Sky Sweeper: A Drone Survelliance Model Using YOLOV8 and Jetson Nano for Plastic Waste Monitoring System

The recent statistics reveals that our country India produces 22 million tons of plastic every year. It has been noted that the inappropriate collection and segregation of plastic garbage makes its disposal a severe concern. The major issue with plastic trash in India is not about how much is produced, but rather inefficient waste management practices, such as ineffectual collection and recycling. The urgent need to address the mounting environmental issues caused by litter and garbage in outdoor spaces, particularly in places like beaches, is what spurred the development of a trash detection drone surveillance model. The drone surveillance model's particular objectives include Trash Detection. Real-time monitoring, Geo-location and mapping, Notifications and alert system, data integration and analysis, efficiency and Cost effectiveness. The proposed UAV surveillance model rightly locates the most plastic populated area through YOLOV8 (You Only Look Once) object detection algorithm and then the deep learning algorithm is applied on the captured data to explore the right location and the location report will be forwarded to the concern official through the digital notification by integrating the model with NVidia Jetson Nano Kit to assist in delegating the workforce to the appropriate location thereby utilizing the available manpower in an efficient way. Also results of the proposed model is compared with YOLOV5 implementation and existing Ensemble models where it is concluded that the proposed YOLOV8 model provides higher accuracy comparatively.