ghanaopendata/ghanaian-research-english huggingface dataset:
Development of a low cost sensor for measuring and apportionment of black carbon in Ghana

The International Energy Agency estimates that 970 million Africans use biomass for cooking [1], emissions from which expose them to pollutants like particulate matter (PM) and black carbon (BC). Due to its small size (range: 135-145 nm) [2], BC is easily inhalable and present worse health impacts than many other PM species [3]. A considerable challenge is accessing affordable standard BC sensors; most cost US$3,000 to US$20,000 and are thus too expensive to deploy in large numbers [3] to provide high spatial resolution. Therefore, in recent low-cost air pollution sensor networks, there has been a noticeable gap in the absence of a BC emissions inventory [3]. In this research, we have designed a BC sensor that costs less than US$200 and incorporates a rechargeable battery and Wifi communication to enable long-term, remote operation. Leveraging Pugh Charts, we chose materials and components available in Ghana. Drawing from recent studies in developing low-cost BC sensors, the sensor uses an optical measurement technique to measure the absorption coefficient from the degree of weakened light intensity of 880 nm wavelength to invert the BC aerosol concentration. We chose absorption measurement at 880 nm to define BC concentration because, at this wavelength, BC is the predominant PM species to absorb light. We developed a low-fidelity prototype where we integrated components to enable the measurement of carbon monoxide (CO) and nitrogen dioxide (NO2) concentrations as well, leveraging the MiCS-4514 sensor module. Simultaneous detection of high BC and CO, and BC and NO2 concentrations can aid in indicating nearby biomass combustion and diesel engine emissions, respectively [4], thus painting a complete picture of major BC pollution drivers. These emissions data will aid policymakers to devise data-driven solutions to BC-associated human health impacts.

Source: Ashesi
Development of a low-cost biomedical device to enhance pneumonia diagnosis in children

Pneumonia has contributed greatly to child mortality, especially among children under the ages of five in sub-Saharan Africa, killing more children than the number of children dying from HIV/AIDS. The current methods of diagnosing pneumonia involved physical examination and chest x-ray which are limited by low accuracy, high error margins, higher cost, and stands the risks of inducing cancer. In this work, a low-cost, non-invasive biomedical device was designed and developed to improve accuracy in diagnosing pneumonia. The device functions to detect fluid in a lung consolidated by pneumonia. Dry grouting sponge was used as a phantom for a healthy lung, while a wet sponge was used to mimic a pneumoniaconsolidated lung. Surface exciter was used to produce sound waves which travelled through one side of the phantom and are detected on the other end using an electronic stethoscope. The signals detected were digitally analyzed using MATLAB and AUDACITY software. The differences in resonant frequencies from the power spectrum analysis of sound waves as they travelled through the sponges were used to distinguish between a pneumonia-consolidated lung and a healthy lung.

Source: Ashesi
Development Of A Tuberculosis Diagnosis Device Using Microfluidics And Lateral Flow Assay

Four hundred twenty-four thousand people die every year in Sub-Saharan Africa due to Tuberculosis (TB) infections. 25% of these deaths are from people living with HIV (PLWHIV). This mainly occurs because Tuberculosis (TB) is more challenging to detect in PLWHIV because of their low viral loads, hence inadequate sample collection for testing. Traditional methods, such as Sputum smear microscopy and bacterial plating, are inaccurate if an insufficient sample exists. A solution such as GeneXpert is advanced and accurate but costly for most rural clinics. This results in late diagnosis and treatment, resulting in high death rates due to TB in PLWHIV. This project aims to develop a tuberculosis diagnosis device using microfluidics and lateral flow assays (LFA). What sets this device apart is that it requires only small sample amounts. Additionally, devices use centrifugal microfluidics to improve sputum processing. The device includes an LFA that uses gold nanoparticles and aptamers for easy visual TB detection. A key design feature is a motor that mixes sputum with an 8% Sodium Hydroxide (NaOH) solution to break down mucus. This prototype can give results in less than 30 minutes, operates on a 6V battery, and weighs under 0.3 kg, making it ideal for rural settings. Future work will focus on biological validation using sputum samples from HIV-positive patients and the fabrication of the LFA using gold nanoparticles and aptamers.

Source: Ashesi
Development Of An Intelligent Storage Device With Fuzzy Logic Decision-Making For Extended Shelf Life Of Tomatoes

This project presents the development of an intelligent storage device with fuzzy logic decision-making designed to extend the shelf life of tomatoes for smallholder farmers in Ghana. Post-harvest losses of perishable crops significantly impact food security and farmer livelihoods in developing regions, with inadequate storage technologies being a primary contributing factor. The system integrates temperature, humidity, and gas sensors to monitor critical storage parameters in real-time, with environmental control achieved through a novel combination of evaporative cooling and low-voltage electrostatic field technology regulated by a fuzzy logic controller. To ensure reliable operation in areas with intermittent electricity, the device incorporates solar power with battery backup and an automatic changeover system. Comparative testing over a 14-day period demonstrated significant improvement in preservation performance. The smart storage system maintained optimal conditions (13.8-14.6ireduced weight loss by 76.3% compared to traditional storage methods and 60.3% compared to basic evaporative cooling (p < 0.0001). The fuzzy logic controller outperformed conventional PID control, with 68.4% reduction in steady-state error while consuming only 12.8W of power

Source: Ashesi
Development of modular hardware and software system for fraud detection using machine learning and data mining techniques with applications in power systems energy thefts

Electricity is a critical commodity that powers the technology that nations and their inhabitants heavily rely on for economic and social activities. However, the issue of electricity theft threatens the looms large for these countries as these misdemeanours cost electricity utilities close to $20 billion worldwide [4]. Ghana is taking the needed steps to combat electricity theft such as employing smart meters and altering supply frequency. There are no methods that completely eradicate the issue of electricity theft, but the solutions deployed by Ghana's electricity utility are also expensive. This project presents a novel method of detecting electricity theft using data mining and machine learning utilising non-intrusive load monitoring techniques (NILM) on a low-cost smart metering device. NILM enables one to know the power consumption levels and durations of individual appliances from the total consumption measured. As the artificial intelligence algorithm is enhanced by the NILM techniques to understand the behaviour of the consumer, there is a greater possibility of making an accurate power fraud prediction and making a fruitful inspection. The final accuracy of the machine learning model that detects theft was tagged at 91.8% and the non-intrusive load monitoring correctly identified the ON/OFF states of appliances 91% of the time but performed not as well in predicting their energy consumption. Furthermore, the smart meter provides electricity utility customers with a device-level breakdown of their consumption for energy monitoring purposes.

Source: Ashesi
Development of sustainable roofing light weight ceiling panels

The need for ESE (Economically, Socially and Environmentally) sustainable building materials has increased over the past few decades due to scarcity of resources and environmental concerns. This study reveals the feasibility of using Epoxy and Royal Plam Fibers (RPF) in the development of affordable and eco-friendly ceiling panels, with the primary goal being to investigate the mechanical properties and compare both the mechanical and thermal properties with existing ceiling panels. Locally sourced RPF was chemically treated with potassium hydroxide. The pullout test determined the critical length of RPF. At ten wt% fiber fractions, composites were to give all the best properties in terms of ultimate tensile strength (UTS), toughness, stiffness, and young modulus. A comparison of the mechanical and thermal properties of mineral slag and Epoxy composites was carried out. A statistical analysis established the significant difference in the mechanical and thermal properties of the fibers and composites. Implications for the results were discussed for the potential mass production of affordable ceiling panels.

Source: Ashesi
Device register for theft deterrent and device recovery

Many people make use of electronic devices such as personal computers, laptops, cameras, mobile phones, gaming consoles, and a whole range of electronic devices to make their lives muc h more productive, entertaining and also to bring about significant ch ange in the world. Just as the population of people who do so is increasing at a geometrical rate, so also is the rate of theft or loss of those devices, and more times than often, there is always a slim chance of recovering those l ost or stolen electronic devices. The aim of this project is to provide an online pla tform whereby people in Ghana can register their electronic devices with ease, alert the necessary authorities in the event of theft or loss, and chec k via an online or mobile service if the reported device has been found. This application is not a guarantee of recovering all missing or stolen elect ronic devices reported in the country, however if most gadgets are registered , it will discourage the theft of electronic devices, reduce and eventually put a stop to the second hand sale of those devices in the black market, and aid in recovery of missing or stolen devices.

Source: Ashesi
Disaster management system: Providing an effective communication mechanism and accessible data analysis in Ghana

Disaster is an unfortunate, yet common phenomenon in our world today. This phenomenon stakes undesirable claims on lives, infrastructure and services alike. Those affected both directly and indirectly must overcome challenges, not only during but also, after the occurrence of disasters. Imperatively, it is always prefered to be better equipped to prevent the disaster and avoid it altogether. Yet that is impossible as not all disasters are man-made. Disaster management then must be up to the task to reduce consequences to the barest minimum. This has not been the case in Ghana. There is a great need for efficient communication channels and accessible data that will greatly help to preserve lives and property in the country. This project focuses directly on meeting this need. This paper outlines the various technologies and processes employed in developing a disaster management system that has great potential in solving the said problem. The application is an Android application with a simple and intuitive design. Challenges encountered in the development process are also discussed. In addition, suggestions on future work on this application are also given.

Source: Ashesi
Disease detection of tomato crop in a hydroponic farming system using a convolutional neural network

There is a need to explore hydroponic farming as a new way of farming produce in urban areas in Ghana. Hydroponic farms usually take up less space than traditional farms and employ a level of automation, making them easier to manage and a more appealing option for the youth. Crop disease identification is usually made best with expert eyes; however, work has been done to improve disease detection using computer vision on single leaves. To aid in the automation of disease identification, there is the need to detect and classify crop diseases on leaf clusters to implement preventions early and increase crop yield. This project focuses on detecting five tomato crop diseases, namely, Bacterial spot, Black leaf mould, Grey leaf spot, Late Blight and Powdery mildew diseases. The resulting model has an accuracy of 99.01% on the test dataset, which included images of single tomato leaves, clustered tomato leaves and images with varying brightness. The model is then uploaded onto Android and iOS mobile devices for convenient, real-time disease classification. The accuracy obtained from the mobile devices is about 90% ± 6.8% when using images from the internet.

Source: Ashesi
Does political stability improve the aid-growth relationship? A panel evidence on selected Sub-Saharan African countries

Significant ambiguity still surrounds the aid-growth relationship despite fifty years of research on the subject. For the case of Sub-Saharan Africa (SSA), a possible reason for the lack of consensus is that until recently the influence of political stability on the aidgrowth relationship had been largely ignored despite its relevance for the region. Further, although overlooked by the literature, the Instrumental Variable (IV) technique, the preferred treatment method of endogeneity in aid-growth relationships, may be ineffective in eliminating endogeneity bias because typical instruments for aid are neither sufficiently exogenous nor strong. Using a dataset of 31 SSA countries from 1984-2007, we re-visit the question of whether aid can spur growth in SSA using firstdifferencing (FD) to eliminate unobserved effect endogeneity while focusing on the role of political stability on the aid-growth relationship in SSA. Results suggest aid promotes growth conditional on political stability in SSA and that First Differencing (FD) eliminates a substantial amount of the endogeneity bias. Our results demonstrate the pertinence of a stable political environment to attaining the UN’s Millennium Development Goals (MDGs) for SSA countries since these goals inherently assume that aid can promote growth.

Source: Ashesi
DoverColl: A system that makes use of IoT to enhance efficiency in waste collection of urban households in ghana

Traditionally, if an urban household wants to dispose of the waste generated, they subscribe to a company's collection service such as Zoomlion which is periodic. However, if there is waste to be collected before the collection date, it leads to an overflow of waste which has potential health risks and brings about foul odours. DoverColl is a waste management system that stream lines the waste collection process by connecting households with waste collectors in real-time with an IoT component. Waste collectors are able to find households easily as a result of routing applications like Google Maps. The system employs a hybrid methodology of the reuse-oriented and agile methodology. This hybrid methodology chosen for this project is suitable because some components of the project exist already, so building one from scratch is less cost-effective and might not be as efficient. These components have been used in working systems, which would increase the system's availability and dependability. The project is also relatively large, and there is a need to make room for changing requirements to ensure that the solution we are building is relevant to the stakeholders and is a sustainable solution.

Source: Ashesi
Driver risk classification in auto insurance: Using deep neural networks and in-vehicle CAN bus data

Among the numerous ways auto insurance companies can contribute to safety on the roads whilst creating more value for themselves and customers is by effectively analyzing individual driver risk level. Every driver’s driving style is their fingerprint and when insurance companies can anticipate their style and the risk associated with it, they can create safer portfolios, reward good driving with lower premiums, customize customer offerings and penalize bad driving with higher premiums. A good driver risk assessment lies in identifying and analyzing behavioral patterns in driving. The challenge however with prevalent risk assessment methods in motor insurance are that they rely on non-precise data (age, occupation, address) and their assessment is merely descriptive, leaving little to no detail about the individual nature of the risk a driver might pose. In this project I design a web interface for users and use In-vehicle sensor data that identify driver behaviour patterns and a deep neural network with continuous learning capabilities to analyse and predict the driver’s risk based on the data from their vehicle.

Source: Ashesi
DUPA university calendar system

The pandemic took everyone by surprise and disrupted the operations of many institutions worldwide. As a result, many institutions have been compelled to undertake their operations remotely. Completely relying on third-party applications to manage the internal operations of an institution could be detrimental to it during situations whereby their servers are compromised by cyberattacks and redundancy failure. The Academic Affairs Department of Ashesi University has expressed its need for an internal system to manage and organize all events and meetings planned for the institution. The DUPA University Calendar is going to be built to meet their needs.

Source: Ashesi
Dynamic story writer for computer role-playing games

Computer Role-Playing Games (CRPG) are a genre of video games were the player controls at least one character, the character has attributes and relationships with other game objects and is important to the story. They are one of many entertainment media that have storytelling as one of its major components. The better the story component of a game the better the gameplay experience is. This project explores an approach to improving gameplay of RPG games by personalization of game stories. This is achieved by having an AI system generate the game story at run time by considering the decisions and choices the player makes. A benefit of this will be that all players will have unique stories and whenever a player restarts the game they will get a new story. This creates an amount of gameplay experience with each story and players get to be actively involved in the narrative direction of the game.

Source: Ashesi
Dzigua Enterprise inventory management web application

Inventory management is key in every business setting. Proper inventory management helps businesses to reduce cost and maximize profit. Hence, this project seeks to design and build a user-friendly inventory management system that will work on a web platform to allow the staff of Dzigua Enterprise in Accra to key in inventory details for their various agricultural products. The staff should be able to key in inventory received and removed either for processing or sales to allow for the team to know how much raw and processed materials they have at various points in time. They should also be able to manage their staff, customers, suppliers and system users.

Source: Ashesi
E-commerce and data analytics: Galleria (clothing commerce)

E-commerce is an important element of everyday living for the modern-day person and consumers appreciate goods and service when they provide accessibility and convenience. The purpose of this capstone project is to build an e-commerce and analytical website for "Jay Walker Creations", a tailoring and clothing business owned by a 28 year old entrepreneur named Joseph Walker. The website is designed to sell products and track consumer behavior and preferences, helping the business make data-driven decisions. With advanced analytical tools, the website gathers and analyzes data on consumer behavior, providing real-time insights on customer engagement, enabling Jay Walker Creations to adapt to changing consumer preferences and market trends.

Source: Ashesi
E-commerce for canteen services

Food ordering applications for restaurants and eateries in Ghana have features such as make orders, select options for delivery or pickup, and provide various options of payment.The context of this project is to ease the pressure on Ashesi University College’s canteen service, give customers flexibility in buying food and take into consideration customizations tailored for Ashesi community (such as the meal plan system). Ashesi has limited eating services, and with a growing population, using the cafeteria services at certain times of the day (where classes are over during lunch times) is a problem. The community will be able to view and order meals, select a delivery or pickup option, and make payments via delivery or otherwise (with the meal plan). There is also a review and rating system, to give instant feedback to the cafeteria services on the meals, and allow the customers to make an informed choice on what they want to eat.

Source: Ashesi
E-commerce for canteen services

This project is about creating an online ordering system for the canteens in Ashesi University College. In Ashesi, there are two canteens which serve a population of about 826 people. This puts pressure on the canteens causing the customers to wait for a long time when ordering food. The proposed system is an online ordering system which would allow the students and staff of Ashesi University College to order their food online. This paper also talks about the back end features the canteens would use to process the orders. The system would also help the canteens improve their services by providing the managers of the canteens with reports and reviews. The system would be a web application so it would need internet to work.

Source: Ashesi
Early stages of traffic modeling and simulation

In Ghana, most junctions are managed by semi - Intelligent Traffic Systems with a fixed-time traffic control. This has become possible due to the advancement of the transport management. Despite these technologies, traffic control is still an issue as policemen sometimes direct traffic even when there are working traffic lights. This is so because the systems have not been adjusted properly to help with good traffic flow. This paper will not focus on exploring how to measure these intelligent systems. It will focus on how Roundabouts since they are often used at large intersections in Ghana. With no intelligent traffic system, the traffic wardens manage traffic. Performance will be based on comparison with existing models. Through the results, this dissertation will outline the benefits of using such a system and the chain reaction it will cause.

Source: Ashesi