Design and implementation of distributed algorithms for WSN-based structural health monitoring

Wang, Miaomiao; Cao, Jiannong; Liu, Miao; Chen, Bo; Xu, You‐Lin; Li, Jing

doi:10.1504/ijsnet.2009.023312

Cited by 16 publications

(7 citation statements)

References 12 publications

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“…The levels 1 and 3 are mainly the tasks for data analysis algorithms [9,31]. The other two levels are in effect a function of event detection and notification.…”

Section: Structural Health Monitoring (Shm)mentioning

confidence: 99%

“…The underlying motivation driving this change from data collection to in-network processing is the needs of the various engineering applications [5][6][7][8][9][10]. This paper mainly discusses two representative engineering application fields: intelligent transportation systems (ITS) and structured health monitoring (SHM) systems.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, VigilNet [12] by He et al the CarTel system [13] by Hull et al and the PATH project [14] at UC Berkeley. Many SHM systems using WSNs have also been proposed [9,10,[15][16][17][18]. However, due to the highly limited resources, most of them only exist in laboratories.…”

Section: Introductionmentioning

confidence: 99%

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iSensNet: an infrastructure for research and development in wireless sensor networks

Cao

et al. 2010

Front. Comput. Sci. China

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This paper describes iSensNet, an infrastructure that we designed and implemented for various research and development projects in wireless sensor networks (WSNs). iSensNet is composed of a WSN platform and an event publish/subscribe middleware. On the WSN platform, users can test their protocols of any and all non-physical layers; the platform provides real time performance evaluation of the protocols. With the provided middleware, iSensNet is able to accept event subscriptions, to decompose an event to sub-events, to build up event detection trees composed of these subevents, to collaborate in detecting the sub-events, and handle the event for various application programs. This paper focuses on the design of iSensNet, taking into consideration the severe resource constraints despite the high performance requirements of the applications.

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“…The levels 1 and 3 are mainly the tasks for data analysis algorithms [9,31]. The other two levels are in effect a function of event detection and notification.…”

Section: Structural Health Monitoring (Shm)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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iSensNet: an infrastructure for research and development in wireless sensor networks

Cao

et al. 2010

Front. Comput. Sci. China

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“…The damage detection results in these communities were then communicated with the surrounding communities and sent back to the central station. Another well‐known method is the collaborative damage event detection proposed in . In this method, each sensor node continuously collected the measured response and examined the existence of any abrupt changes of the structural parameters using the distributed damage index detection algorithm based on discrete wavelet transform.…”

Section: Introductionmentioning

confidence: 99%

Online dual‐rate decentralized structural identification for wireless sensor networks

Huang

Yuen

2019

Struct Control Health Monit

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In this paper, we propose a novel online dual-rate decentralized structural identification algorithm for wireless sensor networks. In this method, at the sensor nodes, the raw response measurements collected at each sensor are processed separately to obtain the preliminary local structural identification results. These results will then be compressed before transmitting with a much lower rate than the sampling rate to the central station for data fusion. At the central station, Bayesian fusion is utilized to integrate the compressed local identification results transmitted from the sensor nodes in order to obtain reliable global estimation. As a result, the large identification uncertainty in the local identification results can be substantially reduced. In addition to data compression, two different rates for sampling and transmission are used to alleviate the data transmission burden so that online model updating can be realized for wireless sensor networks. Examples using a 50-story shear-frame structure, a bridge, and a space truss are presented to demonstrate the performance of the proposed method.

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“…Recent advances in sensor technologies and wireless communication technologies (Wang et al, 2009, Yuan et al, 2006, Goldsmith, 2005, Tao, 2005, Yang and Yacoub, 2006 enable the creation of a new generation of healthcare monitoring systems with wearable electronics and photonics. Ambient intelligence (Aarts and Encarnação, 2008) has become quite influential in the development of new concepts for sensor integration and information processing by combining multidisciplinary fields.…”

Section: Introductionmentioning

confidence: 99%

Sensor integration for perinatology research

Chen

Bouwstra

et al. 2011

IJSNET

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The numbers of high-risk pregnancies and premature births are increasing due to the steadily higher age at which women get pregnant. The long-term quality of life of the neonates and their families depends increasingly critically on the ability to monitor the health status of mother and child accurately, continuously and unobtrusively throughout the perinatal period. Advances in sensor integration have enabled the creation of non-invasive solutions to improve the healthcare of the pregnant woman, and her child before, during and after delivery. In this paper, we present the design work of a smart jacket integrated with textile sensors for neonatal monitoring and software architecture of advanced sensor integration for delivery simulator. A balanced integration of technology, user focuses and design aspects is achieved. Prototypes are built for demonstrating the design concept and the experimental results are obtained in clinical settings.

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Design and implementation of distributed algorithms for WSN-based structural health monitoring

Cited by 16 publications

References 12 publications

iSensNet: an infrastructure for research and development in wireless sensor networks

iSensNet: an infrastructure for research and development in wireless sensor networks

Online dual‐rate decentralized structural identification for wireless sensor networks

Sensor integration for perinatology research

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