Browser-Based Object Detection System for Isolating Plastic Bottles using the COCO-SSD Model.

Publication Date: 02/10/2024

DOI: 10.52589/BJCNIT-IT17PWUT


Author(s): Chidozie Managwu, Ibrahim Kushchu, Daniel Matthias.

Volume/Issue: Volume 7 , Issue 4 (2024)



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.


No. of Downloads: 0

View: 119




This article is published under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
CC BY-NC-ND 4.0