Resource Recovery and Circular Economy Approaches in Industrial Waste Management: Current Developments and Future Perspectives

The rapid growth of manufacturing industries has increased the need for intelligent and sustainable industrial waste management systems. This research presents the design and development of an AI- and IoT-based smart industrial waste monitoring system for real-time monitoring, data acquisition, and intelligent decision-making. The proposed system integrates smart sensors, an ESP32-based controller, cloud computing, and machine learning algorithms to continuously monitor waste-related parameters and classify waste efficiently. Experimental evaluation demonstrates reliable sensor performance, stable cloud communication, accurate waste classification, and effective dashboard visualization for remote monitoring. Statistical analysis and validation confirm the robustness and consistency of the developed system. The proposed framework supports improved resource recovery, reduced environmental impacts, and enhanced operational efficiency, contributing to sustainable manufacturing and circular economy practices. The developed system provides a scalable and cost-effective solution for future smart industrial waste management applications.