Islam, AfridaAl Araf, Md. HaminSiddique, Yasir AnafRahman, Md. Mosaddequr2026-08-112026-08-112026-01-01A. Islam, M. H. Al Araf, Y. A. Siddique and M. M. Rahman, "A Real Time Smart Waste Management System," 2026 IEEE 2nd International Conference on Quantum Photonics, Artificial Intelligence & Networking (QPAIN), Chittagong, Bangladesh, 2026, pp. 1-4, doi: 10.1109/QPAIN69676.2026.11545725.97983315499092-s2.0-105042923124https://hdl.handle.net/10361/28909Waste management is one of the most serious issues of contemporary campuses and urban areas that may lead to an unsanitary environment, resource wastage, and environmental damage. This project introduces the design and implementation of an intelligent waste management system, which combines the use of IoT sensors, machine learning, and cloud-based monitoring. The considered system includes, a low-cost sensor-based design and a machine learning design with a Raspberry Pi and YOLOv8n classifier. With 92% classification accuracy, consistent hazard detection, and real-time monitoring, this model proved versatile. The system minimizes the number of trips to collection, promotes recycling, and allows responsible user behavior by a reward system. In keeping with the global sustainability objectives, the project will provide a replicable and scalable model of cleaner, smarter, and more sustainable communities.4 pagesen-USfalseClassificationMachine learningSustainabilityWaste managementYOLOMachine learning.Sustainable development.Refuse and refuse disposal.Factory and trade waste.Conference Proceeding10.1109/QPAIN69676.2026.11545725