Design And Development Of Aerial Vehicle For Air Quality Monitoring
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Abstract
Air pollution is a significant health concern in India. As a developing country, India has numerous issues such as air pollution and other issues. The aim of this study is to design and develop a system that is used to monitor and predict the air quality index (AQI) of the area using machine learning and IoT (Internet of Things). The system will generate AQI values and a line plot graph for future forecasting values. The proposed system will make it simple, convenient, and convenient for users to monitor air quality. It will also be used to forecast the Air Quality Index of the region using the Zhongli F1-AQI. The performance of the proposed system is evaluated using 5 different methods with and without imputation.
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References
A. D. Deshmukh and U. B. Shinde, “A low cost environment monitoring system using raspberry pi and arduino with zigbee,” in Inventive Computation Technologies (ICICT), International Conference on, vol. 3. IEEE, 2016, pp. 1–6.
H. Kumbhar, “Wireless sensor network using xbee on arduino platform: An experimental study,” in Computing Communication Control and automation (ICCUBEA), 2016 International Conference on. IEEE, 2016, pp. 1–5.
S. Santini, B. Ostermaier, and A. Vitaletti, “First experiences using wireless sensor networks for air pollution monitoring,” in Proceedings of the workshop on Real-world wireless sensor networks. ACM, 2008, pp. 61–65.
M. Mohan and A. Kandya, “An analysis of the annual and seasonal trends of air quality index of delhi,” Environmental monitoring and assessment, vol. 131, no. 1-3, pp. 267–277, 2007.
S. Karamchandani, A. Gonsalves, and D. Gupta, “Pervasive monitoring of carbon monoxide and methane using air quality prediction,” in Computing for Sustainable Global Development (INDIACom), 2016 3rd International Conference on. IEEE, 2016, pp. 2498–2502.
U. Z. Jovanovic, I. D. Jovanovic, A. Z. Petrusic, Z. M. Petrusic, and D. D. Mancic,
“Low-cost wireless dust monitoring system,” in Telecommunication in Modern Satellite, Cable and Broadcasting Services (TELSIKS), 2013 11th International Conference on, vol. 2. IEEE, 2013, pp. 635–638.
A. DAusilio, “Raspberry pi: A low-cost multipurpose lab equipment,” Behavior research methods, vol. 44, no. 2, pp. 305–313, 2012. 34
R. K. Kodali and A. Sahu, “An IoT based weather information prototype using wemos,” in Contemporary Computing and Informatics (IC3I), 2016 2nd International Conference on. IEEE, 2016, pp. 612–616.
Avhankar, M. S., Pawar, J., Singh, G., Asokan, A., Kaliappan, S., & Purohit, K. C. (2023, May). Simulation Environment for the I9 Vanet Platform. In 2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-8). IEEE.
Lambey, V., & Prasad, A. D. (2021). A review on air quality measurement using an unmanned aerial vehicle. Water, Air, & Soil Pollution, 232, 1-32.
Avhankar, M. S., Pawar, J., & Byagar, S. (2022, December). Localization Algorithms in Wireless Sensor Networks: Classification, Case Studies and Evaluation Frameworks. In 2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT) (pp. 01-07). IEEE.
Camarillo-Escobedo, R., Flores, J. L., Marin-Montoya, P., García-Torales, G., & Camarillo-Escobedo, J. M. (2022). Smart multi-sensor system for remote air quality monitoring using unmanned aerial vehicle and LoRaWAN. Sensors, 22(5), 1706.