Human Daily Activity Recognition Using Ceiling Mounted PIR Sensors
- https://doi.org/10.2991/ameii-16.2016.169How to use a DOI?
- Pyroelectric Infrared (PIR) Sensors , Ambient Assisted Living (AAL), Wireless Sensor Networks (WSNs)
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/ameii-16.2016.169 ID - Luo2016/04 ER -