Open AccessSelf‐powered wireless sensor network using event‐triggered energy harvesters for monitoring and identifying intrusion activities
Author(s) -
Dong Chuan,
Li Suiqiong,
Han Ruofeng,
He Qisheng,
Li Xinxin,
Xu Dacheng
Publication year - 2019
Publication title -
iet power electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 77
eISSN - 1755-4543
pISSN - 1755-4535
DOI - 10.1049/iet-pel.2018.5701
Subject(s) - wireless sensor network , real time computing , node (physics) , alarm , event (particle physics) , vibration , wireless , energy (signal processing) , router , computer science , mobile phone , power (physics) , sensor node , engineering , electrical engineering , key distribution in wireless sensor networks , computer network , wireless network , telecommunications , acoustics , statistics , physics , mathematics , quantum mechanics , structural engineering
Monitoring concerned activities and identifying activity types usually require sensors and corresponding data processing circuits, which are often restricted by the limited power supply in wireless sensor networks (WSNs). This study presents a self‐powered smart WSN for passively monitoring and distinguishing different vibration events. In the proposed WSN, the sensing function is performed by vibration‐threshold‐triggered energy harvesters (VTT‐EHs). The output power of the VTT‐EH dramatically increases when an input vibration exceeds the pre‐set vibration‐threshold of the harvester, indicating the occurrence of specific concerned events. On the basis of this principle, two VTT‐EHs with different thresholds were designed to detect and distinguish vibration events with different vibration characteristics. Meanwhile, electromagnetic EHs were applied to generate sufficient power for wirelessly transmitting the alarm signals within several seconds. The prototype of the proposed WSN was developed and evaluated. The sensor node was able to identify two types of intrusive activities: weak shake and strong knock. The alarming signals were first sent to a router node and then transmitted to a mobile phone through the global system of mobile communication network. The mobile phone received the alarming text messages with correct event type within 2 s after the excitation occurred.