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 Pradeepa, S.V.; Gokilavani, R.; Deepan, A.; Sridevi, J.; Selvi, K. Title A name given to the resource Predictive Maintenance and Asset Management Using Motion Analytics 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 Methodologies and Applications of Intelligent Motion Control Systems;pp.75-103 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3693-3637-3.ch004" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3693-3637-3.ch004</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105025077369?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105025077369?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 Pradeepa S.V., JSPM University, Pune, India; Gokilavani R., Chirst University, Banglore, India; Deepan A., Sambhram University, Uzbekistan; Sridevi J., Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology, India; Selvi K., Saveetha Engineering College, Chennai, India Description An account of the resource In this chapter, the researcher studies how motion analytics enabled by smart sensing and data modeling provides an effective way of predictive maintenance and managing assets within industrial systems. It talks about how time based diagnostics and anomaly detection algorithms in the past time along with the history trends could be used to predict machine failures even before it has happened. The combination of machine learning and Internet of Things (IoT) platforms is stressed as one of the enablers of real- time decision making and low rates of downtimes. Such implementation issues as data quality, sensor calibration, system scalability are also tackled in this chapter. It lays stress on the importance of motion analytics with respect to reliable and efficient planning of lifecycle management and key assets. 2026, IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-836933638-0; 979-836933637-3; 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