Impact of Sensor Data Glut on Activity Recognition in Smart Environments

被引：0
|
作者：
Hakim, Alaa E. Abdel [1 ,3 ]
Deabes, Wael A. [2 ,3 ]
机构：
[1] Assiut Univ, Dept Elect Engn, Assiut, Egypt
[2] Mansoura Univ, Comp & Syst Engn Deptarunent, Mansoura, Egypt
[3] Umm Al Qura Univ, Univ Coll, Dept Comp Sci, Mecca, Saudi Arabia
来源：
2017 IEEE 17TH INTERNATIONAL CONFERENCE ON UBIQUITOUS WIRELESS BROADBAND (ICUWB) | 2017年
关键词：
Activity Recognition; Sensor Glut; ADL; Smart Environments; HMM;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In activity recognition applications, rich sensor data may he obviously desirable for performance. However, using much sensor data can lead to undesirable glut. In this paper, we investigate the effect of excessive use of sensor data on the performance of activity recognition. Particularly, we study the effect of using analog temperature sensors data on the accuracy of an HMM-based recognition approach. The performance is comparatively evaluated using confusion matrices before and after including additional temperature sensors.
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页数：5
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