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 Conference Paper Faculty Publications- Conference Papers 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 Agarwal, Vedant; Budhiraja, Samiksha; Sasi, Ashwin; Jeno Lovesum, S.P. Title A name given to the resource Enhanced Approach for Precision Agriculture Using AI/ML Techniques 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 Lecture Notes in Networks and Systems;Volume;1247 LNNS;pp.19-30 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-81086-2_3" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-81086-2_3</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105005391660?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105005391660?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 Agarwal V., Computer Science and Engineering Bangalore, Christ University, Karnataka, Bengaluru, India; Budhiraja S., Computer Science and Engineering Bangalore, Christ University, Karnataka, Bengaluru, India; Sasi A., Computer Science and Engineering Bangalore, Christ University, Karnataka, Bengaluru, India; Jeno Lovesum S.P., Computer Science and Engineering Bangalore, Christ University, Karnataka, Bengaluru, India Description An account of the resource Precision-based agriculture has been made possible by recent technical breakthroughs and developments in information technology. These new developments have made it possible to better utilise contemporary methods and instruments, like IOT, soft computing, and wireless sensor technology, to increase the agricultural productions environmental and economic sustainability. Precision farming is a new trend in agriculture that sets itself apart from traditional farming methods by applying resources in a way that is efficient, planned, systematic, and justified in order to produce higher and better yields. Precision farming uses geographic information systems like weather patterns, remote sensing technologies like Wireless Sensor Networks (WSN), and soft computing tools like Support Vector Machines (SVM), Random Forest (RF), Artificial Neural Networks (ANN), and Decision Trees (DT) to monitor and predict farm produce requirements in real time and for the future. This study examines the application of several methods and tools used in precision farming. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. Subject The topic of the resource Artificial Intelligence; Data Science; Precision Agriculture; Supervised Learning; Unnamed Aerial Vehicle Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 23673370; ISBN: 978-303181085-5; Language A language of the resource English Type The nature or genre of the resource Conference paper 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