Replay Engineering: A Sustainable Approach to Circular Re-source Utilization and Climate Resilience

Replay Engineering is introduced as an interdisciplinary framework that redefines waste as a strategic resource, integrating AI, IoT, and blockchain to enhance circularity, climate resilience, and social equity. This study reviews global challenges in conventional recycling systems—such as low recovery rates, high energy consumption, and lack of transparency—and proposes Replay Engineering as a holistic alternative. Methodologically, the research synthesizes case studies and lifecycle assessment data, supported by machine learning models like ResNet and SVM, achieving over 90% ac-curacy in waste classification. OpenLCA tools are applied to assess environmental impacts, while ROI modeling and market forecasts quantify economic potential. Results show that Replay Engineering can reduce CO₂ emissions by up to 45%, increase material recovery by 40%, and lower operational costs by 20%. Applications span e-waste management, vehicle remanufacturing, and resource redistribution during disasters. The framework aligns with UN SDGs and the EU Circular Economy Action Plan, offering a scalable solution for sustainable development. This study concludes that Replay Engineering not only enhances environmental and economic outcomes but also addresses global disparities through ethical redistribution and policy integration. Future research should explore behavioral incentives, AI-driven logistics, and ESG-oriented policy adoption to accelerate implementation at scale.