of excellence in research and education that has contributed greatly to the state-of-the-art in civil engineering. Completed in 1967 and extended in 1971, the structural testing area of the laboratory has a versatile strong-floor/wall and a three-story clear height that can be used to carry out a wide range of tests of building materials, models, and structural systems. The laboratory is named for Dr. Nathan M. Newmark, an internationally known educator and engineer, who was the Head of the Department of Civil Engineering at the University of Illinois [1956-73] and the Chair of the Digital Computing Laboratory [1947-57]. He developed simple, yet powerful and widely used, methods for analyzing complex structures and assemblages subjected to a variety of static, dynamic, blast, and earthquake loadings. Dr. Newmark received numerous honors and awards for his achievements, including the prestigious National Medal of Science awarded in 1968 by President Lyndon B. Johnson. He was also one of the founding members of the National Academy of Engineering. Contact: Prof. B.F. Spencer, Jr.

Wireless sensor networks (WSNs) have become an increasingly compelling platform for Structural Health Monitoring (SHM) applications, since they can be installed relatively inexpensively onto existing infrastructure. Existing approaches to SHM in WSNs typically address computing system issues or structural engineering techniques, but not both in conjunction. In this paper, we propose a holistic approach to SHM that integrates a decentralized computing architecture with the Damage Localization Assurance Criterion algorithm. In contrast to centralized approaches that require transporting large amounts of sensor data to a base station, our system pushes the execution of portions of the damage localization algorithm onto the sensor nodes, reducing communication costs by an order of magnitude in exchange for moderate additional processing on each sensor. We present a prototype implementation of this system built using the TinyOS operating system running on the Intel Imote2 sensor network platform. Experiments conducted using two different physical structures demonstrate our system’s ability to accurately localize structural damage. We also demonstrate that our decentralized approach reduces latency by 64.8 % and energy consumption by 69.5 % compared to a typical centralized solution, achieving a projected lifetime of 191 days using three standard AAA batteries. Our work demonstrates the advantages of a holistic approach to cyber-physical systems that closely integrates the design of computing systems and physical engineering techniques. 1

Abstract — Smart sensors densely distributed over structures can provide rich information for structural monitoring using their computational and wireless communication capabilities. One key issue in such monitoring is data aggregation. The sensors are typically sampled at high frequencies, producing large amounts of data; limited network resources (e.g., battery power, storage space, bandwidth, etc.) make acquiring and processing this data quite challenging. Efficient data aggregation with data compression is needed to achieve scalable sensor networks for structural monitoring. Model-based data aggregation is proposed using both structural and network analyses. A structural analysis algorithm, the Natural Excitation Technique, motivates adaptation of correlation function estimation to smart sensor networks. The data size is reduced by a factor of 20 to 40, depending on the degree of averaging in the aggregation. This averaging also addresses the wireless communication data loss problem. The algorithm is implemented on Mica2s and experimentally validated using a scale-model building. Keywords- coordinated computing; data compression; distributed algorithm; smart sensors I.

Wireless sensor networks (WSN) are gradually gaining the attention of structural engineers as an attractive tool for structural health monitoring (SHM) applications. In this work, an experimental implementation of a correlation-based, decentralized damage detection technique using a wireless sensor network is presented. The Damage Location Assurance Criterion (DLAC) method is validated experimentally using wireless sensor networks. The networks are deployed on both a steel cantilever beam and on a 3D truss model. The experimental implementations are described and corresponding results are presented. Limitations with sensor functionalities during experiment are also addressed and discussed. 1.