Internet of Things (IoT) Platform for Structure Health Monitoring

Increase in the demand for reliable structural health information led to the development of Structural Health Monitoring (SHM). Prediction of upcoming accidents and estimation of useful life span of a structure are facilitated through SHM. While data sensing is the core of any SHM, tracking the data...

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Main Authors: Ahmed Abdelgawad, Kumar Yelamarthi
Format: Article
Language:English
Published: Hindawi-Wiley 2017-01-01
Series:Wireless Communications and Mobile Computing
Online Access:http://dx.doi.org/10.1155/2017/6560797
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spelling doaj-83af02560af54eea864bb8e2e9589b4f2020-11-25T01:00:17ZengHindawi-WileyWireless Communications and Mobile Computing1530-86691530-86772017-01-01201710.1155/2017/65607976560797Internet of Things (IoT) Platform for Structure Health MonitoringAhmed Abdelgawad0Kumar Yelamarthi1School of Engineering & Technology, Central Michigan University, ET100, Mount Pleasant, MI 48859, USASchool of Engineering & Technology, Central Michigan University, ET100, Mount Pleasant, MI 48859, USAIncrease in the demand for reliable structural health information led to the development of Structural Health Monitoring (SHM). Prediction of upcoming accidents and estimation of useful life span of a structure are facilitated through SHM. While data sensing is the core of any SHM, tracking the data anytime anywhere is a prevailing challenge. With the advancement in information technology, the concept of Internet of Things (IoT) has made it possible to integrate SHM with Internet to track data anytime anywhere. In this paper, a SHM platform embedded with IoT is proposed to detect the size and location of damage in structures. The proposed platform consists of a Wi-Fi module, a Raspberry Pi, an Analog to Digital Converter (ADC), a Digital to Analog Converter (DAC), a buffer, and piezoelectric (PZT) sensors. The piezoelectric sensors are mounted as a pair in the structure. Data collected from the piezoelectric sensors will be used to detect the size and location of damage using a proposed mathematical model. Implemented on a Raspberry Pi, the proposed mathematical model will estimate the size and location of structural damage, if any, and upload the data to Internet. This data will be stored and can be checked remotely from any mobile device. The system has been validated using a real test bed in the lab.http://dx.doi.org/10.1155/2017/6560797
collection DOAJ
language English
format Article
sources DOAJ
author Ahmed Abdelgawad
Kumar Yelamarthi
spellingShingle Ahmed Abdelgawad
Kumar Yelamarthi
Internet of Things (IoT) Platform for Structure Health Monitoring
Wireless Communications and Mobile Computing
author_facet Ahmed Abdelgawad
Kumar Yelamarthi
author_sort Ahmed Abdelgawad
title Internet of Things (IoT) Platform for Structure Health Monitoring
title_short Internet of Things (IoT) Platform for Structure Health Monitoring
title_full Internet of Things (IoT) Platform for Structure Health Monitoring
title_fullStr Internet of Things (IoT) Platform for Structure Health Monitoring
title_full_unstemmed Internet of Things (IoT) Platform for Structure Health Monitoring
title_sort internet of things (iot) platform for structure health monitoring
publisher Hindawi-Wiley
series Wireless Communications and Mobile Computing
issn 1530-8669
1530-8677
publishDate 2017-01-01
description Increase in the demand for reliable structural health information led to the development of Structural Health Monitoring (SHM). Prediction of upcoming accidents and estimation of useful life span of a structure are facilitated through SHM. While data sensing is the core of any SHM, tracking the data anytime anywhere is a prevailing challenge. With the advancement in information technology, the concept of Internet of Things (IoT) has made it possible to integrate SHM with Internet to track data anytime anywhere. In this paper, a SHM platform embedded with IoT is proposed to detect the size and location of damage in structures. The proposed platform consists of a Wi-Fi module, a Raspberry Pi, an Analog to Digital Converter (ADC), a Digital to Analog Converter (DAC), a buffer, and piezoelectric (PZT) sensors. The piezoelectric sensors are mounted as a pair in the structure. Data collected from the piezoelectric sensors will be used to detect the size and location of damage using a proposed mathematical model. Implemented on a Raspberry Pi, the proposed mathematical model will estimate the size and location of structural damage, if any, and upload the data to Internet. This data will be stored and can be checked remotely from any mobile device. The system has been validated using a real test bed in the lab.
url http://dx.doi.org/10.1155/2017/6560797
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