• ARJUN P UNNI
• ALIMON N A
• GOWRI M
• SUDHI KRISHNA N A
• STEFFY LIVERA

The growing demand for plastic in India highlights the necessity of shifting towards sustainable approaches to tackle the mounting waste and pollution challenges. However, the manual collection and segregation of waste present substantial obstacles, impeding the efficacy of waste management endeavours. To address this, our project proposes the development of an advanced waste segregation system leveraging YOLOv8-based object detection technology for real-time identification and classification of diverse waste items. By accurately discerning recyclables, non-recyclables, and other waste types, our system enhances waste management efficacy. Integrated with ByteTrack for multi-object tracking, our solution ensures precise waste detection and continuous monitoring of waste movement dynamics. Moreover, employing a Delta arm equipped with a suction pump facilitates efficient pick and place operations, optimizing waste segregation processes. The Delta arm’s parallel-linkage structure promises swift and accurate movements that can accommodate a wide range of waste types and sizes, ensuring adaptability throughout the segregation process. Our innovative approach promises to revolutionize waste management practices, fostering sustainable solutions for India's burgeoning plastic consumption.

Waste Segregation, Object Detection, Computer Vision, Deep learning, YOLOv8, Delta arm

"Waste Segregation using YOLO v8 based Object Detection and Robotics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.o591-o595, April-2024, Available :http://www.jetir.org/papers/JETIR2404F83.pdf

"Waste Segregation using YOLO v8 based Object Detection and Robotics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppo591-o595, April-2024, Available at : http://www.jetir.org/papers/JETIR2404F83.pdf