Optimizing Municipal Solid Waste Collection Using Smart Bins - A Case Study in United Arab Emirates

The inefficient static municipal solid waste collection (MSWC) routes pose challenges in urban waste management, resulting in high costs, fuel consumption, and emissions. Smart bins equipped with Internet-of-Things (IoT) technology enable real-time waste monitoring, reducing overflow and inefficiencies in waste management. In this study, further improvements are achieved by assuming the collection problem as a Travelling Salesman Problem (TSP) and optimizing the collection routes using a TSP solution algorithm and the Nearest Neighbor (NN) method. The objective of this paper is to determine the efficiency of implementing IoT in waste bins for MSWC routes for better waste collection. Integrating smart bins into MSWC enhances route optimization, yielding significant operational and environmental benefits. Through a simulation model developed in AnyLogic, the study demonstrates that integrating smart bins into MSWC routes can achieve significant reductions in travel distance and carbon emissions, underscoring the significant operational and environmental benefits of IoT-based waste management systems over traditional approaches. The novelty of this work lies in its innovative integration of Internet-of-Things (IoT) technology into municipal solid waste collection, utilizing a Travelling Salesman Problem (TSP) framework to optimize collection routes. This approach not only enhances real-time monitoring and efficiency but also significantly reduces operational costs and environmental impact, setting a new benchmark for smart waste management solutions.