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Title: Technical sustainability of cloud-based blockchain integrated with machine learning for supply chain management
Authors: Wong, S 
Yeung, JKW
Lau, YY 
So, J 
Issue Date: Aug-2021
Source: Sustainability, Aug. 2021, v. 13, no. 15, 8270
Abstract: 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.
Keywords: Blockchain
Cloud infrastructure
Data analytics
Machine learning
Supply chain
Technical sustainability
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Sustainability 
EISSN: 2071-1050
DOI: 10.3390/su13158270
Rights: © 2021 by the authors.Licensee MDPI, Basel, Switzerland.This article is an open access articledistributed under the terms andconditions of the Creative CommonsAttribution (CC BY) license (
The following publication Wong, S.; Yeung, J.-K.-W.;Lau, Y.-Y.; So, J. TechnicalSustainability of Cloud-BasedBlockchain Integrated with MachineLearning for Supply ChainManagement. Sustainability 2021, 13,8270 is available at
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