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 Faculty Publications- Book 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 Raj, Pethuru; Sharma, Durga Prasad; Dutta, Pushan Kumar; Prasad, B. V. V. Siva; Soundarabai, P. Beaulah Title A name given to the resource Artificial Intelligence (AI) for IT Energy Efficiency and Green AI for Environment Sustainability Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Artificial Intelligence (AI) for IT Energy Efficiency and Green AI for Environment Sustainability;pp.1-690 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-89420-6" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-89420-6</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105033419283?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105033419283?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 Raj P., RJIL, Site Reliability Engineering, Reliance Industries (India), Karnataka, Bangalore, India; Sharma D.P., MAISM, Rajasthan Technical University, Rajasthan, Jaipur, India; Dutta P.K., Amity University Kolkata, West Bengal, Kolkata, India; Prasad B.V.V.S., School of Engineering, Anurag University, Telangana, Hyderabad, India; Soundarabai P.B., Dept of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, India Description An account of the resource This volume approaches Artificial Intelligence for sustainability from two angles. First, it looks at AI systems themselves, which consume a surprising amount of energy to function, and examines ways they can be made more efficient and sustainable. Secondly, it examines how AI can be used to create efficiencies and make buildings, power grids, the manufacturing sector, and more sustainable. The chapters here also provide a comprehensive but compact overview of the latest in AI technologies and how they work. This volume will be useful to AI engineers, data scientists, software developers, academics, researchers, and more. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. Publisher An entity responsible for making the resource available Springer Nature Relation A related resource ISBN: 978-303189420-6; 978-303189419-0; Language A language of the resource English Type The nature or genre of the resource Book 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