Tamás Bányai – Sajid Nazir – Péter Veres
This paper explores the potential of Internet of Things (IoT) technologies, such as artificial intelligence (AI), big data analytics, and cloud computing in enhancing waste collection and processing operations. A short literature review is conducted to identify various applications of these technologies in optimizing waste management processes, including real-time data collection, automated monitoring, predictive maintenance, and dynamic route optimization. Based on these findings, a novel approach is proposed that integrates all stakeholders in the waste management value chain through a cloud-based waste management platform. This platform facilitates seamless data sharing and communication, enabling coordinated real-time decision-making and efficient resource allocation. The conceptual model developed in this study is used as a foundation for creating a mathematical model that supports real-time optimization of routing, scheduling, and assignment tasks for waste collection services. The model aims to dynamically adjust operations in response to changing conditions, such as waste volume fluctuations and traffic patterns. This optimization framework enhances key performance indicators (KPIs) by reducing operational costs, minimizing environmental impact through lower emissions, and improving service reliability and customer satisfaction. The proposed approach represents a significant advancement in smart waste management, driving sustainability and efficiency through the use of cutting-edge digital technologies.
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https://www.sciencedirect.com/science/article/pii/S2405896325007888?via%3Dihub