Reliability performance of wireless sensor networks for civil infrastructure – Part II: prediction and verification

AbstractApplication studies on wireless sensor networks (WSN) are actively conducted in the construction industry. However, there are several technical limitations including signal interference caused by the characteristics of wireless sensors, reliability degradation in wireless communication and uncertainty of configuring a network topology. This may lead to a decline in reliability and performance of real-time data acquisition methods. Thus, the paper developed a model capable of predicting reliability performance of wireless signals applied to civil infrastructures. The measured and predicted values of wireless signals are compared and analyzed through a field experiment carried out in an actual bridge to verify the prediction model suggested herein. As a result of the analysis, the prediction model demonstrated a variation up to 8.4% compared with actual measurements, proving the high accuracy of the prediction model. Furthermore, the reception rate at short distances within a 5 m radius is at least ...

[1]  M. Salazar-Palma,et al.  A survey of various propagation models for mobile communication , 2003 .

[2]  Soyoung Hwang,et al.  Remote Monitoring and Controlling System Based on ZigBee Networks , 2012 .

[3]  Biswanath Mukherjee,et al.  Wireless sensor network survey , 2008, Comput. Networks.

[4]  Kevin A. Snook,et al.  縦方向電界場中で曲げたPIN-PMN-PT単結晶の強度 , 2011 .

[5]  Luiz Affonso Guedes,et al.  Reliability and Availability Evaluation of Wireless Sensor Networks for Industrial Applications , 2012, Sensors.

[6]  Razi Iqbal,et al.  Intelligent Transportation Systems Using Short Range Wireless Technologies , 2011 .

[7]  Soon-Wook Kwon,et al.  Integrated Tunnel Monitoring System Using Wireless Automated Data Collection Technology , 2008 .

[8]  S. Jardosh,et al.  A Survey: Topology Control For Wireless Sensor Networks , 2008, 2008 International Conference on Signal Processing, Communications and Networking.

[9]  Youxian Sun,et al.  Impact of Link Unreliability and Asymmetry on the Quality of Connectivity in Large-scale Sensor Networks , 2008, Sensors.

[10]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[11]  F. Golatowski,et al.  Weighted Centroid Localization in Zigbee-based Sensor Networks , 2007, 2007 IEEE International Symposium on Intelligent Signal Processing.

[12]  Wu Jian,et al.  Metal mine underground safety monitoring system based on WSN , 2012, Proceedings of 2012 9th IEEE International Conference on Networking, Sensing and Control.

[13]  Xiang Yang,et al.  A ZigBee-Based Highway Vehicles Prevent Collision Warning System Research , 2011, 2011 Fourth International Symposium on Computational Intelligence and Design.

[14]  Byoung-Jo Choi,et al.  Enhanced self-configuration scheme for a robust ZigBee-based home automation , 2010, IEEE Transactions on Consumer Electronics.

[15]  Weiwei Wu,et al.  An integrated information management model for proactive prevention of struck-by-falling-object accidents on construction sites , 2013 .

[16]  M. Hata,et al.  Empirical formula for propagation loss in land mobile radio services , 1980, IEEE Transactions on Vehicular Technology.

[17]  Berardo Naticchia,et al.  A monitoring system for real-time interference control on large construction sites , 2013 .

[18]  Wen-Tsai Sung,et al.  Multi-Sensor Wireless Signal Aggregation for Environmental Monitoring System via Multi-bit Data Fusion , 2011 .

[19]  Jerome P. Lynch,et al.  Truck-based mobile wireless sensor networks for the experimental observation of vehicle–bridge interaction , 2011 .

[20]  Yacine Rezgui,et al.  An ontology framework for intelligent sensor-based building monitoring , 2012 .

[21]  A. Bonastre,et al.  New challenges in wireless sensor networks: fault tolerance and real time , 2005, 2005 IEEE International Conference on Industrial Technology.