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 Jain, Rituraj; Upreti, Kamal; Ekatpure, Shubham Rajendra; Gupta, Vipul Kumar; Rai, Ashish Kumar; Gothania, Jaishri Title A name given to the resource The convergence of IoT, ML, and big data in self-service innovation 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 Navigating the Self-Service Revolution With Smart Machines;pp.241-269 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.4018/979-8-3373-1295-8.ch009" target="_blank" rel="noreferrer noopener">https://doi.org/10.4018/979-8-3373-1295-8.ch009</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105013421198?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105013421198?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 Jain R., Marwadi University, India; Upreti K., Christ University, India; Ekatpure S.R., Kulicke and Soffa, United States; Gupta V.K., Ramchandra Chandravansi University, Palamu, India; Rai A.K., Ramchandra Chandravansi University, Palamu, India; Gothania J., Muscat, Oman Description An account of the resource Internet of Things, Machine Learning, and Big Data analytics have been bringing a transformation to self-service technologies with automation, personalization, and operations efficiencies. IoT captures the data in real-time by linked sensors; ML will try to find the patterns, providing the output; and Big Data would analyze large datasets to deliver actionable insights. All three together bring smarter and adaptive systems in retail, health care, and rural service industries. The applications include inventory management, personalized healthcare forecasting, and community kiosks. While these innovations are achieved, interoperability, scalability, and high implementation costs in rural areas are some of the persistent challenges. This can be addressed by taking advantage of edge computing, cloud solutions, and the collaboration of stakeholders. Further innovations like 5G and federated learning will shape self-service technologies in the future to deliver efficient, inclusive, and innovative solutions. 2026, IGI Global Scientific Publishing. Publisher An entity responsible for making the resource available IGI Global Relation A related resource ISBN: 979-833731297-2; 979-833731295-8; 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