A Distributed Sensing Framework for Continuous Waste Status Analysis and Location-Guided Collection

Abstract

Urban waste mismanagement remains a critical public health concern, particularly in densely populated market areas where delayed garbage collection can increase the risk of disease outbreaks such as cholera, especially during the rainy season. This issue is largely attributed to the absence of an efficient monitoring mechanism that informs municipal authorities about the real-time status of waste bins. To address this challenge, this project presents an intelligent waste monitoring and collection system that integrates Internet of Things (IoT) technology with Global Positioning System (GPS) capabilities. The proposed system continuously tracks the fill level of garbage bins using embedded sensors and transmits this information to a centralized IoT server. Alongside filllevel data, the system also provides precise geographic location details of each bin through GPS integration. This enables waste management personnel to identify which bins require immediate attention without the need for manual inspection. Automated alerts are generated when bins reach critical capacity, ensuring that collection activities are carried out in a timely manner. Furthermore, the availability of real-time data supports route optimization for garbage collection vehicles, thereby reducing fuel consumption, operational costs, and environmental impact. By enabling data-driven decision-making, the system enhances overall efficiency in municipal waste management operations. Ultimately, this solution not only minimizes the risk of overflow and associated health hazards but also contributes to cleaner and more sustainable urban environments through improved waste collection practices.