Date of Award
Doctor of Philosophy (PhD)
Computer Engineering and Sciences
Waste collection is a critical component of the municipal service to the community within urban set-ups. Increasing levels of waste generation present significant challenges in urban areas due to unprecedented population growth. Consequently, due to the accumulating amounts of waste, waste management has become a primary concern. Several problems also emanate from the current inadequate and inefficient waste management systems that rely on non-scientific techniques. This paper proposes using IoT-based smart bins to improve the waste management process by optimizing waste collection. Al-Awali District in the Saudi Arabian city of Mecca will be the main focus of this study, where the efficiency of operating the intelligent bins technology will be assessed. The smart bins have sensors that apply IoT technology to monitor, in real-time, the fill levels of waste in garbage bins. The data is then communicated wirelessly and stored in a cloud-based IoT backend system that provides the collected information and the exact location of the garbage containers. Once the bins report their state, the most optimal route for the dynamic vehicle routing problem is established by utilizing metaheuristic algorithms such as the Tabu search algorithm. Relevant personnel, such as garbage truck drivers, can easily access information about the waste bins' conditions and the most efficient routes to follow using user-friendly mobile applications. The development and implementation of the smart bins' model and the waste management mobile application show that the suggested system can improve the efficiency of waste management exercises in cities and save financial and physical resources. The significant benefit of the intelligent bins technology is to collect and disseminate information on waste material in time to prevent the overflow of garbage bins, thereby assisting in mitigating environmental pollution.
Alwabli, Abdullah Suliman, "Dynamic Route Optimization for Waste Collection in Smart City" (2021). Theses and Dissertations. 883.