活动识别
计算机科学
云计算
可穿戴计算机
软件部署
物联网
仪表板
边缘计算
家庭自动化
服务器
智能环境
嵌入式系统
可视化
GSM演进的增强数据速率
惯性测量装置
实时计算
人工智能
计算机网络
数据科学
电信
操作系统
作者
Thinagaran Perumal,E. Ramanujam,Sukhavasi Suman,Abhishek Sharma,Harshit Singhal
出处
期刊:IEEE Internet of Things Journal
[Institute of Electrical and Electronics Engineers]
日期:2023-01-15
卷期号:10 (2): 1724-1732
被引量:4
标识
DOI:10.1109/jiot.2022.3209970
摘要
In recent times, numerous human activity recognition (HAR) schemes have been proposed with embedding sensors, wearable devices, smart phones, and vision and ambient sensors. Though the systems have shown better performance they are mostly standalone and still lack the ability to share, host, and perform real-time analysis and visualization of activity data. The Internet of Things (IoT) paradigm has a solution to render the limitations and this will pave the way for HAR in the smart home environment. Thus in this article, an IoT-centric multiactivity recognition system is proposed and deployed on the cloud platform for activity data tracking in the smart home environment. The proposed system collects the real-time data collected using IMU sensors and transmitted to the IoT-Edge Server via Wi-Fi where the data has been fused and classified using light-weight deep learning models. This system has a provision of a Web-based dashboard which is helpful for the home dwellers to monitor the activities in the remote. The performance evaluation justified that the developed system can measure IoT-based activity recognition with greater efficiency in terms of accuracy and F1-score in a shorter response time as of deployment in the cloud platform to detect the activity.
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