Smart Urban Waste Management System Powered by AI and IoT for Efficient Collection, Segregation, and Disposal

Urban waste management systems often suffer from static collection schedules, inadequate segregation, and limited transparency, leading to resource wastage and environmental degradation. This study proposes an integrated innovative waste management framework powered by the Internet of Things (IoT), Artificial Intelligence (AI), and blockchain technologies to address these challenges. The system employs IoT-enabled smart bins with sensors to monitor real-time waste accumulation, environmental conditions, and location data. AI algorithms analyze this data to optimize collection routes, predict waste generation, and perform automated waste categorization, thereby reducing operational costs and improving recycling rates. Blockchain technology is incorporated to ensure secure, tamper-proof waste tracking throughout its lifecycle, enhancing accountability and preventing illegal dumping. The communication between system components is facilitated using energy-efficient protocols such as LoRaWAN and NB-IoT, enabling scalable deployment in diverse urban settings. Experimental evaluations and case studies from major cities demonstrate significant improvements in waste collection efficiency, energy usage, and citizen engagement. The proposed model supports circular economy practices and sustainable urban development by promoting real-time monitoring, data-driven decision-making, and resource optimization. This work highlights the potential of emerging technologies in transforming conventional waste management systems into adaptive, transparent, and environmentally responsible infrastructures for smart cities.