Levels of CO2 increase very rapidly in a poorly ventilated room with people, whose are more vulnerable to airborne diseases and may experience negative effects on decision-making and cognition.
ScholAir monitors air quality sensing CO2, temperature and humidity levels in an indoor environment like a classroom, for instance. The system would be very expensive if we measured ventilation precisely i.e. with thermal cameras, so, our sensors estimate ventilation based in the CO2 concentration levels. This information is sent to the cloud and users can check them using a mobile app, which can also send alerts in case air quality is not as good as expected: high CO2 or low humidity levels.
The system can interact with other equipment, such as an air circulator or an air conditioner, to turn them on or off in order to improve air quality. ScholAir website is used to manage the system and monitor the environment, registering classrooms, sensors and users.
The data generated by the system can also be used to analyze the air quality impact in human health and scholar performance. The space agency data is also used to improve air quality analyzes and to verify the influence of pollution and weather in an indoor environment.
We first considered air quality at schools as it is one of the most affected by social isolation during the COVID-19 pandemic and, probably, whose activities will be the last to be resumed, due to people concentration and proximity. However, ScholAir system can be easily adopted into any kind of indoor environment: public transportation, offices, restaurants, theaters and many others.
Our team is used to working with Internet of Things (IoT) systems, dealing with sensors and environment analysis, so this challenge is all about our research projects.
The solution is divided into three parts: hardware, back-end and front-end. The hardware includes CO2 and temperature/humidity sensors, an ESP32 micro-controller, an OLED display and a power supply. Codes and infrastructure to collect, process and store information are the back-end. ScholAir website and mobile app are the front-end.
The space agency data is also used to improve air quality analyzes and to verify the influence of pollution and weather into the indoor environment. Besides that, ISS air monitoring system inspired us and showed the importance of this challenge.
We used Arduino IDE to develop the ESP32 code, Thing Speak cloud IoT services to collect and store sensors data, MIT APP Inventor to develop the mobile app, Porkbun to create a public website domain (ScholAir website), Flask Python micro framework, Leaflet and Google Charts to develop the website (ScholAir website).
We were able to assemble the hardware components and send data to Thing Speak, develop the website and the mobile app. We had some problems with the CO2 sensor and in the process to deploy data into Thing Speak, but we were able to achieve a full working prototype to demonstrate our solution.
Other kinds of sensors, such as