• Smart Structures and Systems
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• v.25 no.1
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• pp.111-122
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• 2020

Researchers up to date have introduced several Structural Health Monitoring (SHM) techniques with varying advantages and drawbacks for each. Satellite positioning systems (GPS, GLONASS and GALILEO) based techniques proved to be promising, especially for high natural period structures. Particularly, the GPS has proved sufficient performance and reasonable accuracy in tracking real time dynamic displacements of flexible structures independent of atmospheric conditions, temperature variations and visibility of the monitored object. Tall structures are particularly sensitive to oscillations produced by different sources of dynamic actions; such as typhoons. Wind forces induce in the structure both longitudinal and perpendicular displacements with respect to the wind direction, resulting in torsional effects, which are usually more complex to be detected. To efficiently track the horizontal rotations of the in-plane sections of such flexible structures, two main issues have to be considered: a suitable sensor topology (i.e., location, installation, and combination of sensors), and the methodology used to process the data recorded by sensors. This paper reports the contributions of the measurements recorded from dual frequency GPS receivers and uni-axial accelerometers in a full-scale experimental campaign. The Canton tower in Guangzhou-China is the case study of this research, which is instrumented with a long-term structural health monitoring system deploying both accelerometers and GPS receivers. The elaboration of combining the obtained rather long records provided by these two types of sensors in detecting the torsional behavior of the tower under ambient vibration condition and during strong wind events is discussed in this paper. Results confirmed the reliability of GPS receivers in obtaining the dynamic characteristics of the system, and its ability to capture the torsional response of the tower when used alone or when they are combined with accelerometers integrated data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.389-391
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• 2022

Efforts by the Ministry of Environment and local governments in Korea are continuing to manage the aging of water supply and sewage buried underground. With the support of the Korea Institute of Environmental Industry and Technology's water and sewage innovation technology development project, it is conducting a project to predict and exchange accidents due to aging, and to apply smart functions to new buried pipes. As one of these studies, this paper proposes the design of a dashboard concept model for digital twin-based smart pipe health monitoring, one of the key features of the entire study. Since remote control and monitoring are one of the main functions, distributed transmission and reception agents are deployed to visualize monitoring situations in real time and to increase user affinity by deploying intuitive UI. To validate the design of this proposed special digital twin based smart pipe state monitoring, we construct the conceptual model level and measure the agent effectiveness to validate its excellence.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.183-189
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• 2021

In recent years, active research has been devoted toward developing a monitoring system using ambient vibration data in order to quantitatively determine the deterioration occurring in a structure over a long period of time. This study developed a low-cost edge computing system that detects the abnormalities in structures by utilizing the dynamic characteristics acquired from the structure over the long term for ensemble learning. The system hardware consists of the Raspberry Pi, an accelerometer, an inclinometer, a GPS RTK module, and a LoRa communication module. The structural abnormality detection afforded by the ensemble learning using dynamic characteristics is verified using a laboratory-scale structure model vibration experiment. A real-time distributed processing algorithm with dynamic feature extraction based on the experiment is installed on the Raspberry Pi. Based on the stable operation of installed systems at the Community Service Center, Pohang-si, Korea, the validity of the developed system was verified on-site.

• Journal of Korean Society of Steel Construction
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• v.23 no.5
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• pp.629-636
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• 2011

This paper describes the smart structural system that uses smart materials for real-time monitoring and active control of bolted joints in steel structures. The impedance-based structural health monitoring (SHM) techniques, which utilize the electro-mechanical coupling property of piezoelectric materials, was used to detect loose bolts in bolted joints. By monitoring the measured electrical impedance and comparing it with the measured baseline, a bolt loosening damage was detected. The damage was evaluated quantitatively using the damage metrics in conductance signature with respect to the healthy states. When loosening damage was detected in the bolted joint, the external heater actuated the shape memory alloy (SMA) washer. Then the heated SMA washer expanded axially and adjusted the bolt tension to restore the lost torque. An experiment was conducted by integrating the piezoelectric-material-based SHM function and the SMA-based active control function on a bolted joint, after which the performance of thesmart self-healing joint system was investigated.

• Biomedical Science Letters
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• v.29 no.4
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• pp.363-370
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• 2023

Human respiratory viral infections such as COVID-19 are highly contagious, so continuous management of airborne viruses is essential. In particular, indoor air monitoring is necessary because the risk of infection increases in poorly ventilated indoors. However, the current method of detecting airborne viruses requires a lot of time from sample collection to confirmation of results. In this study, we proposed a system that can monitor airborne viruses in real time to solve the deficiency of the present method. Air samples were collected in liquid form through a bio sampler, in which case the virus is present in low concentrations. To detect viruses from low-concentration samples, viral RNA was concentrated and extracted using silica-magnetic beads. RNA binds to silica under certain conditions, and by repeating this binding reaction, bulk samples collected from the air can be concentrated. After concentration and extraction, viral RNA is specifically detected through real-time qPCR (quantitative polymerase chain reaction). In addition, based on liquid handling technology, we have developed an automatic machine that automatically performs the entire testing process and can be easily used even by non-experts. To evaluate the system, we performed air sample collection and automated testing using bacteriophage MS2 as a model virus. As a result, the air-collected samples concentrated by 45 times then initial volume, and the detection sensitivity of PCR also confirmed a corresponding improvement.

• Smart Media Journal
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• v.11 no.9
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• pp.30-38
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• 2022

It is important to grasp biometric data in real time for prompt action in the event of a safety accident at a work site where the risk of safety accidents exists. Among them, blood oxygen saturation is the most important factor in maintaining human life, so real-time oxygen saturation measurement and monitoring is necessary according to the situation as a preemptive response for worker safety management. By receiving real-time bio-signals from workers wearing health and life-risk protective clothing, and sharing and analyzing the worker's risk status in an external system, it is possible to diagnose the worker's current condition and efficiently respond to emergencies that may occur to the worker. In this paper, we propose a wearable oxygen saturation measurement platform technology that can monitor the risk of harmful gases and oxygen saturation of the wearer in real time and ensure the wearer's activity and safety in order to cope with emergency situations at the scene of an accident. If we overcome the limitations identified through the results of the proposed system later and apply improved biodata such as motion correction to the platform, we expect that it will be usable not only in hazardous gas environments, but also in hospitals and homes for emergency patients.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.3
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• pp.199-203
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• 2016

The cost needed to managing equipment is constantly increasing because of increase of power equipment. The regulations such as PAS 55 and ISO 55000 were enacted to manage equipment assets. The advanced management methods such as real-time monitoring, condition evaluation, and health indices are avalable in generation system, transmission system, and substation transformers. However, These methods can not be applied to distribution equipment because of a lot of equipment. Therefore reliability assessment is very important in case of distribution equipment. In this paper, failure rates are extracted considering characteristics of regions, and which are the essential factors to reliability evaluation.

• Journal of Environmental Health Sciences
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• v.43 no.3
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• pp.214-222
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• 2017

Objectives: A hospital is a complex building that serves many different purposes. The indoor environment in a hospital plays a major role in patient well-being and the work efficiency of the hospital staff. This study was conducted to evaluate overall comfort in two major hospitals over the course of one year. Methods: Various indoor environmental conditions were measured in two general hospitals for one year (April 2014 to April 2015). Monitoring alternated between the hospitals at one month per respective monitoring session. The indoor air temperature, relative humidity (RH), mean radiant temperature and air velocity were measured in order to calculate the predicted mean vote (PMV). Carbon dioxide concentration, noise level and illumination level were concurrently measured and applied to the overall IEQ acceptance model for the hospitals (IEQh). Results: The IEQh at the two general hospitals was different at five spaces within a building. The IEQh for summer and winter were significantly different. Real-time IEQh demonstrated that indoor comfort was affected by the hospital's operating hours due to operation of the HVAC system. The percentage of indoor comfort in the hospitals was higher using PMV than IEQh. Conclusion: IEQh in the hospitals was different at locations with different purposes. Indoor comfort assessment using IEQh was stricter than with PMV. Additional research is needed in order to optimize the IEQh model.

• Journal of Sensor Science and Technology
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• v.21 no.5
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• pp.352-358
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• 2012

A sensor network system can be an efficient tool for healthcare telemetry for multiple users due to its power efficiency. One drawback is its limited data size. This paper proposed a real-time application of data compression/decompression method in u-Health monitoring system in order to improve the network efficiency. Our high priority was given to maintain a high quality of signal reconstruction since it is important to receive undistorted waveform. Our method consisted of down sampling coding and differential Huffman coding. Down sampling was applied based on the Nyquist-Shannon sampling theorem and signal amplitude was taken into account to increase compression rate in the differential Huffman coding. Our method was successfully tested in a ZigBee and WLAN dual network. Electrocardiogram (ECG) had an average compression ratio of 3.99 : 1 with 0.24% percentage root mean square difference (PRD). Photoplethysmogram (PPG) showed an average CR of 37.99 : 1 with 0.16% PRD. Our method produced an outstanding PRD compared to other previous reports.

• Journal of Sensor Science and Technology
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• v.18 no.5
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• pp.337-342
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• 2009

This paper describes a robust mobile u-healthcare system with multiple physiological signs measurement capability in real time with integration of WSN(wireless sensor network) technology and CDMA(code division multiple access) network. A cellular phone receives health data in WSN and performs local physiological signs analysis at a phone processor, and then transmits abnormal data to server for further detail or precise health signal evaluation by a medical doctor over a CDMA network. Physiological signs of the patients are continuously monitored, processed and analyzed locally at cellular phone process to produce useful medical information for diagnosis and tracking purposes. By local simple analysis in cellular phone processor we can save the data transmission cost in CDMA network. By using the developed integrate ubiquitous healthcare service architecture, patients can realize self-health checking so that the prevention actions can be taken earlier. Appropriate self-monitoring and self-management can cure disease and relieve pain especially for patients who suffer from chronic diseases that need long term observation.