R. Anitha, A. Parthiban
• Proposed a six-layer smart waste framework aligned with Industry 5.0 principles • Integrated Digital Twin simulation for proactive routing and disruption resilience • Used inventory-based modeling to reduce overflow and optimize collection cycles • Mapped five waste streams to the full 9R circular economy hierarchy • Enabled scalable, human-centric waste systems for sustainable urban deployment Aligned with Industry 5.0 principles, this study introduces a next-generation smart waste ecosystem that prioritizes circularity, human-centricity, and operational resilience. The framework integrates Edge-AI smart bins, Digital Twin simulation, inventory-informed modeling, and graph-theoretic routing to optimize urban solid waste operations without relying on sensor-heavy deployments. Evaluated on a synthetic 10-node urban network under baseline, surge (+40%) and outage scenarios, the system reduced collection frequency by 15-20%, lowered fuel consumption by 12-18%, and eliminated node-level overflow events under simulated disruptions. Circularity integration via the 9R hierarchy improved material recovery rates by 25-30%, with plastics and e-waste showing the largest gains. Sensitivity analysis shows the framework remains robust under ±20% variations in fill rates and ±15% vehicle capacity changes. The proposed simulation-first, inventory-guided architecture offers municipalities a scalable pathway to resilient and circular waste systems, while reducing reliance on continuous connectivity. These findings support SDGs 11, 12 and 13 and lay the groundwork for pilot deployments and economic assessment in diverse urban contexts.