A smart municipal waste management system for route optimization and improved revenue collection

Abstract

Efficient municipal waste management is a critical challenge faced by cities globally, including Kampala. This study presents a case study where we propose a smart municipal waste management system that utilizes advanced technologies to address the specific challenges of route optimization and revenue collection. By integrating data analytics, Internet of Things (IoT) devices, and intelligent algorithms, the system aims to optimize waste collection routes and enhance revenue collection process. To solve the problem of route optimization, the system leverages data analytics techniques to analyze waste generation patterns taking into account factors such as waste disposal behaviors, and geographical information such as real time traffic data. By utilizing this data, the system intelligently determines the most efficient collection routes, reducing travel distances and optimizing resource allocation. This approach not only lowers operational costs but also minimizes the environmental impact associated with waste collection activities. In terms of revenue collection, the smart system incorporates IoT devices, such as smart bins equipped with sensors and communication capabilities. These devices provide real-time data on bin fill levels, enabling accurate and timely billing for waste collection services. The intelligent algorithms are integrated to detect anomalies in revenue collection, facilitating effective enforcement and revenue recovery processes. Over a two-month period, our study aims to implement and evaluate the proposed smart municipal waste management system. We gathered relevant data, including waste generation patterns, waste disposal behaviors, and revenue collection records. The system's performance was assessed based on key metrics, such as route optimization efficiency, revenue collection accuracy, and customer satisfaction. Expected results of this study included improved route optimization which was achieved at a percentage of approximately 60% leading to reduced travel distances and optimized resource allocation tailored to waste management needs. This results in cost savings for waste management authorities and a reduced environmental impact. Moreover, the implementation of the smart system is anticipated to enhance revenue collection by enabling accurate and efficient billing for waste collection services.