UrbanGreen - E-Waste Detection and Analysis using YOLOv5

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Date

2025

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Institute of Electrical and Electronics Engineers Inc.

Abstract

E-waste has become a global concern that challenges environmental sustain ability. The disposal of electronic devices is often poorly managed, especially in urban areas. This research aims to develop an innovative e-waste management system suitable for urban areas, focusing on accurately identifying electronic devices and their harmful components through advanced image processing techniques. (Y olov5) The system identifies various electronic devices, harmful components and materials and assesses their recyclability, improper disposal's environmental and health impacts, empowering users to make informed decisions about disposal and recycling. The system will integrate tools to identify E-waste, promote the reuse of electronic devices, educate the public through interactive educational platforms, and locate nearby e-waste collection centers. By addressing these critical aspects of e-waste management, the project aims to provide a useful platform to manage e-waste effectively in urban areas. This paper was developed to discuss E-waste detection and analysis using YOLOv5 object detection model.

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Keywords

Computer vision, E-waste, E-waste classification, E-waste management, Environment sustainability, Image annotation, Image processing, Impact analysis, Machine learning, Object detection, Waste management, YOLO object detection

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