ZeroX Waste

The rapid growth of urbanization has significantly increased the volume of waste generated in cities, creating major challenges for municipal authorities in effective waste management and complaint resolution. This paper presents “ZeroX Waste,” a smart waste management system designed to streamline waste reporting, monitoring, and resolution using modern web technologies and artificial intelligence. The proposed system is developed using the MERN stack (MongoDB, Express.js, React.js, Node.js) and integrates AI-based image classification and sentiment analysis to automatically identify waste types and prioritize complaints. Users can upload images, videos, and location data of waste, which are processed in real time. The system utilizes Groq’s LLaMA-based models for classification and analysis, while Leaflet API with OpenStreetMap enables accurate GPS tracking and interactive visualization. A real-time dashboard is implemented for municipal authorities and sanitation workers to manage tasks efficiently, ensuring faster response and better coordination. The experimental results demonstrate a structured digital workflow and an improvement of approximately 35–40% in complaint tracking and resolution efficiency compared to traditional manual systems. The proposed solution contributes to smart city development by enhancing transparency, citizen participation, and operational efficiency in urban sanitation management. It provides a scalable and intelligent approach for modern waste management chall enges.