Collaborative supervision of dangerous goods supply chain: A blockchain-based conceptual platform

Abstract

Effective supervision and the prevention of concealment and false reporting in dangerous supply chain goods require collaboration among multiple departments. Because of its decentralized consensus mechanism, blockchain has potential as an efficient tool for the collaborative supervision of dangerous goods supply chains. In this study, a blockchain-based conceptual platform was proposed for the supervision of dangerous goods supply chains. It features multiple layers, namely, blockchain, storage, interaction, and interface, each fulfilling distinct roles to ensure a comprehensive and efficient system. To enable efficient on-chain data sharing of diverse types of data, three modes of on-chain data integration leveraging IPFS (InterPlanetary File System) and FISCO BCOS were implemented. Additionally, a traceable state machine was proposed, which uses smart contracts to facilitate the traceability of the supervision process. The feasibility of the conceptual platform was validated through the deployment of a prototype platform with eight blockchain nodes. The results indicate that the platform has a latency of 500–550 ms and approximately 2 TPS (Transactions Per Second) to complete data sharing. It also has a latency of less than 3 s and more than 1 TPS when carrying out complex supervision process tracing. The proposed conceptual platform has the ability to address data silo issues in the dangerous goods supply chain. Moreover, the traceability of the supervision process enhances the accurate tracing of accident liabilities.