Leveraging Artificial Intelligence for Efficient Waste Management in Smart Cities

Abstract The increasing global waste generation has increased the challenges associated to pollution, waste management, and recycling, necessitating innovative strategies like the application of artificial intelligence (AI). This research highlights the diverse applications of AI in waste-to-energy processes, smart bins, waste-sorting robots, waste generation modeling, monitoring and tracking systems, plastic pyrolysis, distinguishing fossil and modern materials, logistics optimization, illegal dumping prevention, resource recovery, smart city development, process efficiency, cost reduction, and public health improvement. AI integration in waste logistics can reduce transportation distances by up to 36.8%, costs by 13.35%, and time by 28.22%. Furthermore, AI-enabled systems achieve waste identification and sorting accuracies between 72.8% and 99.95%. Combining AI with chemical analysis enhances waste pyrolysis, carbon emission estimation, and energy conversion. This paper also explores how AI can improve efficiency and reduce costs in waste management systems, making them more effective for smart city ecosystems.