Human Daily Activity Recognition Using Ceiling Mounted PIR Sensors

DOI

10.2991/ameii-16.2016.169How to use a DOI?

Keywords

Pyroelectric Infrared (PIR) Sensors , Ambient Assisted Living (AAL), Wireless Sensor Networks (WSNs)

Abstract

Human daily activity recognition is the foundation of automatic Ambient Assisted Living (AAL) system. In the paper, we propose a sensing model which can capture the discriminative spatio-temporal feature of human motion in an efficient way. The object space is separated into distinct discrete sampling cells by reference structure, and the ceiling mounted Pyroelectric infrared (PIR) sensors are used to capture the time-varying signal induced by human motion. The GMM-HMM model is utilized to classify different human activities. We use a self-developed PIR sensor node mounted on the ceiling to conduct experiments in a real office environment. Promising experimental results confirm the validity of our model.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaomu Luo
AU  - Tong Liu
AU  - Baihua Shen
AU  - Jiaming Hong
AU  - Qinqun Chen
AU  - Hao Chen
PY  - 2016/04
DA  - 2016/04
TI  - Human Daily Activity Recognition Using Ceiling Mounted PIR Sensors
BT  - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016)
PB  - Atlantis Press
SP  - 872
EP  - 877
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-16.2016.169
DO  - 10.2991/ameii-16.2016.169
ID  - Luo2016/04
ER  -