An Intelligent Monitoring System for the Safety of Building Structure under the W2T Framework

Monitoring systems for the safety of building structure (SBS) can provide people with important data related to main supporting points in a building and then help people to make a reasonable maintenance schedule. However, more and more data bring a challenge for data management and data mining. In o...

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Main Authors: Haiyuan Wang, Zhisheng Huang, Ning Zhong, Jiajin Huang, Yuzhong Han, Feng Zhang
Format: Article
Language:English
Published: Wiley 2015-08-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2015/378694
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author Haiyuan Wang
Zhisheng Huang
Ning Zhong
Jiajin Huang
Yuzhong Han
Feng Zhang
author_facet Haiyuan Wang
Zhisheng Huang
Ning Zhong
Jiajin Huang
Yuzhong Han
Feng Zhang
author_sort Haiyuan Wang
collection DOAJ
description Monitoring systems for the safety of building structure (SBS) can provide people with important data related to main supporting points in a building and then help people to make a reasonable maintenance schedule. However, more and more data bring a challenge for data management and data mining. In order to meet this challenge, under the framework of Wisdom Web of Things (W2T), we design a monitoring system for the SBS by using the semantic and the multisource data fusion technologies. This system establishes a dynamical data cycle among the physical world (buildings), the social world (humans), and the cyber world (computers) and provides various services in the monitoring process to alleviate engineers’ workload. Furthermore, all data in the cyber world are organized as the raw data, the semantic information, and the multisource knowledge. Based on this organization, we can concentrate on the data fusion from the viewpoints of time, space, and multisensor. At last, a prototype system powered by the semantic platform LarKC is tested from the aspects of sample performance and time consumption. In particular, noisy data (i.e., inconsistent, abnormal, or error data) are detected through the fusion of multisource knowledge, and some rule-based reasoning is conducted to provide personalized service.
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spelling doaj-art-61b49f9f9e8b4dfda43a99df29fe6b922025-08-20T03:19:28ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-08-011110.1155/2015/378694378694An Intelligent Monitoring System for the Safety of Building Structure under the W2T FrameworkHaiyuan Wang0Zhisheng Huang1Ning Zhong2Jiajin Huang3Yuzhong Han4Feng Zhang5 International WIC Institute, Beijing University of Technology, Beijing 100124, China Knowledge Representation and Reasoning Group, Vrije University Amsterdam, 1081 HV Amsterdam, Netherlands Department of Life Science and Informatics, Maebashi Institute of Technology, Maebashi 371-0816, Japan International WIC Institute, Beijing University of Technology, Beijing 100124, China China Academy of Building Research, Beijing 100013, China China Academy of Building Research, Beijing 100013, ChinaMonitoring systems for the safety of building structure (SBS) can provide people with important data related to main supporting points in a building and then help people to make a reasonable maintenance schedule. However, more and more data bring a challenge for data management and data mining. In order to meet this challenge, under the framework of Wisdom Web of Things (W2T), we design a monitoring system for the SBS by using the semantic and the multisource data fusion technologies. This system establishes a dynamical data cycle among the physical world (buildings), the social world (humans), and the cyber world (computers) and provides various services in the monitoring process to alleviate engineers’ workload. Furthermore, all data in the cyber world are organized as the raw data, the semantic information, and the multisource knowledge. Based on this organization, we can concentrate on the data fusion from the viewpoints of time, space, and multisensor. At last, a prototype system powered by the semantic platform LarKC is tested from the aspects of sample performance and time consumption. In particular, noisy data (i.e., inconsistent, abnormal, or error data) are detected through the fusion of multisource knowledge, and some rule-based reasoning is conducted to provide personalized service.https://doi.org/10.1155/2015/378694
spellingShingle Haiyuan Wang
Zhisheng Huang
Ning Zhong
Jiajin Huang
Yuzhong Han
Feng Zhang
An Intelligent Monitoring System for the Safety of Building Structure under the W2T Framework
International Journal of Distributed Sensor Networks
title An Intelligent Monitoring System for the Safety of Building Structure under the W2T Framework
title_full An Intelligent Monitoring System for the Safety of Building Structure under the W2T Framework
title_fullStr An Intelligent Monitoring System for the Safety of Building Structure under the W2T Framework
title_full_unstemmed An Intelligent Monitoring System for the Safety of Building Structure under the W2T Framework
title_short An Intelligent Monitoring System for the Safety of Building Structure under the W2T Framework
title_sort intelligent monitoring system for the safety of building structure under the w2t framework
url https://doi.org/10.1155/2015/378694
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