WASTE AND SANITATION MANAGEMENT SYSTEM WITH AI-ASSISTED SCHEDULING AND ISSUES REPORTING

Abstract

Effective waste and sanitation management is essential for protecting public health, preserving the environment, and maintaining the well-being of urban communities. As cities grow and population density increases, the challenges of managing waste collection, disposal, and sanitation services become more complex and resource-intensive. Traditional systems often suffer from issues such as inconsistent collection schedules, missed pickups, overflowing bins, and slow responses to reported problems. These challenges are worsened by a limited workforce, aging infrastructure, and the rising volume of waste produced each day. The AI-assisted Waste and Sanitation Management System was developed through a systematic process that combined elements of software engineering, artificial intelligence, user-centered design, and system integration. This section details the essential components, development procedures, and evaluation methods applied throughout the system’s design and implementation phases. The AI-assisted Waste and Sanitation Management System was assessed for its ability to enhance scheduling accuracy, efficiently address reported issues, and boost overall service performance. The findings presented are based on a 30-day period of simulation and field testing conducted in collaboration with a local barangay waste management unit. Incorporating artificial intelligence into waste and sanitation management offers a promising shift in how urban services are delivered. This study's findings reveal that AI-assisted scheduling and real-time issue tracking significantly enhance efficiency, responsiveness, and citizen participation. Nonetheless, a thorough evaluation of system implementation and performance is essential to understand its broader impact and potential for large-scale adoption.