Blockchain Enabled Supply Chain using Machine Learning for Secure Cargo Tracking
Keywords:
BC Technology, Supply Chain Management, Cargo Tracking System, Mask RCNN, Smart Contract, Object and bar code detectionAbstract
Blockchain (BC) technology is becoming popular in the current trend search. In case of high security, it enables the decentralized network and anyone can interact with each other without intermediate lack of security. Globally, a considerable amount of commercial goods are transferred. The challenge in modern society is how to successfully transport cargo to safe destinations. The transport of imports is carried out based on the monitoring from the origin to the end, which makes it difficult to report the condition of the product and the quantity discrepancies in the existing system. To accomplish efficient crypto freight transportation, the proposed Mask Recurrent Convolutional Neural Network and Merkle Tree (MRCNN-MT) method in Supply Chain Management (SCM) address the problems in the existing system with a constant surveillance organization and decentralized product retention. Machine Learning (ML) is included in solving the problems faced by BC Technology in this cyber world. ML and Blockchain (BC) technology together have the potential to deliver very effective and beneficial results. The blink application is used to produce warning messages, and continuous monitoring to produce higher performance with the minimal human intrusion. Create secure folders in suspicious products using SCM in the proposed system. Information is secured by encryption using decentralized applications when running programs using synchronized registry entries to preserve network storage.
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