Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

A formal methodology to design and deploy dependable wireless sensor networks

Wireless Sensor Networks (WSNs) are being increasingly adopted in critical applications, where verifying the correct operation of sensor nodes is a major concern. Undesired events may undermine the mission of the WSNs. Hence their effects need to be properly assessed before deployment to obtain a good level of expected performance and during the operation in order to avoid dangerous unexpected results. In this paper we propose amethodology that aims at assessing and improving the dependability level of WSNs by means of an event-based formal verification technique. The methodology includes a process to guide designers towards the realization of dependable WSN and a tool ("ADVISES") to simplify its adoption. The tool is applicable to homogeneous WSNs with static routing topologies. It allows to generate automatically formal specifications used to check correctness properties and evaluate dependability metrics at design time and at runtime for WSNs where an acceptable percentage of faults can be defined. During the runtime we can check the behavior of the WSN accordingly to the results obtained at design time and we can detect sudden and unexpected failures, in order to trigger recovery procedures. The effectiveness of the methodology is shown in the context of two case studies, as proof-of-concept, aiming to illustrate how the tool is helpful to drive design choices and to check the correctness properties of the WSN at runtime. Although the method scales up to very large WSNs, the applicability of the methodology maybe compromised by the state space explosion of the reasoning model, which must be faced partitioning large topologies into sub-topologies

A formal methodology to design and deploy dependable wireless sensor networks

Wireless Sensor Networks (WSNs) are being increasingly adopted in critical applications, where verifying the correct operation of sensor nodes is a major concern. Undesired events may undermine the mission of the WSNs. Hence their effects need to be properly assessed before deployment to obtain a good level of expected performance and during the operation in order to avoid dangerous unexpected results. In this paper we propose amethodology that aims at assessing and improving the dependability level of WSNs by means of an event-based formal verification technique. The methodology includes a process to guide designers towards the realization of dependable WSN and a tool ("ADVISES") to simplify its adoption. The tool is applicable to homogeneous WSNs with static routing topologies. It allows to generate automatically formal specifications used to check correctness properties and evaluate dependability metrics at design time and at runtime for WSNs where an acceptable percentage of faults can be defined. During the runtime we can check the behavior of the WSN accordingly to the results obtained at design time and we can detect sudden and unexpected failures, in order to trigger recovery procedures. The effectiveness of the methodology is shown in the context of two case studies, as proof-of-concept, aiming to illustrate how the tool is helpful to drive design choices and to check the correctness properties of the WSN at runtime. Although the method scales up to very large WSNs, the applicability of the methodology maybe compromised by the state space explosion of the reasoning model, which must be faced partitioning large topologies into sub-topologies