Abstract:

[Purpose] Addressing challenges such as difficult fine-grained classification and low traceability credibility in material identification from the inventory scenarios of logistics food supply chain, this paper proposes an innovative technical framework integrating lightweight multimodal distillation and blockchain traceability. Built-in business constraints assist in improving the fine-grained classification and recognition of food materials, ensuring compliance of related businesses through reliable traceability of data such as material images, purchase orders, and supplier contracts, providing reference for the digital transformation of the smart logistics food supply chain. [Methods] Different from traditional multimodal recognition, this technical framework breaks through limitations and constructs a dynamic distillation framework with cross-modal attention alignment. The semantic constraints of the procurement ledger are embedded in the YOLOv7 tiny improved model. Through the triple feature fusion of visual, weighing, and business rules, food material recognition in partially occluded scenes is achieved. Further improvement of the dual chain blockchain technology framework and optimization of the smart contracts through federated learning achieve rapid traceability verification of food weighing images, forming a technical loop of "precise recognition, dynamic optimization, and trusted traceability". [Results] This work effectively improves the accuracy of food ingredient identification, ensures data tamper resistance and system stability, reduces procurement deviation, and meets the requirements of food safety and quality control. [Limitations] There are certain specific requirements for the deployment environment, and further experiments will be conducted in follow-on research to propose feasible solutions. [Conclusions] This work provides a replicable new paradigm for smart logistics supply chain using blockchain and artificial intelligence applications. It is expected to be promoted in state-owned enterprises, effectively reducing the cost of yearly loss and improving logistics procurement precision, reliability, quality and efficiency.

Key words: smart supply chain, smart AI cloud scale, lightweighting, knowledge distillation, blockchain traceability