• Journal of Advanced Marine Engineering and Technology
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• v.40 no.1
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• pp.50-54
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• 2016

A Wireless Sensor Network (WSN) is better than a conventional network for use in construction and Operations and Maintenance (O&M) because of its lower surveillance system cost. However, effective operation of a WSN is often difficult to obtain because the surveillance targets are usually fixed inside the building or underground. Therefore, this environmental constraint should be considered in the design of the WSN plant equipment surveillance system prior to installation. This study employs simulations of WSN-based fixed facility surveillance using the TinyOS TOSSIM simulator to investigate ideal types and setups of the WSN. Simulation target protocols included LEACH and flooding and gossiping protocols. The results show that the hierarchically-structured LEACH protocol demonstrated better load-balancing and efficiency than the flatly-structured flooding and gossiping protocol.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.25-37
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• 2024

The objective of this study was to create intelligent rail robots that are optimized for facility management and implement digital twin systems for smart road tunnel management. An autonomous surveillance system is formed by combining the sensing platform consisting of railing robots, fixed cameras and environmental detection sensors with the digital twin data platform technology for tunnel monitoring and early fire suppression. In order to develop mobile rail robots for fire extinguishing, we also designed and manufactured robots for extinguishing & monitoring and fire extinguishing devices, and then we examined the optimization of all parts. Our next step was to build a digital twin for road tunnel management by developing continuous image display system and implementing 3D modeling. After constructing prototypes, we attempted simulations by configuring abnormal symptom scenarios, such as vehicles fires. This study's proposal proposes high-accuracy risk prediction services that will enable intelligent management of risks in the tunnel with early response at each stage, using the data collected from the intelligent rail robots and digital twin systems.