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 Article Faculty Publications -Articles 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 Venugopal, Anita; Purad, Hemavati C.; Shanbhog, Manjula; Malhotra, Richa; Kaur, Tejinder; Jha, Nivedita Title A name given to the resource AI-driven deep learning framework for energy-efficient optimization in IoT-enabled wireless networks 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 International Journal of Information Technology (Singapore); Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s41870-025-02649-z" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s41870-025-02649-z</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105014889373?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105014889373?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 Venugopal A., IT Deparment, Dhofar University, Dhofar, Salalah, Oman; Purad H.C., Department of AIML, Ballari Institute of Technology &amp; Management, Karnataka, Ballari, India; Shanbhog M., Department of Computer Science, Christ University, Bangalore, India; Malhotra R., Dr. Akhilesh Das Gupta Institute of Professional Studies (ADGIPS), Delhi, India; Kaur T., Department of MMICTBM, Maharishi Markandeshwar (Deemed To Be University), Mullana, Haryana, Ambala, India; Jha N., Symbiosis Institute of Business Management, Symbiosis International (Deemed) University, Nagpur, India Description An account of the resource Artificial intelligence (AI) and Internet of Things (IoT)-enabled wireless sensor networks (WSNs) have revolutionized industries by providing automation, real-time monitoring, and analytics that are predictive. WSNs still face significant obstacles such data security, network flexibility, and energy limitations in spite of these developments. In order to optimize energy use in Internet of Things (IoT)-based WSNs, this study introduces a novel Reinforcement Learning-based Energy-Efficient Communication Protocol (RL-EECP) to optimize the lifetime of networks and guarantee effective data transmission. The suggested protocol integrates sleep scheduling, reinforcement learning, and data fusion techniques. Also, an adaptive prioritization approach is introduced that assesses nodes according to the surroundings, significance, and energy consumption. Experiments show that RL- EECP performs better than existing studies in extending node lifetime and preserving excellent network performance. Bharati Vidyapeeth's Institute of Computer Applications and Management 2025. Subject The topic of the resource Data Fusion; Energy Efficiency; IoT; Network Optimization; Reinforcement Learning; Sleep Scheduling; Wireless Sensor Networks Publisher An entity responsible for making the resource available Springer Science and Business Media B.V. Relation A related resource ISSN: 25112104; Language A language of the resource English Type The nature or genre of the resource Article 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