An Intelligent Sorting and Decision-Making Platform for Express Packaging Waste Utilizing Computer Vision
Keywords:
AI-driven, Express packaging waste recycling, Technical architecture, Process reengineering, Operating mechanismAbstract
This paper explores the transformative application of artificial intelligence (AI) in the domain of express packaging waste recycling, presenting a comprehensive analysis of an AI-driven technical architecture. The architecture integrates key technologies such as intelligent identification and classification, dynamic path optimization and scheduling, and data-driven prediction and decision-making. These technologies enable precise sorting of waste materials, efficient logistics planning, and proactive resource allocation, significantly enhancing operational efficiency. Furthermore, the paper elaborates on AI-empowered recycling process reengineering, which includes expanding the recycling capabilities of intelligent express lockers, establishing automated sorting and processing centers, and implementing blockchain-based traceability and credit systems. These innovations streamline waste collection, reduce manual intervention, and ensure transparency in recycling processes. In addition, the paper examines the operation mechanism of the AI-driven recycling system, focusing on the design of multi-party collaborative incentive mechanisms, dynamic pricing and market regulation, and risk early warning and emergency response systems. By fostering collaboration among stakeholders, adjusting pricing based on real-time demand, and mitigating potential risks, the system promotes sustainable resource management. Through these advancements, AI not only revolutionizes express packaging waste recycling by improving efficiency and reducing costs but also contributes to environmental sustainability by minimizing waste and optimizing resource utilization.
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Copyright (c) 2025 Chong Wei
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