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 Selvakumar, P.; Ganesh Kumar, R.; Kumar, Pallapati Ravi; Manjunath, T.C.; Arun, M.R. Title A name given to the resource AI-Driven Energy Efficiency in Buildings and Urban Environments 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 Advancing the Clean Energy Frontier Through AI-Powered Green Innovation;pp.69-93 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-5540-5.ch003" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-5540-5.ch003</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105028049818?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105028049818?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 Selvakumar P., Department of Science and Humanities, Nehru Institute of Technology, Coimbatore, India; Ganesh Kumar R., Christ University, India; Kumar P.R., Koneru Lakshmaiah Education Foundation, India; Manjunath T.C., Rajarajeswari College of Engineering, India; Arun M.R., Vel Tech Rangarajan Dr. Sagunthala R&amp;D Institute of Science and Technology, India Description An account of the resource In buildings, AI-driven energy management systems (EMS) are revolutionizing the way energy is consumed. Smart building technologies equipped with AI can monitor environmental conditions, occupancy patterns, and equipment performance to fine-tune their operations, leveraging intensive machine learning to learn the preferences of building occupants and adapt accordingly to ensure comfort while minimizing energy use. Predictive maintenance, powered by AI, also contributes to energy efficiency by identifying equipment that operates inefficiently or is at risk of failure, enabling timely interventions that prevent energy waste. The industrial sector, a significant consumer of global energy, is another arena where AI is making remarkable strides in enhancing energy efficiency. 2026 by IGI Global Scientific Publishing. All rights reserved. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833735542-9; 979-833735540-5; 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