Jinxiang Pei

Keqi Wang, Wei Xie, Wencen Wu et al.

After being legalized as an agricultural commodity by the 2018 U.S. Farm Bill, the Industrial Hemp production is moved from limited pilot programs to a regulated agriculture production system, and the market keeps increasing since then. However, Industrial Hemp Supply Chain (IHSC) faces several critical challenges, including high complexity and variability, data tampering, and lack of immutable information tracking system. In this paper, we develop a blockchain enabled internet-of-things (IoT) platform for IHSC to support process tracking, scalability, interoperability, and risk management. Basically, we create a two-layer blockchain with proof-of-authority based smart contract, which can leverage local authorities with state/federal regulators to ensure and accelerate quality control verification and regulatory compliance. Then, we develop a user-friendly mobile app so that each participant can use 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. Our study indicates the proposed platform can support interoperability, improve the efficiency of quality control verification, and ensure the safety of regulated IHSC.

Keqi Wang, Wei Xie, Wencen Wu et al.

With the passage of the 2018 U.S. Farm Bill, Industrial Hemp production is moved from limited pilot programs to a regulated agriculture production system. However, Industrial Hemp Supply Chain (IHSC) faces critical challenges, including: high complexity and variability, very limited production knowledge, lack of data and information tracking. In this paper, we propose blockchain-enabled IHSC and develop a preliminary simulation-based digital twin for this distributed cyber-physical system (CPS) to support the process learning and risk management. Basically, we develop a two-layer blockchain with proof of authority smart contract, which can track the data and key information, improve the supply chain transparency, and leverage local authorities and state regulators to ensure the quality control verification. Then, we introduce a stochastic simulation-based digital twin for IHSC risk management, which can characterize the process spatial-temporal causal interdependencies and dynamic evolution to guide risk control and decision making. Our empirical study demonstrates the promising performance of proposed platform.