Title: An IoT-integrated adaptive waste management system for optimal route planning and enhanced sustainability

Authors: K.N. Pallavi; K.N. Rashmishree

Addresses: Department of Computer Science and Engineering, NMAM Institute of Technology, NITTE (Deemed to be University), Nitte, India ' CGS Green Sustainergy Pvt. Ltd., Chennai, India

Abstract: The rapid growth of urban populations has led to a significant increase in waste generation, making effective waste management a critical concern. As cities strive to enhance liveability and quality of life, efficient urban planning becomes essential. We propose a smart city-based IoT-integrated system for adaptive waste management. This system aims to improve fuel efficiency, reduce the time waste trucks take to reach designated intelligent bins, and optimise routes for energy efficiency. Experimental results demonstrate that MOAHA significantly outperforms established optimisation algorithms, such as the multi-objective salp swarm algorithm (MSSA), multi-objective simulated annealing (MOSA), and multi-objective whale optimisation algorithm (MOWOA), achieving up to 30% improvement in routing efficiency and energy savings.

Keywords: internet of things; IoT; waste bin; adaptive waste management; optimisation; smart city.

DOI: 10.1504/IJEWM.2025.149531

International Journal of Environment and Waste Management, 2025 Vol.38 No.3, pp.282 - 294

Received: 13 May 2024
Accepted: 04 Oct 2024
Published online: 05 Nov 2025 *

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