Abstract
Smart waste management systems (SWMS), including various technologies, including routing, scheduling, infrastructure, and the Internet of Things (IoT), are used to enhance the efficiency and automation of waste management processes. The availability of big data generated by IoT sensors has the potential to significantly improve waste management systems by providing valuable insights and enabling automation. This study presents a data analytics framework that supports decision-makers in implementing, monitoring, and optimising SWMS. The framework utilises IoT sensor data and employs data analytic techniques to analyse and predict municipal bins’ waste generation trends and patterns. Finally, the framework demonstrates the capability to forecast waste generation, leading to the development of a sustainable environment and efficient managerial administration in waste management.
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Ahmed, S., Mubarak, S., Wibowo, S., Tina Du, J. (2023). Data Analytics Framework for Smart Waste Management Optimisation: A Key to Sustainable Future for Councils and Communities. In: Strauss, C., Amagasa, T., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2023. Lecture Notes in Computer Science, vol 14147. Springer, Cham. https://doi.org/10.1007/978-3-031-39821-6_11
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DOI: https://doi.org/10.1007/978-3-031-39821-6_11
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