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 Sahaaya Arul Mary, S.A.; Sharon Jessika, S.; Sinha, Vishwanath; Goyal, Arshi; Sanjith Surya, S.; Pal, Shaunak Title A name given to the resource Human Activity Analysis Based on Smartphones and Smart Glasses Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Lecture Notes in Electrical Engineering;Volume;1419 LNEE;pp.407-417 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-96-5969-2_25" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-96-5969-2_25</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105028681113?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105028681113?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 Sahaaya Arul Mary S.A., Faculty of Engineering and Technology, Department of AIML and DS, Christ University, Kengeri Campus, Karnataka, Bangalore, India; Sharon Jessika S., School of Computer Science and Engineering, VIT Vellore Institute of Technology, Vellore, Vellore, India; Sinha V., School of Computer Science and Engineering, VIT Vellore Institute of Technology, Vellore, Vellore, India; Goyal A., School of Computer Science and Engineering, VIT Vellore Institute of Technology, Vellore, Vellore, India; Sanjith Surya S., School of Computer Science and Engineering, VIT Vellore Institute of Technology, Vellore, Vellore, India; Pal S., School of Computer Science and Engineering, VIT Vellore Institute of Technology, Vellore, Vellore, India Description An account of the resource The study explores the application of smart glasses and smartphones to study human behavior. Through ensemble and deep learning methodologies, the study seeks to autonomously scrutinize data from each device to improve accuracy and resilience in activity identification. The methodology adopted entails the utilization of distinct models for data derived from smartphones and smart glasses, as opposed to amalgamating attributes, to acquire distinctive insights into user activities. The study outcomes demonstrated promising results, showcasing elevated precision in activity recognition across various machine learning models. Comparative analyses with prior research work reveal enhancements in algorithmic efficacy. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. Subject The topic of the resource Activity identification; Algorithmic efficacy; Comparative analysis; Data analysis; Deep learning; Ensemble learning; Human activities; Precision; Smart glasses; Smartphones Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 18761100; ISBN: 978-981965968-5; 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