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Special Issue "Internet of Things for Structural Health Monitoring"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 31 August 2020.

Special Issue Editors

Prof. Dr. Francesco Lamonaca
Website
Guest Editor
Università degli Studi del Sannio, Benevento, Italy
Interests: measurements; structural health monitoring; noninvasive monitoring; distributed monitoring; Internet of Things; time synchronization; wireless sensor network; signal processing; image processing; human health monitoring
Dr. Carmelo Scuro
Website
Guest Editor
Università della Calabria, Cosenza, Italy
Interests: measurements; structural health monitoring; noninvasive monitoring; distributed monitoring; Internet of Things; numerical analysis; cultural heritage; experimental analysis on construction materials; mechanical characterization of materials; genetic algorithm
Dr. Domenico Luca Carnì
Website
Guest Editor
Università della Calabria, Cosenza, Italy
Interests: measurements; structural health monitoring; noninvasive monitoring; distributed monitoring; Internet of Things; time synchronization; wireless sensor network; signal processing; automatic classifiers

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is emerging as an important technology for monitoring systems, and it is crucial in the framework of structural health monitoring for modern and ancient structures (new and cultural heritage buildings, bridges, roads, dikes, walls, monuments, and so on). This Special Issue aims to highlight advances in the open research topics in this field, which include, but are not limited to, the following:

  1. IoT-based distributed data acquisition systems for structural health monitoring;
  2. Development, modeling, testing, and metrological characterization of sensors, smart measurement instruments, and smart objects for non-invasive or semi-invasive structure monitoring;
  3. Compressive sensing;
  4. Communication network design and optimization;
  5. Energy saving and energy harvesting methods and techniques;
  6. Synchronization methods and techniques for signals and data acquisition systems;
  7. Data collection and management methods (big data and data retrieval);
  8. Automatic classifiers for danger detection, alarm generation, automatic scheduling of inspections, and maintenance activities;
  9. New numerical models describing the structural behavior of buildings and structures.

Prof. Dr. Francesco Lamonaca
Dr. Carmelo Scuro
Dr. Domenico Luca Carnì
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • IoT for structural health monitoring
  • Non-invasive monitoring
  • Semi-invasive monitoring
  • Nondestructive testing
  • Sensors for structural health
  • Compressive sensing
  • Measurement methods for structural health
  • Distributed measurement systems for structural health monitoring
  • Synchronization of signals, smart objects, and devices
  • Wireless sensor networks
  • Structural health monitoring of cultural heritage buildings and sites
  • Energy saving
  • Energy harvesting
  • Post-seismic and pre-seismic evaluation protocols
  • Big data
  • Data retrieval
  • Automatic classifiers
  • Artificial intelligence
  • Cultural heritage monitoring
  • Numerical analysis
  • Genetic algorithm

Published Papers (2 papers)

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Research

Open AccessArticle
Fuzzy-Based Approach Using IoT Devices for Smart Home to Assist Blind People for Navigation
Sensors 2020, 20(13), 3674; https://doi.org/10.3390/s20133674 - 30 Jun 2020
Abstract
The demand of devices for safe mobility of blind people is increasing with advancement in wireless communication. Artificial intelligent devices with multiple input and output methods are used for reliable data estimation based on maximum probability. A model of a smart home for [...] Read more.
The demand of devices for safe mobility of blind people is increasing with advancement in wireless communication. Artificial intelligent devices with multiple input and output methods are used for reliable data estimation based on maximum probability. A model of a smart home for safe and robust mobility of blind people has been proposed. Fuzzy logic has been used for simulation. Outputs from the internet of things (IoT) devices comprising sensors and bluetooth are taken as input of the fuzzy controller. Rules have been developed based on the conditions and requirements of the blind person to generate decisions as output. These outputs are communicated through IoT devices to assist the blind person or user for safe movement. The proposed system provides the user with easy navigation and obstacle avoidance. Full article
(This article belongs to the Special Issue Internet of Things for Structural Health Monitoring)
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Open AccessArticle
A Convolutional Neural Network for Impact Detection and Characterization of Complex Composite Structures
Sensors 2019, 19(22), 4933; https://doi.org/10.3390/s19224933 - 12 Nov 2019
Cited by 2
Abstract
This paper reports on a novel metamodel for impact detection, localization and characterization of complex composite structures based on Convolutional Neural Networks (CNN) and passive sensing. Methods to generate appropriate input datasets and network architectures for impact localization and characterization were proposed, investigated [...] Read more.
This paper reports on a novel metamodel for impact detection, localization and characterization of complex composite structures based on Convolutional Neural Networks (CNN) and passive sensing. Methods to generate appropriate input datasets and network architectures for impact localization and characterization were proposed, investigated and optimized. The ultrasonic waves generated by external impact events and recorded by piezoelectric sensors are transferred to 2D images which are used for impact detection and characterization. The accuracy of the detection was tested on a composite fuselage panel which was shown to be over 94%. In addition, the scalability of this metamodelling technique has been investigated by training the CNN metamodels with the data from part of the stiffened panel and testing the performance on other sections with similar geometry. Impacts were detected with an accuracy of over 95%. Impact energy levels were also successfully categorized while trained at coupon level and applied to sub-components with greater complexity. These results validated the applicability of the proposed CNN-based metamodel to real-life application such as composite aircraft parts. Full article
(This article belongs to the Special Issue Internet of Things for Structural Health Monitoring)
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