Autopilot Eco Plane to Reduce Air Pollution
Nalagamage BuddishanDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri LankaAmalsha Thathsarani FernandoDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri LankaKaveesha Senuri LiyanageDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri LankaSanka DevindaDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri LankaNelum AmarasenaLecturer, Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri Lanka
Vol 7 No 11 (2023): Volume 7, Issue 11, November 2023 | Pages: 141-146
International Research Journal of Innovations in Engineering and Technology
OPEN ACCESS | Research Article | Published Date: 08-11-2023
doi.org/10.47001/IRJIET/2023.711020
Abstract
This research paper explores the concept of an autonomous drone, “Eco plane” as a potential solution to reduce air pollution caused by commercial aviation. This drone will be equipped with an air quality detector to identify areas with high pollution levels. It will fly over these areas while carrying a chemical solution to purify the air. Image processing techniques will be employed to detect and avoid obstacles, optimizing the plane's purifying capabilities. Real-time data on air quality and pollution levels will be collected and displayed on a mobile app dashboard, aiding in the monitoring of daily air purification progress. The collected data will also be analyzed to develop algorithms that predict the lifespan of individuals residing in polluted areas and determine when the environment becomes uninhabitable. Furthermore, this research will employ machine learning techniques to identify pollutants, providing valuable insights to policymakers for effective pollution reduction strategies.
Keywords
air pollution, source identification, machine learning, real-time and drone
Citation of this Article
Nalagamage Buddishan, Amalsha Thathsarani Fernando, Kaveesha Senuri Liyanage, Sanka Devinda, Nelum Amarasena, “Autopilot Eco Plane to Reduce Air Pollution” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 11, pp 141-146, November 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.711020
Licence
Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology
This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
References
- World Health Organization (WHO). (2018). Ambient (outdoor) air quality and health. Retrieved from https://www.who.int/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health
- S. Guo, X. Tao, and L. Liang, “Exploring Natural and Anthropogenic Drivers of PM 2.5 Concentrations Based on Random Forest Model: Beijing–Tianjin–Hebei Urban Agglomeration, China,” Atmosphere, vol.14, no. 2, p. 381, Feb. 2023, doi:https://doi.org/10.3390/atmos14020381.
- Saima Zafar, Ghosia Miraj, Raja Baloch, Danish Murtaza, Khadija Arshad, "An IoT Based Realtime Environmental Monitoring System using Arduino and Cloud service".
- Fotouhi, Azade & Ding, Ming & Hassan, Mahbub. (2017). Understanding autonomous drone maneuverability for Internet of Things applications. 1-6. 10.1109/WoWMoM.2017.7974336.
- Zheng, X., Ding, X., Li, G., Liu, J., Feng, Q., Wang, Q., Zhang, X., et al. (2019). A study of air pollution monitoring data for thirty-four provincial capital cities in China. International Journal of Environmental Research and Public Health, 16(17), 3079. doi:10.3390/ijerph16173079.
- C R, Aditya & Deshmukh, Chandana & K, Nayana & Praveen Gandhi Vidyavastu. (2018). Prediction of Air Pollution using Machine Learning Models. International Journal of Engineering Trends and Technology. 59. 204-207. 10.14445/22315381/IJETT-V59P238.
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