Role of Blockchain Technology and Machine Learning in Design of Smart and Secure Warehouse Management System: A Survey
##plugins.themes.academic_pro.article.main##
Abstract
Blockchain network is defined as interconnection of many computers, and each and every computer holds the copy of the ledger. It can be observed as continuously budding chain of blocks, and blocks are interconnected with the support of hash function. Validating of new blocks is followed by a set of protocols and consensus mechanism from every node in the network. The records are kept and arranged in linear fashion chain. The main feature of the Blockchain technology is that it allows secure communication between untrusted parties without the involvement of any third party authority. Artificial intelligence, which emulates the human intelligence, is impacting heavily on the business and social media applications nowadays. Machine learning which is the subset AI, automatically learns and improve based on input data. Whereas deep learning which is subset of machine learning uses networks to identify complex patterns in data. The basic approach of machine learning is to collect and analyze the data at central location like server. But in today’s scenario the data is decentralized and emerges from multiple sources. Hence the need of distributed machine learning algorithms in many applications is required. ML can be used to make chain smarter than before. By making use of decentralized data architecture of Blockchain we can build good models of machine learning. This paper investigates the possibility of integrating Blockchain Technology and Machine learning for optimization and improvement of Warehouse operations at data and transactions levels by providing security processes needed for smart and secure warehouse system.
##plugins.themes.academic_pro.article.details##
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
- SUDEEP TANWAR, QASIM BHATIA, PRUTHVI PATEL, APARNA KUMARI, PRADEEP KUMAR SINGH, WEI-CHIANG HONG,” Machine Learning adoption in Blockchain-based Smart Applications: The Challenges, and a way forward”, published in IEEE Access Vol. 8, 2019. DOI: https://doi.org/10.1109/ACCESS.2019.2961372
- N. Chandrasekaran, Radhakhrishna Somanah, Dhirajsing Rughoo, Raj Kumar Dreepaul, Tyagaraja S.
- Modelly Cunden and Mangeshkumar Demkah, “Digital Transformation from Leveraging Blockchain
- Technology, Artificial Intelligence, Machine Learning and Deep Learning”, Published in Advances in
- Intelligent Systems and Computing Information Systems Design and Intelligent Applications, 2019, p. 271- 283, Springer.
- Yizhuo Zhang, Yiwei Liu, Chi-Hua Chen, “Survey on Blockchain and Deep Learning”, 2020 IEEE 19th DOI: https://doi.org/10.1109/TrustCom50675.2020.00272
- International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
- K. SALAH, M. H. REHMAN, N. NIZAMUDDIN, and A. Al-Fuqaha,” Blockchain for AI: Review and
- Open Research Challenges”, IEEE Access, Vol. 4 2018
- Kushal Singla, Joy Bose, Sharvil Katariya, “Machine Learning for Secure Device Personalization Using
- Blockchain”, 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI).
- Xuhui Chen, Jinlong Ji, Changqing Luoy, Weixian Liaoz and Pan Li,” When Machine Learning Meets
- Blockchain: A Decentralized, Privacy-preserving and Secure Design”, 2018 IEEE International Conference on Big Data (Big Data)
- Hyunil Kim, Seung-Hyun Kim, Jung Yeon Hwang and Changho Seo,” Efficient Privacy-Preserving
- Machine Learning for Blockchain Network”, IEEE Access 2017
- Saurabh Singh, Pradip Kumar Sharma, Byungun Yoon, Mohammad Shojafar, Gi Hwan Cho, In-Ho Ra,” Convergence of Blockchain and Artificial Intelligence in IoT Network for the Sustainable Smart City”, Journal of Sustainable Cities and Society, Science Direct, 2020 DOI: https://doi.org/10.1016/j.scs.2020.102364
- Lenny Koh, Alexandre Dolgui & Joseph Sarkis, “Blockchain in transport and logistics – paradigms and
- transitions”, International Journal of Production Research, Vol. 58, No. 7, 2054–2062, 2020. DOI: https://doi.org/10.1080/00207543.2020.1736428
- Anandkumar Balasubramaniam, Malik Junaid Jami Gul, Varun G. Menon & Anand Paul,” Blockchain
- For Intelligent Transport System”, IETE Technical Review, 2020
- Enna Hirata, Maria Lambrou, Daisuke Watanabe, “Blockchain technology in supply chain management: insights from machine learning algorithms”, Maritime Business Review Vol. 6 No. 2, 2021 pp. 114-128 Emerald Publishing Limited. DOI: https://doi.org/10.1108/MABR-07-2020-0043
- Khizar Abbas , Lo’Ai A. Tawalbeh , Ahsan Rafiq , Ammar Muthanna , Ibrahim A. Elgendy , and Ahmed A. Abd El-Latif,” Convergence of Blockchain and IoT for Secure Transportation Systems in Smart Cities”, Hindawi Security and Communication Networks Volume 2021. DOI: https://doi.org/10.1155/2021/5597679
- Luba Eremina, Anton Mamoiko and Li Bingzhang,” Use of blockchain technology in planning and
- management of transport systems”, E3S Web Conf. Volume 157, 2020 Key Trends in Transportation
- Innovation (KTTI-2019).
- Walaa Hamdy, Noha Mostafa, and Hesham Elawady,” Towards a Smart Warehouse Management
- System”, Proceedings of the International Conference on Industrial Engineering and Operations
- Management Washington DC, USA, September 27-29, 2018.
- Alessandro Tufano, Riccardo Accorsi, Riccardo Manzini,” A machine learning approach for predictive warehouse design”, The International Journal of Advanced Manufacturing Technology (2022) 119:2369– 2392. DOI: https://doi.org/10.1007/s00170-021-08035-w
- Tan Gürpinar et.al.,”The Current State of Blockchain Applications in Supply Chain Management”,
- ICBCT ’21, March 26–28, 2021, Shanghai, China
- Nikish Kumar et. al.,” An Autonomous Food Wastage Control Warehouse: Distributed Ledger and
- Machine Learning based Approach”, 11th ICCCNT 2020 July 1-3, 2020 - IIT – Kharagpur.
- Zeinab Shahbazi and Yung-Cheol Byun,” Integration of Blockchain, IoT and Machine Learning for
- Multistage Quality Control and Enhancing Security in Smart Manufacturing”, Sensors 2021, 21, 1467.
- https://doi.org/10.3390/s21041467. DOI: https://doi.org/10.3390/s21041467
- “Using blockchain to drive supply chain innovation”, A series exploring Industry 4.0 technologies and their potential impact for enabling digital supply networks in manufacturing., Deloitte.