Optimising unplanned waste collection: An IoT-enabled system for smart cities, a case study in Tangier, Morocco

An innovative approach to the collection of unplanned municipal waste through the integration of an Internet of Things (IoT) enabled system in urban settings is presented. Despite significant strides in waste management optimisation, traditional systems have largely overlooked the management of occasional or seasonal waste such as green waste, wild dump, and construction debris. The authors seek to address this gap by deploying an IoT-enabled system to optimise resource utilisation and efficiency. Building on existing infrastructures for real-time tracking of waste collection circuits, equipment, and bin filling levels, the system incorporates an additional module to manage unpredictable waste categories. The system collects field data leveraging existing resources with minimal investment. To manage the sporadic nature of these waste types, the system employs a flexible approach with the use of sensors and algorithms for dynamic route planning and waste collection. Using the city of Tangier, Morocco, as a case study, a comprehensive methodology for waste location capture, GIS mapping, priority-based route identification, scenario testing, and operational cost estimation is implemented. A modified version of the Contraction Hierarchies algorithm is applied to compute optimal waste collection paths, ensuring timely and efficient waste removal while minimising environmental impact. The findings from this research promise significant implications for municipal waste collection, particularly in developing countries, opening new possibilities for sustainable waste management practices in smart cities. An innovative Internet of Things enabled system is introduced for managing unplanned municipal waste, like green waste and construction debris, by optimising resource utilisation and efficiency. The system, implemented in Tangier, Morocco, expands upon existing waste tracking infrastructure, using sensors and dynamic route planning algorithms to handle sporadic waste types effectively. The outcome of this research shows potential for significant improvements in municipal waste management, particularly in developing countries, thereby promoting sustainable waste management practices in smart cities.image