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dc.contributor.authorNuhu, B.K.-
dc.contributor.authorOlaniyi, Olayemi Mikail-
dc.contributor.authorAliyu, Ibrahim-
dc.contributor.authorJeKyeong, Ryu-
dc.contributor.authorLim, C. G-
dc.date.accessioned2021-07-08T16:04:07Z-
dc.date.available2021-07-08T16:04:07Z-
dc.date.issued2019-
dc.identifier.citationNuhu, B. K., Olaniyi, O. M., I. Aliyu, JeKyeong Ryu, and C. G Lim (2019). Wireless Sensor Network based Structural Health Monitoring Expert System. International Journal of Wearable Device,6(1):9-16en_US
dc.identifier.urihttp://dx.doi.org/10.21742/ijwd.2019.6.1.02-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/7495-
dc.descriptionWireless Sensor Network based Structural Health Monitoring Expert Systemen_US
dc.description.abstractStructural Health Monitoring (SHM) is a process of detecting damages in Engineering structures in order to reduce the frequency of collapse of buildings. In this work, an expert system was incorporated into SHM for monitoring residential buildings. The developed system used a Wireless Sensor Network (WSN) based on a 2.4GHz Radio Frequency (RF) band. The developed expert system is based on fuzzy inference and decision-making process also based on British Standard (BS): 7385 - Evaluation and measurement for vibration in building and BS 13670:2009. From the performance evaluation result, the system’s reliability was calculated to be decreasing from 99% to 50% over a space of 100 years. Energy utilization results showed that the system has the capability to operate with 30% of its energy saved, thereby working for longer hours. The developed system showed a remarkable level of reliability and the energy-saving capability is good. Hence, the system is adequate for SHM.en_US
dc.language.isoenen_US
dc.publisherGlobal Vision Press Australiaen_US
dc.subjectStructural health monitoringen_US
dc.subjectWireless sensor networken_US
dc.subjectExpert systemen_US
dc.titleWireless Sensor Network based Structural Health Monitoring Expert Systemen_US
dc.typeArticleen_US
Appears in Collections:Computer Engineering

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