Abstract

Nowadays urban residents, especially ones in the city are more aware of air quality and how it can affect their health. Due to the limitation of spare sense nodes, the air quality information is very coarse in resolution that is not greatly understood nor accepted by the community. The demand for better resolution, information and prediction of air quality in these areas has brought us to this solution. Our proposed system gives us a real-time and fine-grained data map of the air quality in the city by using crowdsourced automobiles as well as their built-in sensors, which significantly improves the feasibility and practicability of the system in a more dynamic way. By using LoRa WAN network, we can increase the range without worrying about the amount of sensor data to be transmitted. Once the data from the sensors is obtained, it is sent to the cloud through a base station where the data is processed using various algorithms and a fine-grained air quality pollution map of the city is generated to help understand the air pollution levels properly.

Full Text
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