A localized algorithm for Structural Health Monitoring using wireless sensor networks

Santos, Igor Leão dos; Pìrmez, Luci; Lemos, írico; Delicato, Flávia C.; Vaz, Luiz A.; Souza, José Neuman de; Zomaya, Albert Y.

doi:10.1016/j.inffus.2012.02.002

Cited by 38 publications

(27 citation statements)

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“…The fi rst, communication overhead, compromises the WSAN lifespan, because the nodes of the WSAN have limited energy resources. 4,6,8 An effective solution for maximizing the system life span is to process and reduce the sensed data locally, within the physical WSAN. Such data reduction consists of decreasing the amount of data (which reduces the corresponding transmissions) used by applications to make decisions.…”

Section: The Challenge Of Wsan Virtualizationmentioning

confidence: 99%

“…4 Moreover, because the CoS infrastructure follows an open, fl exible, and reconfi gurable design concept, 4 it can support applications requiring large-scale WSAN deployments, such as precision agriculture and structural health monitoring (see the related work sidebar). 6 Despite these advantages, however, there's still at least one important challenge to deal with in their design. This challenge pertains to the development of a model for WSAN virtualization that simultaneously meets the requirements of several applications, while dealing with the resource-constrained nature of WSANs and prolonging their lifespan.…”

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confidence: 99%

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Olympus: The Cloud of Sensors

et al. 2015

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A decentralized wireless sensor and actuator network (WSAN) virtualization model leverages the cloud of sensors paradigm to make the best use of the cloud and physical WSAN environments.n the last few years, we've witnessed the emergence of a new paradigm, the cloud of things (CoT), 1 a combination of cloud computing 2 and the Internet of Things (IoT). 3 A cloud is a large-scale (ideally unlimited) set of userfriendly virtualized computing resources that can be dynamically reconfi gured to serve a variable load, seeking optimum resource utilization. 2 The IoT paradigm envisions a global network infrastructure linking a wide variety of physical and virtual devices-the "smart things" that provide identifi cation, data processing, sensing, and connection capabilities to support the development of cooperative services and applications. 3 Essentially, in the CoT paradigm, the cloud acts as an intermediate layer between smart things and applications. Such an intermediate layer hides the complexity of smart things necessary to implement applications. 1 The IoT can benefi t from the cloud's virtually unlimited resources to implement service management and composition for utilizing smart things and the data they produce, 1 whereas the cloud can benefi t from the IoT by extending its scope to deal with real-world objects (smart things) in a distributed and dynamic way.Smart sensors play an important role in the CoT paradigm. 1 These sensors are tiny battery-powered devices endowed with processing, storage, sensing, actuation, and wireless communication capabilities. Such capabilities enable smart sensors to be grouped together to monitor variables, forming a wireless sensor and actuator network (WSAN). 3 WSANs include sink nodes, which are nodes at the edge of the WSAN that don't have the computational, energy, or communication resource constraints of smart sensors. Sink nodes serve as entry points for application requests, as well as points for collecting data from the smart sensors. In WSANs, the data acquired by the smart sensors can be processed and interpreted locally and/or sent to one or more of the sink nodes. Actuators can perform actions on the physical environments in response to the smart sensors' decisions.Given these smart sensor capabilities, WSANs show an advantage within the CoT paradigm in their support of the development of myriad novel coop-

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Section: The Challenge Of Wsan Virtualizationmentioning

confidence: 99%

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confidence: 99%

Olympus: The Cloud of Sensors

et al. 2015

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“…The work presented in [37] proposes a localized SHM algorithm supported by multilevel information fusion techniques to enable detection, localization, and extent determination of damage sites. We describe the requirements of this SHM application.…”

Section: Structural Health Monitoring Application Descriptionmentioning

confidence: 99%

“…As described in [37], the SHM application operates following five stages (setup, data collection, extract peaks, damage detection, and report). In the setup stage, the network is configured and the sensors collect the accelerometers data of the monitored structure.…”

Section: Structural Health Monitoring Application Descriptionmentioning

confidence: 99%

An approach based on the domain perspective to develop WSAN applications

et al. 2015

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As wireless sensor and actuator networks (WSANs) can be used in many different domains, WSAN applications have to be built from two viewpoints: domain and network. These different viewpoints create a gap between the abstractions handled by the application developers, namely the domain and network experts. Furthermore, there is a coupling between the application logic and the underlying sensor platform, which results in platform-dependent projects and source codes difficult to maintain, modify, and reuse. Consequently, the process of developing an application becomes cumbersome. In this paper, we propose a modeldriven architecture (MDA) approach for WSAN application development. Our approach aims to facilitate the task of the developers by: (1) enabling application design through high abstraction level models; (2) providing a specific methodology for developing WSAN applications; and (3) offering an MDA infrastructure composed of PIM, PSM, and transformation programs to support this process. Our approach Communicated by Prof. allows the direct contribution of domain experts in the development of WSAN applications, without requiring specific knowledge of programming WSAN platforms. In addition, it allows network experts to focus on the specific characteristics of their area of expertise without the need of knowing each specific application domain.

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“…This is normally the instance of a completely in-network system SHM process, thus algorithm is delegated as a multilevel fusion process. It is observable, particularly in the SHM literature, the broad utilization use of damage coefficients as consequences of multilevel fusion processes [3], [4], [5]. The quick advantage of utilizing information fusion techniques for calculating a damage coefficient is that only such coefficient,…”

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confidence: 99%

An Energy Efficient Decentralized Detection Of System For Structural Health Monitoring In Wireless Sensor And Actuator Networks

Roopa¹

2017

IJRASET

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In smart cities, infrastructures, such as bridges and buildings, are equipped with smart sensing and actuator devices interconnected via wireless links composing a wireless sensor and actuator network (WSAN). The WSAN nodes are able to measure a variety of environmental parameters, process the sensing data locally, work in a collaborative way, make decisions on the occurrence of relevant events, and react to such events performing local control actions or sending warnings to remote operators. The unprecedented capabilities of monitoring and responding to stimuli in the physical world of wireless sensor and actuator networks (WSAN) enable these networks to provide the underpinning for several Smart City applications, such as structural health monitoring (SHM). In those applications, civil structures, endowed with wireless smart devices, are able to selfmonitor and autonomously respond to situations using computational intelligence. A decentralized algorithm for detecting damage in structures by using a WSAN. As key characteristics, beyond presenting a fully decentralized (in-network) and collaborative approach for detecting damage in structures, our algorithm makes use of cooperative information fusion for calculating a damage coefficient. The algorithm in terms of its accuracy and efficient use of the constrained WSAN resources. Keywords: Decentralized Algorithm, Information Fusion, Structural Health Monitoring, Wireless Sensor and Actuator Networks, Smart Cities I. INTRODUCTION ADVANCED detecting systems play a major role as empowering technologies to construct brilliant urban areas. In urban areas, infrastructures, such as flyovers, bridges and buildings are furnished with smart sensing and actuator gadgets interconnected by means of wireless connections creating a wireless sensor and actuator network (WSAN) [1]. The WSAN hubs can able to measure a variety of natural parameters, process the detecting information locally, work cooperatively, make choices on the occurrence of significant events, and respond to such events performing nearby control activities or sending notices to remote administrators. Applications running on top of WSAN can give a wide assortment of services to the citizens. The SHM is a rising innovation, managing with the improvement and execution of continuous and reliable monitoring frameworks for civil foundation structures using a thick WSAN. The detecting devices normally utilized for SHM applications are strain gauges, anemometers, thermistors, and accelerometers. These gadgets gather information from the monitored environment, for example, vibration estimations using accelerometers, and convey them as advanced information. In this manner, by preparing this information, the SHM techniques permit the identification, localization and degree of extent determination of harm in structures. Most of the SHM algorithms found in the literature employ centralized architectures with sensing nodes transmitting messages to a centralized entity wherein the damage detection processes effecti...

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A localized algorithm for Structural Health Monitoring using wireless sensor networks

Cited by 38 publications

References 12 publications

Olympus: The Cloud of Sensors

Olympus: The Cloud of Sensors

An approach based on the domain perspective to develop WSAN applications

An Energy Efficient Decentralized Detection Of System For Structural Health Monitoring In Wireless Sensor And Actuator Networks

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