === 'video') { // force a resize of the carousel setTimeout( function() { $('[data-slick]').slick("setPosition") }, 2500 ) } }); }; (function (d, s, id) { var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) return; js = d.createElement(s); js.id = id; js.src = "https://connect.facebook.net/en_US/sdk.js"; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); Inspiration What it does I have just idea no more, but I think it helps too much How I built it Challenges I ran into Accomplishments that I'm proud of What I learned What's next for helps to use less Examination of Coronavirus slices helps to use less Examination of Coronavirus slices

https://devpost.com/software/faco-fight-against-corona-jfcza9

GIF Confusion matrix for our final model INSPIRATION A diagnosis of respiratory disease is one of the most common outcomes of visiting a doctor. Respiratory diseases can be caused by inflammation, bacterial infection or viral infection of the respiratory tract. Diseases caused by inflammation include chronic conditions such as asthma, cystic fibrosis, COVID-19, and chronic obstructive pulmonary disease (COPD). Acute conditions, caused by either bacterial or viral infection, can affect either the upper or lower respiratory tract. Upper respiratory tract infections include common colds while lower respiratory tract infections include diseases such as pneumonia. Other infections include influenza, acute bronchitis, and bronchiolitis. Typically, doctors use stethoscopes to listen to the lungs as the first indication of a respiratory problem. The information available from these sounds is compromised as the sound has to first pass through the chest musculature which muffles high-pitched components of respiratory sounds. In contrast, the lungs are directly connected to the atmosphere during respiratory events such as coughs, heart rate. PROBLEM STATEMENT In this difficult time, a lot of people panic if they have signs of any of the symptoms, and they want to visit the doctor. It isn’t necessary for the patients to always visit the doctor, as they might have a normal fever, cold or other condition that does not require immediate medical care. The patient who might not have COVID-19 might contract the disease during his visit to the Corona testing booth, or expose others if they are infected. Most of the diseases related to the respiratory systems can be assessed by the use of a stethoscope, which requires the patient to be physically present with the doctor. Healthcare access is limited—doctors can only see so many people, and people living in rural areas may have to travel to seek care, potentially exposing others and themselves. SOLUTION We provide a point of care diagnostic solutions for tele-health that are easily integrated into existing platforms. We are working on an app to provide instant clinical quality diagnostic tests and management tools directly to consumers and healthcare providers. Our app is based on the premise that cough and breathing sounds carry vital information on the state of the respiratory tract. It is created to diagnose and measure the severity of a wide range of chronic and acute diseases such as corona, pneumonia, asthma, bronchiolitis and chronic obstructive pulmonary disease (COPD) using this insight. These audible sounds, used by our app, contain significantly more information than the sounds picked up by a stethoscope. app approach is automated and removes the need for human interpretation of respiratory sounds, plus user disease can also be detected by measuring heart beat from camera of smartphone. The application works in the following manner: User downloads the application from the app store and registers himself/herself. After creating his/her account, they have to go through a questionnaire describing their symptoms like headache, fever, cough, cold etc. After the questionnaire, the app records the users’ coughing, speaking, breathing and heart rate in form of video from smartphone. After recording, the integrated AI system will analyze the sound recording, heart rate comparing it with a large database of respiratory sounds. If it detects any specific pattern inherent to a particular disease in the recording, it will enable the patient to contact a nearby specialist doctor. The doctor then receives a notification on a counterpart of this app, for doctors. The doctor can view the form, watch the audio recording, and also read the report given by the AI of the application. The doctor, depending upon the report of the AI, will develop a diagnosis, suggest medicines, or recommend a hospital visit if the person shows symptoms of corona or other serious condition. In cases where the AI detects a very seriously ill patient, it will also enable the physician to call an ambulance to the users’ location and continuously track the user. HOW WE ARE GOING TO BUILD IT We will take a machine learning approach to develop highly-accurate algorithms that diagnose disease from cough and respiratory sounds. Machine learning is an artificial intelligence technique that constructs algorithms with the ability to learn from data. In our approach, signatures that characterize the respiratory tract are extracted from cough and breathing sounds. We start by matching signatures in a large database of sound recordings with known clinical diagnoses. Our machine learning tools then find the optimum combination of these signatures to create an accurate diagnostic test or severity measure (this is called classification). Importantly, we believe these signatures are consistent across the population and not specific to an individual so there is no need for a personalized database Following are the steps the app will take: Receive an audio signal from the user's phone microphone Filter the signal so as to improve its quality and remove background noise Run the signal through an artificial neural network which will decide whether it is an usable breathing or cough signal Convert the signal into a frequency-based representation (spectrogram) Run the signal through a conveniently trained artificial neural network that would predict the user's condition and possible illness Store features of the audio signal when the classification indicates a symptom IMPACT FACO will help patients get themselves tested at home, supporting in areas where tests and access to tests are limited. This will help democratize care in hard-to-reach or resource-strapped areas, and provide peace of mind so that patients will not overwhelm already stressed healthcare systems. Doctors will be able to prioritize patients with an urgent need related to their speciality, providing care from the palm of their hand, limiting their exposure and travel time. CHALLENGES WE RAN INTO No financial support Working under quarantine measures Working in different time-zones Scarcity of high-quality data sets to train our models with One Feature Related Problem- Legal shortcomings we might face when adding the tracking patient feature ACCOMPLISHMENTS We went from initial concept to a full working prototype. We got a jumpstart on organizational strategy, revenue and business plans—laying the groundwork for building partnerships with healthcare providers and pharmacies. On the creative side, we built our foundational brand and design system, and created over 40 screens to develop a fully working prototype of our digital experience. Our prototype models nearly the entire app experience—from recording respiratory sounds to reporting to managing contact, care, and prescriptions with physicians. Technologically, we successfully developed an algorithm for disease and have begun the application development process—well on our way to making this a fully functional product within the next 20 days. You can explore the full prototype here or watch the demo (and check out our promo gif )! WHAT WE'VE DONE SO FAR We wanted to show that the project is feasible. Scientific literature has shown that audio data can help diagnose respiratory diseases. We provide some references below. However, it is unclear how reliable such a model would be in real situations. For that reason, we used a publicly available annotated dataset of cough samples: It is a collection of audio files in wav format classified into four different categories. We wrote code in Python that converts those samples into MEL spectrograms. For the time being we are not using the MEL scale, just the spectrograms. We did several kinds of pre-processing of the signals, including data augmentation, then convert all pre-processed signals, along with their categories into a databunch object that can be used for training artificial neural networks created in the fastai library. The signals within the databunch were divided into training and validation sets. Because the dataset size was reduced, we used transfer learning . That is, we used previously trained networks as a starting point, rather than training from scratch. We treated the spectrograms as if it were images and used powerful models pre-trained to classify images from large datasets. In particular, we tried both two variants of resnet and two variants of VGG differing on their depth (number of hidden layers). This approach implied turning the sprectograms into image-like representations and normalizing them according to the statistics of the original dataset our models were trained on (imagenet). We first changed the head of the networks to one that would classify according to our categories and trained only that part of the net, freezing the rest. Later on we unfroze the rest of the net and further trained it. We finally compared the different models by the confusion matrices that we obtained from the validation test. We finally settled on a model based on VGG19 . We exported the model for later use in classifying audio samples through the pre-existing interface of our mobile app. The results are promising, especially considering the small amount of data that we have available at this moment. We have included an image of the final confusion matrix that shows how our current network can correctly classify all four categories of signal about 50% of the time, far better than the random level of 25%. We conclude that wav files obtained trough a phone mic provide information that can be useful for diagnosing respiratory condition. We are confident that we can vastly improve both the sensitivity and the specificity of our model if we can gain access to larger, more representative datasets. We provide an image of the final confusion matrix for our model in the gallery. This is a repository that contains the most important pieces of our work, including some code, the confusion matrix image and the exported final model. SUMMARY We are developing digital healthcare solutions to assist doctors and empower patients to diagnose and manage diseases. We are creating easy to use, affordable, clinically validated and regulatory cleared diagnostic tools that only require a smartphone. Our solutions are designed to be easily integrated into existing tele-health solutions and we are also working on apps to provide respiratory disease diagnosis and management directly to consumers and healthcare providers. Feel free to click on our website for more information. We developed this website using Javascript, HTML, CSS, Figma, and integrated it with Firebase to manage hosting and our database. Thank you for reading, and don't hesitate to reach out if you have any questions! REFERENCES Porter P, Claxton S, Wood J, Peltonen V, Brisbane J, Purdie F, Smith C, Bear N, Abeyratne U, Diagnosis of Chronic Obstructive Pulmonary Disease (COPD) Exacerbations Using a Smartphone-Based, Cough Centred Algorithm, ERS 2019, October 1, 2019. Porter P, Abeyratne U, Swarnkar V, Tan J, Ng T, Brisbane JM, Speldewinde D, Choveaux J, Sharan R, Kosasih K and Della, P, A prospective multicentre study testing the diagnostic accuracy of an automated cough sound centered analytic system for the identification of common respiratory disorders in children, Respiratory Research 20(81), 2019 Moschovis PP, Sampayo EM, Porter P, Abeyratne U, Doros G, Swarnkar V, Sharan R, Carl JC, A Cough Analysis Smartphone Application for Diagnosis of Acute Respiratory Illnesses in Children, ATS 2019, May 19, 2019. Sharan RV, Abeyratne UR, Swarnkar VR, Porter P, Automatic croup diagnosis using cough sound recognition, IEEE Transactions on Biomedical Engineering 66(2), 2019. Kosasih K, Abeyratne UR, Exhaustive mathematical analysis of simple clinical measurements for childhood pneumonia diagnosis, World Journal of Pediatrics 13(5), 2017. Kosasih K, Abeyratne UR, Swarnkar V, Triasih R, Wavelet augmented cough analysis for rapid childhood pneumonia diagnosis, IEEE Transactions on Biomedical Engineering 62(4), 2015. Amrulloh YA, Abeyratne UR, Swarnkar V, Triasih R, Setyati A, Automatic cough segmentation from non-contact sound recordings in pediatric wards, Biomedical Signal Processing and Control 21, 2015. Swarnkar V, Abeyratne UR, Chang AB, Amrulloh YA, Setyati A, Triasih R, Automatic identification of wet and dry cough in pediatric patients with respiratory diseases, Annals Biomedical Engineering 41(5), 2013. Abeyratne UR, Swarnkar V, Setyati A, Triasih R, Cough sound analysis can rapidly diagnose childhood pneumonia, Annals Biomedical Engineering 41(11), 2013. FACO APP VIDEO DEMO LINK FACO PRESENTATION LINK FACO 1st Pilot Web App LINK Built With android-studio doubango fastai firebase google-cloud google-maps java machine-learning mysql numpy pandas python pytorch sklearn sound-monitoring-and-matching-api spyder webrtc Try it out github.com

https://devpost.com/software/smart-ventilators-pq2nwa

Side View Of the final Ventilator Attachment assembly in FUSION 360 Side View Of the final Ventilator Attachment assembly in FUSION 360 Top View Of the final Ventilator Attachment assembly in FUSION 360 Isometric View Of the final Ventilator Attachment assembly in FUSION 360 Isometric view Of the final Ventilator Attachment assembly in FUSION 360 Back View Of the final Ventilator Attachment assembly in FUSION 360 this is the actual 4T arrangement sitting inside the model Valve with inlet and outlet pipe Inspiration As we know the world needs a helping hand in this difficult time period and ventilator shortage is a really big issue across globe. I come from India where we have only 20,000 ventilators for 1.3 billion population which is almost 1 ventilator for every 65,000 people. This condition inspired me to do something for the humanity, since i am doing mechanical engineering I targeted mechanical ventilators and tried to increase its efficiency to the fullest What it does I have made and special attachment which can be attached to any ventilator. this attachment is nothing just a simple 4T pipe splitting into 4 at the end which can be attached to the outlet of ventilator to use a single ventilator for multiple patient. Now the hack is that I have attached an unidirectional flow control valve at the ends of these junction this allows us to control pressure in each pipe an also stops cross contamination which enables it to be used in any situation irrespective of the type of patient we have Also all these flow control valves are connected to micro controller which is further connected to an APP which enables a single doctor to regulate many ventilators and much more patients just through a tap of a button in the app How I built it I used Autodesk Fusion 360 to design the 4T pipe and the flow control valve and used the same software for the assembly of the same (4T pipe and unidirectional flow control vale ) Further I have Made and entire assembly which exactly reflects how the real world attachment will look like I did flow simulations on ANSYS and used ANSYS Fluent tool for taking out computational fluid dynamics of the flow and taking out different pressures and calibrations to achieve a viable scale for the APP IOT part is done on Arduino micro controller and IOT modules like Node MCU etc for the control of these valve Making an APP for this setup so that the doctor can control all of them through an APP Challenges I ran into TO find appropriate pressure stats for an ventilator and developing perfect calculations for the pressure calculations Since I am a mechanical engineer so i don't have much knowledge of these IOT although i have made a simple IOT model in Proteus but i wasn't able to make a very good code for the same The biggest challenge with which i am still struggling is to build the APP due to no knowledge of the APP i am searching for someone who can help me in coding aspects of IOT and building APP part for the project What I learned A lot more about fluid dynamics, building equations and getting results out of iy. Tackling new challenges like methods of stopping cross contamination without any additional part . Generating an ideas so that it can meet every aspect like cost, application, etc What's next for Smart Ventilators Trying to build a really good APP for it and refining codes for IOT part so as to make the system more and more effective and easy to use Built With autodesk-fusion-360 cfd iot

https://devpost.com/software/zero-contact-uav-bot

Ardu Pilot Software AA Interactive Form to collect Input UAV Weather Forecast For Pre-Flight Checks Mission Planner UAV / Drone Taking off Access Database for Logging Sky Vector for logging Aeronautical chart Code snippet in step level (MainTask) Code snippet (Sub Task Module) for Input Inspiration The Novel Corona-virus has affected humanity in various ways, be it our economy, our freedom of movement, and the loss of loved ones. Something that struck me was elderly people having to wait in a queue for medicines at an outlet. Even though there are home delivery services, the risk of infection is extremely high as this job requires you to move around places at a higher rate and I recollected news of people infected by pizza delivery agents / Swiggy agents throughout India on multiple occasions. The Lockdown definitely has slowed down the infection rates but we are forgetting that all essential services are not contactless. That's when I decided to create a solution to this by using a Drone / UAV to Deliver essentials and medicines primarily for the vulnerable among us so that we ensure they are safe, Drones are usually manually remote-controlled by a pilot. Me myself being an aerospace engineer with focus on Avionics and with Automation Anywhere. I decided to use an AutoPilot Mission Planner to write coded commands to the Flight controller in order to make the Flight Autonomous and deliver the essential package and return home. From the News Bengaluru on superspreader alert after delivery boy tests positive - Click here to read 83-year-old man collapses while waiting in New World queue in New Lynn - Click here to read Features in a nutshell Interactive User input Database Logging Autonomous UAV Flight Automated Pre Flight Checks Address to Geo Coordinates conversion Distance, Payload release altitude Calculation AutoPilot Command creation (Flight Plan) Payload Delivery (Essential package Delivery) Scalability What it does The Bot collects the delivery address and input data using Interactive forms and converts the address string into location coordinates using Geocoding API and uses Python Script to calculate the Flight Distance using Haversine Formula based on the range of the UAV and Performs Pre-Flight Checks such as Wind speed, Temperature, Precipitation Probability, Cloud Cover, Visibility and more. It also checks for any nearby airport and logs the Aeronautical charts for the way-points using Sky Vector web service. It then Sends Flight information to the DGCA for Flying permission via API. It then calculates the payload release altitude based on logic using the Indian regulatory guidelines for construction. Finally, the bot compiles this information to create a flight plan command and uses the Mission Planner which is Ground Control Software to write the code into the Flight controller AutoPilot using a wireless transmitter and launches the UAV on its mission. While doing this each flight is tracked by a unique flight control number and logged to a database for future audit and compliance purposes and folder is created with Logs, charts, and autopilot code. Hence this Bot enables users to completely automate the Pre-Flight processes and automate the creation of code for Autonomous UAV Flight which will Deliver the payload (Essential Package) at the desired location and return back home and complete the mission. This makes the complete process contactless and safe. Hence serving the essential needs of the most vulnerable and reducing the infection rate. How I built it This RPA Solution is Built on Automation Anywhere A2019 and integrates with various technology as mentioned below, which is the real beauty of RPA. Microsoft Bing Geocoding API Python 3.8.3 Ardu Pilot Mission Planner ( with wireless transmitter ) Interactive Forms UAV Forecast Service Sky Vector Chart Service DGCA API Microsoft Access Database UAV / Drone & Payload release mechanism Challenges I ran into One of the challenges was to use complex mathematical formulae using Python to derive certain parameters. However, the Python Package on A2019 made it really easy to call Python functions inside and code and get the output. Also creating a waypoint plan for the Autopilot was initially a challenge however using the product documentation I was able to create the flight plans using Log to file package making all the values dynamic. Accomplishments that I'm proud of I am happy that I was able to use my academic knowledge in Aerospace, my work expertise in Robotic Process Automation, and my curiosity to explore new possibilities in creating this solution which can help the world in this traumatic situation. I am also happy that I was able to bring out the true sense of Anywhere in the name "Automation Anywhere". What I learned It was indeed a great experience to develop this bot with a lot of research, trial & error and new learnings. I was able to start off with Python and I'm looking forward to trying out further possibilities. What's next for Zero Contact UAV Bot The RPA solution can be scaled up for usage with Queue (WLM) and to further improvise and add on more features. To make the solution more independent we can have a "Raspberry Pi" attached to the drone and connected to the Flight controller and the Internet. We can install AA Bot agent on the Raspberry Pi running windows and we can remotely deploy the automation considering the Drone as a bot runner with wings ;). This drone will be a fully automated solution for an Autonomous Flight using Robotic Process Automation as the base Technolgy. Other areas of usage Delivery Services Search and Rescue Facilities Climbers and Firefighters Mine and Oil Industry Military and Gaurd Services Disaster Relief Services Built With api ardupilot automationanywhere autonomousuav flightcontroller geocodingapi missionplanner payloadreleasemechanism python skyvector uavforcast Try it out github.com

https://devpost.com/software/khousto-entergy-com-liheap-outreach-bot

I work for a public utility that services Louisiana, Mississippi, Texas, and Arkansas. As of 2016, 37% of our customers experienced an energy burden above the national threshold. The federal government has a program, Low Income Home Energy Assistance Program, or “LIHEAP” that assists low-income households, particularly those with disproportionately high energy costs, to cover their home energy costs by making payments directly to the customers’ utility provider. Customers can receive LIHEAP assistance by contacting agencies across the state and applying for a LIHEAP grant. Historically, the agencies have not had the adequate marketing resources to notify the communities they serve that assistance may be available to them. We have tried manual outreach campaigns in the past, but they are costly and time-consuming with a limited subset of customers able to be contacted. With the onset of COVID-19, some of the hardest hit financially have been our low-income customers. The pandemic created a more pressing need to get LIHEAP information to low-income customers who may need more assistance than ever in paying their electric bill. Additionally, with the passing of the CARES Act, an additional $900 million was given to LIHEAP so there are now more funds than ever for our customers to receive. We created a bot to assist with the customer outreach informing them of the LIHEAP program and instructing how to apply for a LIHEAP grant. First the LIHEAP bot pulls all customer data on a weekly basis. This consists of demographic information along with any past due bill amount. The bot then compares the customer information with credit information to find those whose annual household income is $35,000 or less. Using both sets of data, the bot will create a subset containing only those whose annual household income is $35,000 or less and who have a past due bill of greater than $125. Using this subset of customer data, the bot then does a geographic comparison by zip code to find the closest LIHEAP agency by customer. The LIHEAP bot then contacts the customers via email and auto-dialer letting them know they may be eligible to receive a LIHEAP grant, provides them with the contact information (address, phone number, email, and website) for the closes LIHEAP agency, and in the email outreach includes an infographic of a guide to applying for a LIHEAP grant. The bot runs every week in production and currently contacts about 75,000 customers each week. From the first week’s running, we found that of the customers who went through the process and received a LIHEAP grant, the average grant was almost $500. At scale, we estimate that we should see over $1 million in LIHEAP grants given to our eligible customers. This bot positively impacts all stakeholders of our company; it helps our low-income customers by assisting them in receiving grants to pay their electric bill, it supports our communities by informing them of options available to them, the grants also reduce our potential electric disconnects and lowers bad debt write-off to the company, supporting our shareholders’ interests, and assists our employees by performing an outreach that would have previously been done manually for a minute subset of who the bot is able to contact. Built With automation Try it out github.com

https://devpost.com/software/central-patient-register

Process Flow Chart Pie Chart for Top diseases with most number of people affected in district Line Chart for Patients Corresponding to Different DiseasesAgainst Age Inspiration Covid-19 pandemic situation in India as well as all districts but districts level authorities don’t have idea about the patients and diseases information. So, this process provided the all information about the patient and diseases then district level authorities easy to handle this type of the situation. What it does • Collect the patient details in standard format from the all district level hospitals. • Bot will segregate data disease wise and will generate the evident data through chart as well • Bot will generate the different types of report (clustering the types of disease originating in particular area ) and bot will send the all information to district level authorities. Additionally: BOT can categorically post the same updates on district portal How we built it • Patient registration form filled by hospital. • Bot will collect all patient information from district level hospital. • Bot will merge the all hospital of patients information. • Bot will show the age wise bar chart and disease wise pie chart. • Bot will highlight the district as well as show the count patient and disease wise in map. • Bot will send email with all reports to district level authorities. Challenges we ran into • AA 2019 being very different compared to previous versions was itself a challenge to understand and work upon. • To implement idea of Central Patient Register on National level and to collect and manage huge data was bit of challenging Accomplishments that we're proud of • To get the desired Outputs what has been thought of and decided in the Project Planning Phase. • Got well Equipped with the new functionalities added in AA2019, like extracting and writing excel data through table format, incorporating Python to analyses the collected data. • Proud to generate the reports that could help India as a whole to be aware from the CORONA pandemic and insights of the hotspots areas to avoid spreading contamination and take necessary precautions. What we learned • Correct Data collection and analysis could play the vital role in predicting the future danger and to prepare ourselves for the corresponding precautions • AA2019 has come up with new add-ons that enhanced the data analysis capacity and the scope of automation. What's next for Central Patient Register • Bot can maintained those information state wise. • Bot can maintain the accidental cases and other cases. • Bot can categorically post the same updates on district portal. Built With dashboard excel folium forms javascript matplotlib pandas python web Try it out drive.google.com

https://devpost.com/software/covid-hero

chifa - the covid hero chatbot web page chatbot chat session Inspiration Since the outcome of fast-growing pandemic Covid-19, it has become important for us as an individual to keep a minimum distance from other well beings that we call social distancing. It has become important to know the precautions and so one may face many doubts and queries related to COVID. To keep us aware and to answer the COVID related queries we have developed a chatbot called COVID-hero that will guide you throughout this global disaster. How we built it This app lets you know the coronavirus cases in your country. It’s more than statistics, it’s also helped the user to know what the Do’s and Don'ts in this pandemic are. It also helps to know the symptoms of COVID-19. Permit to the invalid persons (blind or illiterate) scan QR and that 'll read for us the notice Remember the drugs taking time for persons who's has Alzheimer for example There is also an option for self-screening. You can use it to test yourself whether you have coronavirus or not. Challenges we ran into This project deals with API and Dialog flow. API will let you the exact data of the country. Most members we new with dealing with API. They were knowing what API means but didn't do a practical project. This was taking time busting for us. Most importantly, we were having time timezones so our coordination was not establishing among each other. This project needs a lot of attention. Accomplishments that we're proud of At last, we planned our whole work which team members have to do what. Due to timezone, we establish a common time we all met and discuss our work. We successfully created the chatbot with teamwork and consistency. As most of them never experienced any hackathon. Everyone shows their teamwork and at last created our project at best. What we learned With teamwork we accomplish our project. We learn team collaboration and remotely working. We all learn new technology like trending one chatbot. We learn HTML/CSS and javascript. We deal with APIs and dialog flow. We know how the frameworks work. The most important thing we learn consistency and teamwork which makes this project successful. Our connections increased with this hackathon. What's next for COVID-hero We are planning to introduce this website on a large scale. We will be adding more features like Doctor consultancy, showing data through graphs, and informing the nearest hospital with an SMS. We will work on the website and make it more useful by adding a sign-in feature. We will also create a chatbot for the hospital. With data collected we will make more usefull and more intelligent the chatbot to permit anticipate users illness. Built With css dialogflow html javascript node.js Try it out covid-hero.herokuapp.com github.com

https://devpost.com/software/whatsapp-and-rpa-automated-loan-application-processing

Inspiration - The time taken to process loan application when I applied for a loan and the current COVID-19 scenario where people have lost their job and would like to apply for a loan What it does - It automated the application process and helps the user to apply for a loan, get details on FAQ for loan document, etc. right from his mobile using bank authorized WhatsApp channel then all the documents are collected via the bank website and verified against 6 parameters by RPA Bot and then it forms the user with the application status in less than 5 min. Alos the bak gets the data to perform analytics on it which will help the bak to take key business decisions based on the data collected. How I built it - Level -1 WhatsApp bot integrated with NLP, Level-2 Website to collect user data, Level-3 RPA bot with Work Load management to do the heavy lifting of multiple verifications for the data and match them against submitted documents. Challenges I ran into - WhatsApp free trial with limited functionality, barcode reading with python as free libraries have limited options.No access to user information from Cibil and Experian website which is publicly available hence had to use dummy values Accomplishments that I'm proud of - Created this whole project in less than 24 hours and the learning of coalescing 3 different technologies to create a unified solution. What I learned - When we try to solve a real-life problem the ideas and bring this into action drive us and also RPA when combined with next-gen technologies, can be if used to cater multiple un-explored solutions. What's next for WhatsApp and RPA Automated Loan Application Processing - Creating an ML library to do predective Analysis and create another way of automating this where the user can directly fill the details and uploads documents from WhatsApp along with multi-lingual support.. Built With a2019 api barcode-reader iqbot lamp-stack natural-language-processing php python rest whatsapp

https://devpost.com/software/chatbot-using-ibm-watson-automation-anywhere-and-ai

Android flask Noise reduction node-red Automation Anyhere api call Inspiration Started when my employees worried of getting sick and scared of going outside, So I reaches out to Dr. anjali and started working on this project. What it does It will give active cases near you, you can ask queries reagarding covid-19, detect coughing How we built it We built it using python , C Challenges we ran into It has taken tremendous effort to build this during the hackathon. Including training multiple AI model in limited amount of time, Configuring IBM cloud, Node-red application, Building a flask RESTful app, android application and also integrating with AA Accomplishments that we're proud of Building succesful model What we learned Building AI models, IBM and AA platform features What's next for Chatbot using-IBM-Watson Automation Anywhere and AI Including more complex automation using AA Built With c flask python Try it out github.com

https://devpost.com/software/smart-checking

SMART Checking Inspiration I have travelled during 'lockdown' and found out that travel in COVID-19 era is hard. It requires longer hour, many health-related checking and a lot of documents.Therefore, a simpler way for checking travellers COVID-19 era would be crucial. What it does SMART Checking use bot to automate checking travellers documents, extract data,and gain insights from the documents. So, any decision could be made in much shorter time. How I built it SMART checking is built using Automation Anywhere Enterprise A2019 What's next for SMART Checking Bot for more documents format. Built With a2019

https://devpost.com/software/face-mask-recognition-for-covid-19

End - To - End COVID-19 Solution Face Mask recognition: What it does : The application identifies who all in the image are wearing a face mask. It can be used for single person image or even group image. How we built it : Python code first identifies the number of faces in the image. Then it checks whether every face has a mask on it or not. Once python checks for face mask in every image, automation anywhere BOT will create a report to show how many people had face mask or not Challenges we ran into : Create a object detection algorithm from scratch was a difficult task as it required proper environment setup and integration. Accomplishments that we're proud of: The algorithm is accuracy is same as that any prebuilt object detection recognition tool in market What we learned: Building python algorithms from scratch and also integrating them with RPA tools What's next for Face mask recognition for COVID-19 : we are working on a full fledged solution for COVID19 were the algorithms for face mask, face recognition, social distancing, temperature check will all be integrated with automation anywhere and the final report will have details of all Built With python Try it out github.com

https://devpost.com/software/covid19-infobot

Inspiration People are in great misconceptions and believing myths regarding Covid 19. So, I wanted to create a bot which can be a fact machine for everybody What it does This info bot is capable of telling latest data of covid19 cases in India and fact regarding covid 19 How I built it Its built using dialogflow and nodejs webhook. Challenges I ran into Implementation of webhook and creating a bot was very new to me this is my first chat bot Accomplishments that I'm proud of I have made the bot capable of bursting myth of covid19. What I learned Dialogflow, NodeJs and ExpressJs What's next for Covid19 Infobot I want to implement languages like hindi and want to make it more capable of giving facts. Apart from that I want it to give more details on live covid19 data so it can fetch data for every city. Built With bot covid19 dialogflow express.js heroku node.js react redux Try it out bot.dialogflow.com souravdey777.github.io github.com github.com

https://devpost.com/software/forgeconnect-automate-bot

ForgeConnect Automate Bot automates the creation of apps in the Atlassian cloud. Try it out bitbucket.org

https://devpost.com/software/autocode

Architecture Diagram Problem Statement Our Inspiration COVID-19 has forced most of us to work from home for the last 3 months or so and now we realize that it may soon become the new normal. This transition has brought new challenges to our workdays. At the end of each day, many of us have felt burnt out and we have been looking for productivity-improving tools and techniques. All of us felt the need of a personal assistant, who could help us summarize the meeting points in a deck, who could create flow charts/architecture diagrams out of handcrafted notes and send it to different stakeholders, who could help in creating mock-up web pages, and so on. While such an assistant would always be an asset; in current times, it can prove to be a game-changer. What it does? We as developers, always have tools and skills to automate a portion of our tasks, but what if we could give a similar power in everyone's hands? Users can now take a picture of their meeting notes/ hand-drawn mock-ups and send it to AutoCode. AutoCode will read the image and extract relevant information from it. It then creates a PowerPoint deck or a web mockup for you and emails it to you. AutoCode is building a modern productivity suite for workers. All of us would want people to focus on what matters instead of wasting their time on mundane tasks, such as formatting slides, aligning shapes, annotating images, reshaping training data, etc. How we built it We used a combination of Computer Vision, RPA and Python language to build the AutoCode solution. The solution can be divided into 3 modules: A2019 RPA code, Computer Vision (Google API) python script, and another python script that generates the PowerPoint/web page. The A2019 code lies at the heart of our solution. It orchestrates the entire process and decides the flow of the process. The computer vision (Google API) python script extracts the text and coordinates of the entities present in the input handwritten image and saves it in a form of structured excel table (xlsx). The PowerPoint creating python script uses this structured output and maps out the entities in a PowerPoint template, thereby, creating a deck. Challenges we ran into As a team, we all agree our biggest challenge was to work remotely and stay connected to make sure that we develop this solution efficiently and in time. Our other challenge was to find and use the appropriate technologies to get the desired results. We tried multiple Computer Vision APIs by providers such as Microsoft, AWS, Google, Abbyy, etc. to arrive at a decision of using Google Vision API. Also, creating the logic to convert structured data into PowerPoint and HTML codes was a challenging task. In addition to these challenges, we had many plans for our end product, all of which could not be possible within this time but we would surely want to work on them in the weeks to come. What we learned First, of all, we learned, working, and collaborating in this new normal. Probably, it was the first hackathon, that we participated in, remotely. It was difficult at times, but an enriching experience altogether. Secondly, we learned that the automation use cases are more obvious and evident than what we think them to be. At times, we are just stuck with point use cases that come from our client discussions and ignore the broader use cases that could have a much wider impact on society and business. Thirdly, RPA, along with other cutting-edge automation and digital transformation technologies, has great potential in improving business efficiency, enhancing employee productivity, and driving innovation across industries. Last but not the least, this hackathon has enabled us to think more innovatively and focus on the problem at hand; which many times gets difficult with the 'Business as usual' ecosystem we tend to work in. What's next for AutoCode Today, AutoCode is an innovative product and we have plans to scale it to become a generally available product for all. Initially, we plan to pilot the solution for a few companies and customize as needed to align with their templates, company logos, client logos, architecture diagrams, process flows. With time, we plan to understand the nuances of how we can scale this product to all the companies and more users, We will make required upgrades to the product and roll it out for the broader market. The product will be equally relevant in the post COVID world, as it is today, even if we assume an unlikely scenario of things to get back to pre-COVID normal. Built With a2019 api automationanywhere computer-vision google-vision imap json python python-pptx smtp Try it out drive.google.com

https://devpost.com/software/website-build-bot-templates

Website Build Bot Templates contains template forms that allow the automatic creation of websites of various types: blog, event, company, and ecommerce. Try it out bitbucket.org

https://devpost.com/software/covid-19-challenge

Inspiration WhatsApp instructions of use Start the conversation Give us feedback Winners at the COVID-19 Global Hackathon Inspiration Across the world, hospitals are collapsed because of thousands of citizens requesting medical services related to the pandemic. Just in Europe, over 1 073 947 people are directly affected by COVID19 , and we got really inspired by a real story of a Doctor, that writes in an article "I’m a Doctor in Italy. We Have Never Seen Anything Like This, my country’s health care system may soon collapse. None of us have ever experienced a tragedy like this." The coronavirus COVID-19 has reached our cities, crossing borders and radically modifying our daily lives. The exceptional nature of the situation means that each and every one of us has to invest efforts that help stop this pandemic, but how can we do it? So our team start thinking: What if we start promoting telemedicine and digitalising the consults related to symptoms or where to find hospitals, test labs, food or hygiene products. Also helping to fight Fake news and providing motivational content for any person passing through this hard moment. Telemedicine & consultations online has great advantages: we do not saturate Hospitals with non-urgent visits, we lower the potential infection of doctors and also we reduce the number of displacement and, therefore, the contacts that may cause the spread of the virus. * Hospitals are collapsing because of the overwhelming request of medical services related to this pandemic. * And this are also other problems we are seeing and it inspire us to build this solution: 1) Healthy individuals with lack of knowledge and inaccurate information unnecessarily going to the hospital with the risk of being exposed to the virus. 2) Waiting times prolonged for people that need the immediate attention. 3) Hospitals Exceeding their capacity & resources with non-emergency cases. What it does Through a virtual assistant that runs on WhatsApp, we provide non-emergency support, an through Natural Language Processing models we try to understand how the users feels during the day, for example: User say: "Bad, I feel very sick" I think that I'm infected Please connect me with a Telemedicine Volunteers Marie resides in a remote town in Sussex in England, and during several weeks she presented pronounced cough and headaches. So, she start getting worried, and decided to consult a doctor, but this time she doesn't move from her home, and she will be treated in Amsterdam, 7,300 kilometers away. How? She turn on the mobile, open her WhatsApp and connect to a video call, detail her symptoms in the conversation, and wait for a doctor to connect to the call. User say: "I'm ok, just looking for information" I live in Santiago de Chile and I want to track Today's news about COVID-19, find Hospitals near me, Test Labs, find Food and Hygiene products or identify a Fake new. via GIPHY User say: "I want to become a Volunteer" Doctors, Pharmaceutics, Psychologists, among other health workers can become members to our Volunteer Global Telemedicine network. Become a Hero How we built it We use Natural Language Processing models to understand what users are saying and typing... We connect the NLP model to FB Messenger and Whatsapp API to capture Parameters from the conversations and provide the users the best option. Also, this effort wouldn't be possible with the support of over 100 Developers and Citizens that help us on task's such as Testing, conversational design, communication among others. Their names are: Daniel Rojas Roa (VR/AR Developer), Andrey (Health Coach), Joshua Pedraza (AI Developer) & many other testers of the platforms across countries like: Canada, United States, México, Guatemala, Brasil, Chile, Costa Rica, Colombia, Spain and others. Challenges we ran into -Terms of Use of Messenger & Whatsapp for Business API for Emergencies Services. -Train the model in different areas such as: Feeling Bad or Sick, Feeling ok and looking for news, places or products, and Becoming a Volunteer. Accomplishments that we're proud of Whatsapp Virtual Agent: (Testing Instructions): 1- Add the phone number as a contact: +1 415 523 8886 2- Write the command: * Join * 3- Start the conversation: "Hi", "Heeelp", "Let's start" or any other Open Github Repo to our solution Terms of Use What we learned Contribution with multiple countries to address this pandemic can help us have a better context of the challenges that we share and which one are really different, make a match between them and scale a powerful solution against human main challenges, such as COVID19. Telemedicine is an effective first filter and allows Medical & Health center's to allocate available resources to those critical cases who really need them. In addition, using remote control terminals, it facilitates the monitoring of chronically ill patients, to whom treatment is provided at home whenever possible. What's next for Bacty Bot Build cheap Telemedicine equipment Empower Doctors across the world //Disclaimer: Opinions are our own, not of any company, program or their products. Each Developer Expert is fully responsible of their services, and is not affiliated with other Company nor do they offer services on behalf of a Tech Company. Customers are fully responsible for their use of services, if any. This code is a sample, should not be used for any potential production workloads.// Built With facebook-messenger machine-learning natural-language-processing whatsapp-api Try it out youtu.be youtu.be github.com youtu.be

https://devpost.com/software/covid-19-informer

Menu Daily Graph Language support Understand User Queries ML based daily Prediction Location based response Latest News Deaths and Infected Updates Recovery Update Inspiration With the spread of fake news about Covid-19, with thought why can't we use the same resource to spread proper authentic news for public awareness What it does Its a WhatsApp Chatbot which having key features as follows: Designed to send you realtime statistics updated every 1 hour, you can also send Hi to get current data from the bot anytime !!! District wise data for each State State wise data for India Country wise data Some short headlines for the day Predictions for next day using ML with past each-day statistics Language support: Hindi is also available You can even send your location to how far you are from nearest COVID-19 infected patient Apart from the queries you ask the bot which is guided by menues, the bot can understand phrases to some extent. Graph of last 15 days cases every day sharp at morning 9:00 AM How we built it We build the server using nodeJs which uses services of Chat-Api to interact with the Whatsapp server. Moreover we have used crontabs to schedule regular updates for our database and to inform users if there are any new cases. Challenges we ran into Understanding the user queries feature was started with a bit of hard coding but with due course of time we implemented it properly with NLP( Natural Language Processing). Accomplishments that we're proud of We already have 350+ users onboard who are regularly getting informed by our chatbot. What we learned We learned many things like serverside scheduling, standalone JavaScript codes for updates, etc. But more over all these we learned how it feels when we do something for the society. What's next for Covid-19 Informer With this Covid-19 Epidemic, We've learned this type of situation become infestation only due to lack of potential and transparent communication between the government and citizens of the country. In this world of technology, almost everyone of us have smart phone in our pockets, but most of us are far away from the genuine information, helpful services from the Internet. On the other hand, everyone has WhatsApp messenger installed and working. We have come up with an idea to deliver the information and these services to their whatsapp. Our solution includes a fully automated chat-bot and using some native services like locations, camera etc and we think that this can used for a hell lot more purposes. Built With chat-api crontab natural-language-processing node.js yandex Try it out pcms19.000webhostapp.com github.com

https://devpost.com/software/linkedin-jobs-finder

Inspiration Helps students find jobs on LinkedIn during Covid-19 What it does Automates the job finding process How I built it Built using the bot service in automation anywhere's Control Room Challenges I ran into It was my first dabble into RPA. I was new to some things but I didn't face many difficult challenges Accomplishments that I'm proud of It works! What I learned Robotic Process Automation What's next for LinkedIn Jobs Finder Add more features Built With automation-anywhere-bot

https://devpost.com/software/onboarding-automation

On-Boarding Form As per our policy in AstraZeneca, we have obtained permission from Botathon managers to showcase our bot internally with AA Inspiration Due to this lockdown owing to Covid-19, many organisations will face challenges in on-boarding new joiners to their company. New joiners would find it difficult to print, scan documents due to the closure of all shops. Hence we decided to make this transition smooth by making it digital What it does This Bot will generate a background verification form and send it to each new joinee and help in collating the information to the HR team. Based on HR's response, welcome mail will be triggered to each individuals. How I built it We used Google Forms to create a background verification which includes all the personal, educational, previous employment if any and reference details. Using AA 11.3 and VBA we automated the process. Challenges I ran into Time constraint and working remotely with team members Accomplishments that I'm proud of Being a part of a project which makes a positive difference in this Covid-19 situation What I learned It is possible to work together as a team even in remote workspace What's next for Onboarding Automation We are hoping that this Bot will make a significant difference in On-boarding process for all the organisations and further try to improve the capability of the process Built With aa11.3 googleforms vba