Venue: ESPC 2022 Competition

Reviews:

final_score: rating: 4: Accept + Potential Winner. This work can be presented and it is a strong contender to win this competition.
review_content: summary: Quite a complete end-to-end solution.
strengths: This is clearly above PoC level and it is quite astonishing if everything has been achieved in this competition.
Product & service oriented end-to-end approach, which is technically feasible.
Technically “complete” realization, including the sensor product & full-stack IoT solution.

weaknesses: We cannot point out any significant weaknesses.
review_title: null

final_score: rating: 3: Accept. This work can be presented during the event, but it is not a contender to win the competition.
review_content: summary: Pawamaan" Smart Air Quality Monitoring System can be presented during the event. It combines sampling CO2, VOCs, PM and environmental variables and it is interesting to learn what the team thinks their contribution is to relatively saturated low-costs sensor research market. There are good ideas mentioned such as adding voice control features to the sensor. However, there is no discussion on data accuracy, calibration or an indication that they understand the basic physical processes involved in the gases and particles they are measuring.      
strengths: The main strength of the Pawamaan" Smart Air Quality Monitoring System is that it provides the user an end-to-end solution where the user can see six parameters of air quality with reference to climate change discussion: CO2 ,Particulate matter, Volatile Organic Compounds, Humidity, Temperature and light intensity. These parameters are measured and displayed on the device and the mobile app. 

The team contributes to the upsurge of low-cost sensors in the research literature and in the market.  

The prototype air quality sensor with its casing looks quite mature indicating that the work has been done previously.  The app works on both Android and IoS platforms which is a strength.  

The idea of adding voice control features to the system is very interesting. 




weaknesses: The main weakness of the Pawamaan" Smart Air Quality Monitoring System is that is that there is not discussion on sensor sampling rate, measurement accuracy, calibration procedures, data analysis and data visualisation. There is a large body of work on using ML for calibrating low-cost sensor components.  

The use cases are inadequately described.  The sensors chosen are more suitable for indoor sampling and not applicable for outdoor environments such as football stadiums. To evaluate the performance of the system there needs experimental design indicating an understanding of what is being sampled. For example there are 1000s' VOCs and we need to better understand the purpose measurement.      

It not specified what is 'smart' about this system in comparison to the many other low-cost sensors that have been developed.
review_title: null

final_score: rating: 4: Accept + Potential Winner. This work can be presented and it is a strong contender to win this competition.
review_content: summary: The author as presented a complete end-end system for air quality measurement. 
strengths: 1. Clear video demonstration.
2. System packaging is good
weaknesses: 1. Hardware block diagram is missing
2. Document should have been more descriptive.
review_title: null

final_score: rating: 4: Accept + Potential Winner. This work can be presented and it is a strong contender to win this competition.
review_content: summary: The authors present Pawamaan an air quality sensing system that integrates various off-the-shelf sensors. Their solution enables users to view the current air quality levels either by using the on-device display or a mobile app. 
strengths: - The problem being addressed in important, and the solution is timely. 
- The authors have built an end to end system that takes into considering various deployability and usability issues. 
- The systems integrated various sensors and the user interface on the device displays the readings in a user friendly way. 
- The solution is well presented, and the video though on the shorter side (see weakeness) has sufficient details to highlight the strengths of their system
weaknesses: - The first minute of the video includes stock footage and in most cases you need explicit permission from the creators of videos (such as news sites) before you can embed them in your video. 
- The video could have been made longer with details on the challenges faced in building the system, the approaches taken to address the challenges, and the avenues for future work. 
- What was the power consumption of your system? Will it be possible to include additional sensors in your system? Some insights on extending the platform would have been useful.
- What is the overall weight of your solution? Will it be possible to have fixed deployment of Pawamaan where the device is plugged to the mains supply?
- It would be interesting to see the power consumption of the various modules given that the system is running on a 10000 mAh battery. It would be nice to see how much power savings can be achieved by disabling the communication, caching the results and transmitting only when the air quality level change by a significant amount.
review_title: null

final_score: rating: 4: Accept + Potential Winner. This work can be presented and it is a strong contender to win this competition.
review_content: summary: In this work, an air pollution monitor was developed measuring six different parameters such as CO2, PM, VOC, Temperature, Humidity and light intensity. A proper 3D box is made as well as app is designed to see the data.
strengths: 1. Very good presentation video. 
2. Good 3D design of the air pollution monitor. 
3. Good app. 

weaknesses: 1. Not sure why Raspberry Pi is needed? It needs too much power. The design is not low-power.
2. Display has only one PM parameter. Which one? 
3. The sensors used are not accurate. For example, DHT11 has high error and failure rate.
4. No calibration of sensors. 
5. No block diagram or flow chart. The writing could had been better.
6. No plots of data. 
7. This device is unsuitable for outdoors as outdoor air and indoor air pollution issues are different.
8. App could have used plots.
review_title: null

Decision: Accept