Browser-Based Object Detection System for Isolating Plastic Bottles using the COCO-SSD Model.
Publication Date: 02/10/2024
Author(s): Chidozie Managwu, Ibrahim Kushchu, Daniel Matthias.
Volume/Issue: Volume 7, Issue 4 (2024)
Page No: 1-7
Journal: British Journal of Computer, Networking and Information Technology (BJCNIT)
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.
Keywords:
Object Detection, Machine Learning, TensorFlow.js, COCO-SSD, Browser-based AI, Plastic Waste, Real-time Detection.
