Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Vinodha, D.; Anita, E. A. Mary; Thirunavukkarasu, Padmavathy; Geetha, P. Title A name given to the resource Blockchain-Based Digital Twin for Predictive Maintenance of Machines Using Machine Learning Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Blockchain-Based Digital Twins: Research Trends and Challenges;pp.249-277 Identifier An unambiguous reference to the resource within a given context <a href="https://www.scopus.com/pages/publications/105006551760?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105006551760?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vinodha D., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Anita E.A.M., CHRIST (Deemed to be University), Karnataka, Bangalore, India; Thirunavukkarasu P., Department of Computational Intelligence, SRM Institute of Science and Technology, Tamil Nadu, Kattakulathur, India; Geetha P., Department of Computational Intelligence, SRM Institute of Science and Technology, Tamil Nadu, Kattakulathur, India Description An account of the resource Digital Twin (DT) is a software replica of the physical asset or process that serves the automobile industry by empowering engineers and data scientists to gain a deeper insight into the system and solve the biggest challenges with less time and cost. Blockchain technology is an evolving and promising technology that foresees providing surveil -lance facilities for DTs, resulting in firming up security and improving the openness, reliability, and unchangeability of DTs. By incorporating intellectual behavior in blockchain-based DTs, the functions of machines can be governed parallelly, and the major maintenance activities can be predicted effectively. This chapter explores the design of various frameworks using recent technologies. Some of them are DTs, blockchain, artificial intelligence, and the Internet of Things which drive resolution in the industry to minimize the governing cost of machines. 2025 by Apple Academic Press, Inc. Subject The topic of the resource Blockchain; Deep learning; Digital twin; Edge computing; Industrial machines; Long-term memory; Machine learning; Novel framework; Predictive maintenance; Stakeholders Publisher An entity responsible for making the resource available Apple Academic Press Relation A related resource ISBN: 978-104026679-3; 978-177491842-5; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online