Human Activity Analysis Based on Smartphones and Smart Glasses
Activity identification; Algorithmic efficacy; Comparative analysis; Data analysis; Deep learning; Ensemble learning; Human activities; Precision; Smart glasses; Smartphones
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.
Sahaaya Arul Mary, S.A.; Sharon Jessika, S.; Sinha, Vishwanath; Goyal, Arshi; Sanjith Surya, S.; Pal, Shaunak
Lecture Notes in Electrical Engineering;Volume;1419 LNEE;pp.407-417
Springer Science and Business Media Deutschland GmbH
Restricted Access; Hardcopy may be available in the library
https://doi.org/10.1007/978-981-96-5969-2_25 https://www.scopus.com/pages/publications/105028681113?origin=resultslist
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