Air Pollution Detection System Using Edge Computing
Existing solutions to measuring air quality can be expensive and potentially mutes high air pollution events. The IoT Pollution Project is exploring how IoT concepts can be applied with smart systems to detect pollution in real-time. Using a network of Raspberry Pi prototypes, the project aims to measure heavily populated areas around the City of Tacoma, while building a real-time interface measuring current air quality. The project also explores the use of edge computing as an alternative to cloud computing. The vast expansion of IoT devices poses threats to the infrastructure of cloud computing as more devices process and store data to the cloud. The project demonstrates how edge devices can alleviate the work done on the cloud by calculating rolling averages over a time interval on the edge device and then deploying the data to the cloud. The project uses Microsoft Azure Framework, IoT concepts and edge computing concepts to build the project architecture. © 2019 IEEE.
2019 International Conference on Engineering Applications, ICEA 2019
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Biondi, K., Al-Masri, E., Baiocchi, O., Jeyaraman, S., Pospisil, E., Boyer, G., & De Souza, C. P. (2019). Air Pollution Detection System Using Edge Computing. 2019 International Conference on Engineering Applications, ICEA 2019. Presented at the 2019 International Conference on Engineering Applications, ICEA 2019 - Proceedings, Sao Miguel, Azores; Portugal. https://doi.org/10.1109/CEAP.2019.8883458