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Knowing the challenges of keeping and manipulating more and more immutable transaction records in a blockchain network of various supply chain parties and the opportunities of leveraging sophisticated analyses on the big data generated from these records, design of a robust blockchain architecture based on a cloud infrastructure is proposed. This paper presents this technical design with consideration of the technical sustainability in terms of scalability and big data processing and analytics. A case study was used to illustrate how the technical sustainability is achieved by applying the proposed technical design to the real-time detection of the maritime risk management. This case also illustrates how machine learning mechanism helps to reduce maritime risk by guiding a cargo ship to adjust to the planned or safe route from a detour to a danger zone. This paper also discusses the implications for further research direction.
Simon Wong; John-Kun-Woon Yeung; Yui-Yip Lau; Joseph So. Technical Sustainability of Cloud-Based Blockchain Integrated with Machine Learning for Supply Chain Management. Sustainability 2021, 13, 8270 .
AMA StyleSimon Wong, John-Kun-Woon Yeung, Yui-Yip Lau, Joseph So. Technical Sustainability of Cloud-Based Blockchain Integrated with Machine Learning for Supply Chain Management. Sustainability. 2021; 13 (15):8270.
Chicago/Turabian StyleSimon Wong; John-Kun-Woon Yeung; Yui-Yip Lau; Joseph So. 2021. "Technical Sustainability of Cloud-Based Blockchain Integrated with Machine Learning for Supply Chain Management." Sustainability 13, no. 15: 8270.