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 Mahalakshmi, J.; Balakrishnan, C.; Tharwani, Alisha; Dhanasekaran, Seshathiri Title A name given to the resource AI-Driven Health Coach for Diabetes Management 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 Internet of Medical Things: Case Studies and Applications in Healthcare;pp.65-81 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003476344-5" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003476344-5</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105034135564?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105034135564?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 Mahalakshmi J., Department of Computer Science, CHRIST University, Bengaluru, India; Balakrishnan C., Department of Computer Science, CHRIST University, Bengaluru, India; Tharwani A., Department of Computer Science, CHRIST University, Bengaluru, India; Dhanasekaran S., UiT, The Arctic University of Norway, Troms Norway Description An account of the resource Artificial intelligence (AI) is transforming diabetes care through innovative approaches that enhance monitoring, prediction, and treatment. AI-powered health coaches exemplify this progress by automating various aspects of patient care, such as creating personalized dietary plans and managing medication schedules, thereby optimizing resource utilization with minimal human intervention. In India, where diabetes affects over 77 million people and significantly elevates the risk of complications like heart disease and stroke, AI-driven tools offer immense potential. Food recognition and nutritional apps powered by AI can revolutionize diabetes management by tracking dietary intake and providing tailored recommendations. However, widespread adoption faces barriers, including challenges related to localization, cultural relevance, and integration with healthcare systems. This chapter examines the role of AI in diabetes management, evaluating the benefits and limitations of current applications. It also proposes a framework for an AI-driven health coach tailored to the Indian context. The proposed solution aims to bridge existing gaps by delivering accurate, culturally sensitive, and integrated diabetes management tools, ultimately improving long-term health outcomes for Indian patients. 2026 selection and editorial matter, Balakrishnan C, Jayapriya J, Vinay M, Sanjeev Kumar Singh, Nadarajah Manivannan individual chapters, the contributors. Publisher An entity responsible for making the resource available CRC Press Relation A related resource ISBN: 978-104050436-9; 978-103274893-1; 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