Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/18851
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dc.contributor.authorNuhu Kontagora, Bello-
dc.contributor.authorIbrahim, Aliyu-
dc.contributor.authorMutiu Adesina, Adebgoye-
dc.contributor.authorJe Kyeong, Ryu-
dc.contributor.authorOlaniyi, Olayemi Mikail-
dc.contributor.authorChang Gyoon, Lim-
dc.date.accessioned2023-05-11T10:41:15Z-
dc.date.available2023-05-11T10:41:15Z-
dc.date.issued2020-11-16-
dc.identifier.citationNuhu, B. K., Olaniyi, O. M., I. Aliyu, JeKyeong R., and C. G Lim (2019). Wireless Sensor Network-based Structural Health Monitoring Expert System. International Journal of Wearable Device,6(1):9-16 Available Online at: http://dx.doi.org/10.21742/ijwd.2019.6.1.02en_US
dc.identifier.otherhttp://dx.doi.org/10.21742/ijwd.2019.6.1.02-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/18851-
dc.description.abstractStructural Health Monitoring (SHM) is a process of detecting damages to engineering structures. The goal of SHM is to improve both the safety and reliability of infrastructures such as buildings, bridges, and highways. Several efforts have been made to develop improved SHM systems. However, most of these studies only considered vibration as a monitoring parameter without incorporating expert systems based on fuzzy inference. In this work, an expert system was incorporated into SHM for monitoring residential buildings based on building temperature and vibration measurements. The developed system used a Wireless Sensor Network (WSN) with a 2.4 GHz Radio Frequency (RF) band. Results of the system performance evaluation indicated a decrease in reliability from 99% to 50% within a decade of its deployment. In terms of energy conservation, results showed that the system was able to save 30% of energy, thereby increasing its lifetime. The fuzzy expert SHM system is able to detect building conditions with a good level of reliability, energy conservation capability and high accuracy of 94.4% and 100% as the least and best performance, respectively. Hence, direct integration of this system into building structures could aid early detection of building impairment.en_US
dc.language.isoenen_US
dc.publisherBuilding Research & Informationen_US
dc.subjectWireless sensor networken_US
dc.subjectexpert systemen_US
dc.subjectFuzzy logicen_US
dc.subjectSHMen_US
dc.titleDistributed network-based structural health monitoring expert systemen_US
dc.typeArticleen_US
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