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 Book Chapter 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/. Title A name given to the resource Machine Learning and IoT in Smart Agriculture Description An account of the resource Smart agriculture is becoming more necessary as food demands quickly rise in response to a growing global population. Additionally, agriculture serves as the primary source of income for almost 60% of India's people. Yet most of our farming practices are still archaic and out-of-date. The fast-expanding population may not be able to be fed using these methods. Smart agriculture uses cutting-edge technology, including Internet of Things (IoT), global positioning systems (GPS), machine learning, robots, and the use of linked gadgets. Smart agriculture could support an artificial intelligence (AI)-integrated agricultural system that gathers data about the agricultural area and then analyses it to help the farmer make the best decisions for producing high-quality crops. The field of AI, with its superior learning capability, is a critical method for tackling several difficulties related to agriculture. AI provides appealing computing and analytical techniques for the better integration of various information-gathering forms from various sources. This paper elaborates the innovative ways AI can be used in the field of Indian agriculture. The study also goes into detail on the impact of smart farming on agricultural research. The analysis demonstrates the range and impact of cutting-edge technology in Indian agriculture, including sensors for rainfall rate prediction, GPS, moisture and temperature sensors, and aerial satellite photos. 2025 selection and editorial matter, Sirisha Potluri, Suneeta Satpathy, Santi Swarup Basa, and Antonio Zuorro; individual chapters, the contributors. All rights reserved. Creator An entity primarily responsible for making the resource Tanguturu A.; Saradha S.; Rao K.V.; Preethi N. Source A related resource from which the described resource is derived AI in Agriculture for Sustainable and Economic Management, pp. 112-118. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003451648-9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003451648-9</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204618671&amp;doi=10.1201%2F9781003451648-9&amp;partnerID=40&amp;md5=8c5f6348290f30677b74bf148375b19b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85204618671&amp;doi=10.1201%2f9781003451648-9&amp;partnerID=40&amp;md5=8c5f6348290f30677b74bf148375b19b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-104009810-3; 978-103258569-7 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Tanguturu A., Christ University, Lavasa, Pune, India; Saradha S., Christ University, Lavasa, Pune, India; Rao K.V., Christ University, Lavasa, Pune, India; Preethi N., CHRIST University, Lavasa Campus, Pune, India