International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Design and Implementation of an Intelligent Edge-IoT Based Waste Segregation System for Urban Residential Complexes

Author(s) Dr. Kailash Pati Dutta, Mr. Ankit Kumar Sahu, Mr. Raj Kumar Vishwakarma, Mr. Ranjan Raj
Country India
Abstract Urban residential complexes are experiencing severe challenges in managing the continuously increasing volume of municipal solid waste, which often contains a heterogeneous mix of biodegradable, recyclable, and hazardous materials. Traditional collection and manual segregation processes are slow, error-prone and lead to significant environmental deterioration. With the rapid advancements in Internet of Things (IoT), edge computing, and machine learning, the possibility of performing real-time waste classification directly at the point of generation has emerged as a sustainable and scalable solution. In this study, an intelligent edge-IoT based waste segregation system is designed and implemented for urban residential environments, enabling rapid, accurate, and autonomous sorting with minimal human intervention. Leveraging deep learning-based visual recognition, lightweight edge inference, and sensor-driven decision mechanisms, the system enhances operational efficiency while reducing computational latency typically associated with cloud-centric frameworks. Analytical experimentation validates notable improvements over conventional systems in terms of classification accuracy, responsiveness, and deployment feasibility. The proposed system demonstrates strong potential for smart-city waste governance and establishes a robust foundation for circular-economy practices.
Keywords Edge Computing, Internet of Things (IoT), Waste Segregation, Deep Learning, Smart Cities, Image Classification
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-12
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.63175
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E-ISSN 2582-2160
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