GROUP ACTIVITY RECOGNITION BY INTEGRATION AND FUSION OF INDIVIDUAL MULTISENSORY IoT DATA

摘要

#$%^&*AU2020102094A420201008.pdf#####GROUP ACTIVITY RECOGNITION BY INTEGRATION AND FUSION OF INDIVIDUAL MULTISENSORY IoT DATA ABSTRACT The wearable and smartphone embedded sensors have attracted the researchers for human activity identification. Multi-Sensory data in the healthcare application is widely increased in research because it aims to monitor the behaviors of humans, estimating energy expenditure, posture detection, etc. In recent days, the researchers are giving importance to the multi-Sensor fusion method for the reason of achieving good performance, robustness, solving difficulties present in single sensor values. In recent years, several fusion methods are proposed to identify and monitor human activities by using multiple sensors. Group Activity Recognition (GAR) method has impressed the researchers, and it is widely spread in recent years. The main aim of this framework is to introduce a new multi-sensory fusion of IoT data to improve human activities and group activities, also to reduce the misrecognition rate. The framework model is proposed for group activities by integrating the individual sensor data to conclude group activity. The proposed framework focuses on developing protocols to integrate IoT data, features, and multiple classification algorithms to enhance physical activities by monitoring human activities and evaluation. 1| P a g eGROUP ACTIVITY RECOGNITION BY INTEGRATION AND FUSION OF INDIVIDUAL MULTISENSORY IoT DATA Drawings: Data Cd at M perat on Pun 5e ws sigal Processag 1 ! neiromT ~ete r Alrtering zurzruto sofa pe S ig na Ienntton ------------------------------- I pnoirt reni Actvigy DTails Figure~~~~~~~~S 1: Prpoe Grou AciiReontnFrmwk 1- |N PW a g