TY - GEN
T1 - The health monitoring system based on distributed data aggregation for WSN used in bridge diagnosis
AU - Xiao, Haitao
AU - Li, Tansheng
AU - Ogai, Harutoshi
AU - Zou, Xiaohong
AU - Otawa, Takenari
AU - Umeda, Shinya
AU - Tsuji, Takunori
PY - 2010/1/1
Y1 - 2010/1/1
N2 - Wireless sensor network are deployed today to monitor the environment, but their own health status is relatively opaque to network administrators, in most cases. In bridge diagnosis system, we develop a wireless sensor network to gather the vibration data of bridge. In past field bridge diagnosis experiment, node failure and data packets loss always occurred in the WSN and can not be detected. It causes some collected data is broken and cannot be used to analyze the health status of bridge. Furthermore, in field experiment it is always difficult to set the location of nodes in order to ensure the quality of link is good. In this paper, we consider the problem of monitoring the health of nodes, the quality of links and the healthiness of bridge diagnosis data from active end-to-end measurements in wireless sensor networks. Our system, DAMS (Distributed data Aggregation active Monitoring System), provides failure detection and symptom alerts, while being frugal in the use of energy and bandwidth. In order to improve the performance of active monitoring method we use distributed data aggregation to reduce the amount of communication and energy consumption. The monitoring system contains three functions, monitoring the health of nodes, monitoring the link quality and monitoring the healthiness of bridge diagnosis data. Key performance measures of this system include high detection accuracy (low false alarm probabilities), high responsiveness (low response latency), low energy consumption and low complexity. We debug the system in the wireless sensor network developed for bridge diagnosis and obtain the result in field experiment.
AB - Wireless sensor network are deployed today to monitor the environment, but their own health status is relatively opaque to network administrators, in most cases. In bridge diagnosis system, we develop a wireless sensor network to gather the vibration data of bridge. In past field bridge diagnosis experiment, node failure and data packets loss always occurred in the WSN and can not be detected. It causes some collected data is broken and cannot be used to analyze the health status of bridge. Furthermore, in field experiment it is always difficult to set the location of nodes in order to ensure the quality of link is good. In this paper, we consider the problem of monitoring the health of nodes, the quality of links and the healthiness of bridge diagnosis data from active end-to-end measurements in wireless sensor networks. Our system, DAMS (Distributed data Aggregation active Monitoring System), provides failure detection and symptom alerts, while being frugal in the use of energy and bandwidth. In order to improve the performance of active monitoring method we use distributed data aggregation to reduce the amount of communication and energy consumption. The monitoring system contains three functions, monitoring the health of nodes, monitoring the link quality and monitoring the healthiness of bridge diagnosis data. Key performance measures of this system include high detection accuracy (low false alarm probabilities), high responsiveness (low response latency), low energy consumption and low complexity. We debug the system in the wireless sensor network developed for bridge diagnosis and obtain the result in field experiment.
KW - Brige diagnosis
KW - Data aggregation
KW - Packet loss rate
KW - Wireless sensor networks
UR - http://www.scopus.com/inward/record.url?scp=78649240885&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78649240885&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:78649240885
SN - 9784907764364
T3 - Proceedings of the SICE Annual Conference
SP - 2134
EP - 2138
BT - Proceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers
PB - Society of Instrument and Control Engineers (SICE)
ER -