Title :
A rescue-assist wireless sensor networks for large building
Author :
Long Cheng ; Chengdong Wu ; Yunzhou Zhang ; Li Chen
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
This article designs a rescue-assist wireless sensor networks for fire rescue and health care in large building. This system consists of wearable tags, route sensor nodes and base station. The wearable tag detects the activity of the user. We firstly propose an efficient fall detection algorithm. This algorithm has a low computational complexity and can be used in sensor node. And the wearable tag sends emergency information to the base station when the user is detected falling down and cannot get up in a given time. And then we propose a localization method to locate the user in NLOS environment. This method removes the NLOS effects through a NLOS identification algorithm to improve the localization accuracy. The system and proposed algorithms have been put into actual test application, the experimental results demonstrate that the system is able to apply in rescue and the localization algorithm can locate the user accurately in the building.
Keywords :
computational complexity; health care; wireless sensor networks; NLOS environment; NLOS identification algorithm; base station; computational complexity; emergency information; fall detection algorithm; fire rescue; health care; large building; rescue assist wireless sensor networks; route sensor nodes; wearable tags; Accelerometers; Base stations; Biomedical monitoring; Buildings; Robot sensing systems; Wireless sensor networks; Zigbee; Fall detection; Indoor localization; Non-line of sight; Receive signal strength; Wireless sensor networks;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2013 8th IEEE Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-6320-4
DOI :
10.1109/ICIEA.2013.6566590