Structural monitoring-the collection and analysis of structural response to ambient or forced excitation-is an important application of networked embedded sensing with significant commercial potential. The first generation of sensor networks for structural monitoring are likely to be data acquisition systems that collect data at a single node for centralized processing. In this paper, we discuss the design and evaluation of a wireless sensor network system (called Wisden) for structural data acquisition. Wisden incorporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchronization. We also study the applicability of wavelet-based compression techniques to overcome the bandwidth limitations imposed by lowpower wireless radios. We describe our implementation of these mechanisms on the Mica-2 motes and evaluate the performance of our implementation. We also report experiences from deploying Wisden on a large structure.
Accurate personnel and vehicle tracking has been achieved using networks of small, unobtrusive, low-cost wireless sensors. The wireless MSTAR sensors developed in this work are based on previous pioneering MEMS sensing and TinyOS communications software work completed at UC Berkeley. The works has been funded under the DARPA SensIT, SensorWebs, and on-going DARPA NEST programs. These MSTAR sensors deliver around the clock all-weather surveillance and perimeter protection for field environments, including buildings, camp and tent locations, streets, mountainous regions, and other geographies. These capabilities satisfy many on-going intelligence and warfighter safety requirements. The MSTAR sensors are quickly deployed by hand emplacement or air-drop from a UAV or other airborne platform. The combination of multimode sensing on each wireless MSTAR sensor and multiple MSTAR sensors in the environment yields low false detections within the network perimeter. In addition, using the geopgraphy dispersion and networked algorithms, it is possible to estimate the target's speed, direction, and loosely classify the target. Satellite exfiltration of data provides real-time access to the data on a worldwide
Accurate personnel and vehicle tracking has been achieved using networks of small, unobtrusive, low-cost wireless sensors. The wireless MSTAR sensors developed in this work are based on previous pioneering MEMS sensing and TinyOS communications software work completed at UC Berkeley. The works has been funded under the DARPA SensIT, SensorWebs, and on-going DARPA NEST programs. These MSTAR sensors deliver around the clock all-weather surveillance and perimeter protection for field environments, including buildings, camp and tent locations, streets, mountainous regions, and other geographies. These capabilities satisfy many on-going intelligence and warfighter safety requirements. The MSTAR sensors are quickly deployed by hand emplacement or air-drop from a UAV or other airborne platform. The combination of multimode sensing on each wireless MSTAR sensor and multiple MSTAR sensors in the environment yields low false detections within the network perimeter. In addition, using the geopgraphy dispersion and networked algorithms, it is possible to estimate the targets speed, direction, and loosely classify the target. Satellite exfiltration of data provides real-time access to the data on a worldwide
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