title: Sensing Home: A Cost-Effective Design for Smart Home via Heterogeneous Wireless Networks.
abstract: The aging population has inspired the marketing of advanced real time devices for home health care, more and more wearable devices and mobile applications, which have emerged in this field. However, to properly collect behavior information, accurately recognize human activities, and deploy the whole system in a real living environment is a challenging task. In this paper, we propose a feasible wireless-based solution to deploy a data collection scheme, activity recognition model, feedback control and mobile integration via heterogeneous networks. We compared and found a suitable algorithm that can be run on cost-efficient embedded devices. Specifically, we use the Super Set Transformation method to map the raw data into a sparse binary matrix. Furthermore, designed front-end devices of low power consumption gather the living data of the habitant via ZigBee to reduce the burden of wiring work. Finally, we evaluated our approach and show it can achieve a theoretical time-slice accuracy of 98%. The mapping solution we propose is compatible with more wearable devices and mobile apps.
authors.affiliation: School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. fanxiaohu@hust.edu.cn.
authors.forename: Xiaohu
authors.initials: X
authors.lastname: Fan
authors.affiliation: School of Software Engineering, Huazhong University of Science and Technology, Wuhan 430074, China. thao@hust.edu.cn.
authors.forename: Hao
authors.initials: H
authors.lastname: Huang
authors.affiliation: School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. qishipeng@hust.edu.cn.
authors.forename: Shipeng
authors.initials: S
authors.lastname: Qi
authors.affiliation: School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. luoxc613@hust.edu.cn.
authors.forename: Xincheng
authors.initials: X
authors.lastname: Luo
authors.affiliation: School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. zengjing@hust.edu.cn.
authors.forename: Jing
authors.initials: J
authors.lastname: Zeng
authors.affiliation: School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China. baidu@hust.edu.cn.
authors.forename: Qubo
authors.initials: Q
authors.lastname: Xie
authors.affiliation: Wuhan National Laboratory for Optoelectronics, No. 1037 Luoyu Road, Wuhan 430074, China. cs_xie@hust.edu.cn.
authors.forename: Changsheng
authors.initials: C
authors.lastname: Xie
keywords: activity recognition; cost-effective; mobile integration; pervasive computing