Smart Structures and Systems, Vol. 14, No. 1 (2014) 1-16 DOI: http://dx.doi.org/10.12989/sss.2014.14.1.001 1 Copyright © 2014 Techno-Press, Ltd. http://www.techno-press.org/?journal=sss&subpage=8 ISSN: 1738-1584 (Print), 1738-1991 (Online) Spatio-temporal protocol for power-efficient acquisition wireless sensors based SHM Nikola Bogdanovic 1 , Dimitris Ampeliotis 1 , Kostas Berberidis 1 , Fabio Casciati 2 and Jorge Plata-Chaves 1 1 Department of Computer Engineering and Informatics, University of Patras & C.T.I RU-8, 26500, Rio - Patra, Greece 2 Department of Civil Engineering and Architecture, University of Pavia,Via Ferrata 1, 27100 Pavia, Italy (Received September 16, 2013, Revised April 25, 2014, Accepted June 30, 2014) Abstract. In this work, we address the so-called sensor reachback problem for Wireless Sensor Networks, which consists in collecting the measurements acquired by a large number of sensor nodes into a sink node which has major computational and power capabilities. Focused on applications such as Structural Health Monitoring, we propose a cooperative communication protocol that exploits the spatio-temporal correlations of the sensor measurements in order to save energy when transmitting the information to the sink node in a non-stationary environment. In addition to cooperative communications, the protocol is based on two well-studied adaptive filtering techniques, Least Mean Squares and Recursive Least Squares, which trade off computational complexity and reduction in the number of transmissions to the sink node. Finally, experiments with real acceleration measurements, obtained from the Canton Tower in China, are included to show the effectiveness of the proposed method. Keywords: spatio-temporal correlated data; sensor reachback; adaptive predictor; wireless sensor network; structural health monitoring 1. Introduction Recent advances in microelectronics and wireless communications have enabled the development of low cost, low power devices that integrate sensing, processing and wireless communication capabilities. These devices, named sensor nodes, implement Wireless Sensor Networks (WSNs) which, as an alternative to the conventional wired systems, provide accurate and continuous monitoring of a phenomenon over some specific territory or structure. Typical applications of WSNs range from medical to military, and from home to industry. Within our interests, one outstanding application is Structural Health Monitoring (SHM), which consists in monitoring the behavior of civil structures, such as buildings, bridges, aircrafts and ships, during forced vibration testing or natural excitation (e.g. earthquakes, winds, live loading), as described by Lynch (2006). Corresponding author, Ph. D. Student, E-mail: bogdanovic@ceid.upatras.gr