Smart Waste Segregation Monitoring System Using Computer Vision for Community Waste Management

Abstract

Proper waste segregation is an important part of effective solid waste management, but manual monitoring can be time-consuming and inconsistent. This study presents the development of a web-based smart waste segregation monitoring system that uses computer vision to assist in identifying and classifying common types of waste. The system allows users to upload or capture images of waste materials, which are analyzed and categorized into appropriate waste classifications such as biodegradable, recyclable, residual, and special waste. The system also provides monitoring and reporting features that allow administrators to track classification records and generate summarized reports. The proposed system was developed using an iterative software development methodology and evaluated based on functionality, usability, accuracy, performance efficiency, and reliability. The system aims to support communities and organizations in improving waste segregation practices through an accessible and technology-assisted monitoring platform.

Keywords: waste segregation, computer vision, artificial intelligence, waste classification, environmental management, web-based system

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