Journal of Blockchain Research

Volume 1 (2022)

Number 1

Blockchain-enabled IoT platform for end-to-end supply chain risk management

Pages: 1 – 17

DOI: https://dx.doi.org/10.4310/JBR.2022.v1.n1.a1

Authors

Keqi Wang (Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts, U.S.A.)

Wei Xie (Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts, U.S.A.)

Wencen Wu (Department of Computer Engineering, San Jose State University, San Jose, California, U.S.A.)

Jinxiang Pei (Mechanical and Industrial Engineering, Northeastern University, Boston, Massachusetts, U.S.A.)

Qi Zhou (QuarkChain Inc., San Mateo, California, U.S.A.)

Abstract

Driven by the critical challenges of Industrial Hemp Supply Chain (IHSC), including high complexity and variability, data tampering, and lack of an immutable information tracking system, we develop a blockchain-enabled IoT platform to support process tracking, scalability, interoperability, and risk management. Built on parallel processing and state-sharding technology, we develop a two-layer blockchain with proof-of-authority based smart contracts and a hierarchical automatic verification system, which can leverage the distributed resources from local authorities with state/federal regulators, accelerate quality control verification, and ensure regulatory compliance and data integrity. Then, we create a blockchain-enabled IoT platform with user-friendly mobile app so that each participant can use a smart phone to real-time collect and upload their data to the cloud, and further share the process verification and tracking information through the blockchain network. The proposed platform can support interoperability and traceability, and improve end-to-end supply chain safety, throughput, efficiency, and transparency. It can be extended to general biopharmaceuticals, agriculture and food supply chains.

Keywords

blockchain, end-to-end supply chain risk management, safety regulation, Internet-of-Things (IoT), state sharding, parallel processing

Full Text (PDF format)

Received 9 December 2021

Accepted 14 May 2022

Published 13 October 2022