Research Article
CEEDS: A Cost Effective Event Detection System for Energy Efficient Railway Bridge Monitoring with Wireless Sensor Network
@ARTICLE{10.4108/eai.18-5-2016.151251, author={Soumendu Kumar Ghosh and Suman Maroju and Raja Datta and Prabir Kumar Biswas}, title={CEEDS: A Cost Effective Event Detection System for Energy Efficient Railway Bridge Monitoring with Wireless Sensor Network}, journal={EAI Endorsed Transactions on Future Internet}, volume={3}, number={8}, publisher={EAI}, journal_a={UE}, year={2016}, month={5}, keywords={event detection, wireless sensor network, railway bridge health monitoring, threshold, simple moving average, exponential moving average.}, doi={10.4108/eai.18-5-2016.151251} }- Soumendu Kumar Ghosh
Suman Maroju
Raja Datta
Prabir Kumar Biswas
Year: 2016
CEEDS: A Cost Effective Event Detection System for Energy Efficient Railway Bridge Monitoring with Wireless Sensor Network
UE
EAI
DOI: 10.4108/eai.18-5-2016.151251
Abstract
Railway Bridge Health Monitoring (RHM) is of prime importance as damages in bridges can lead to huge casualties. Wireless sensor network (WSN) has come up as a promising technology for health monitoring. WSN has severe energy and hardware constraints. In this paper, we propose an event detection system for WSN deployed for RHM. Our proposed system takes different constraints of sensor networks into consideration and efficiently uses the limited resources of sensors. The system keeps the sensors awake only during the time a train passes over the bridge and in sleep mode otherwise. The real time exponential moving average of the vibration signal of a sensor placed on the railway track is computed by our algorithm and the arrival of the train is detected if consecutive series of samples lie within two threshold bounds. Theoretical and experimental results indicate that our proposed system can considerably increase the service lifetime of sensor networks and aid in automating the RHM.
Copyright © 2016 Soumendu Kumar Ghosh et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.