Abstract:

Plastic waste, especially in urban environments and water bodies, poses a significant environmental threat. This paper presents a browser-based object detection system for identifying and isolating plastic bottles using state-of-the-art machine learning models. The system leverages TensorFlow.js, ML5.js, and P5.js libraries along with the COCO-SSD model to detect plastic bottles in real time using a mobile camera interface. By employing a browser-based architecture, the system offers cross-platform functionality, eliminating the need for server-based computations or specialized hardware. Experimental evaluation showed high detection accuracy across various environments, underscoring the potential for real-world applications in waste management and recycling efforts.