• Title/Summary/Keyword: real-time health monitoring system

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Safety Evaluation on Real Time Operating Systems for Safety-Critical Systems (안전필수(Safety-Critical) 시스템의 실시간 운영체제에 대한 안전성 평가)

  • Kang, Young-Doo;Chong, Kil-To
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.10
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    • pp.3885-3892
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    • 2010
  • Safety-Critical systems, such as Plant Protection Systems in nuclear power plant, plays a key role that the facilities can be operated without undue risk to the health and safety of public and environment, and those systems shall be designed, fabricated, installed, and tested to quality standards commensurate with the importance of the functions to be performed. Computer-based Instrumentation and Control Systems to perform the safety-critical function have Real Time Operating Systems to control and monitoring the sub-system and executing the application software. The safety-critical Real Time Operating Systems shall be designed, analyzed, tested and evaluated to have capability to maintain a high integrity and quality. However, local nuclear power plants have applied the real time operating systems on safety critical systems through Commercial Grade Item Dedication method, and this is the reason of lack of detailed methodology on assessing the safety of real time operating systems, expecially to the new developed one. This paper presents the methodology and experiences of safety evaluation on safety-critical Real Time Operating Systems based upon design requirements. This paper may useful to develop and evaluate the safety-critical Real Time Operating Systems in other industry to ensure the safety of public and environment.

Evaluation on real-time multi-point sensing performance of IoT-based hybrid measurement system (IoT 기반 하이브리드 계측시스템 실시간 다점 측정 성능 평가)

  • Kim, Heonyoung;Kang, Donghoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.4
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    • pp.543-550
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    • 2018
  • The rapid growth of IoT technology induced by the fourth industrial revolution has resulted in research into various types of wireless sensors, and applications based on this technology are prevalent in many areas. However, among the various sites where this technology is used, railway bridges and tunnels with lengths of tens of kilometers have problems with data acquisition, due to the signal noise induced by the long distance measurement and EMI induced by the high voltage power feeding system, when conventional electric sensors are used. To overcome these problems, many studies on fiber optic sensors have been conducted as a substitute for the conventional electric sensors. However, restrictions on the types of fiber optic sensors have limited their application in railways. For this reason, a hybrid measurement system with IoT based wireless data communication, in which both electric and fiber optic sensors can be applied simultaneously, has been developed. In this study, in order to evaluate the applicability of the hybrid measurement system developed in the previous study, a real-time test for 4 types of measurement environments, which reflect possible railway sites, is performed. As a result, it was confirmed that the signals from both the electric and fiber optic sensors, which were acquired at a remote area in real-time, showed good agreement with each other and that this measurement system has the potential to handle sensors with a sampling rate of 2.5 kHz. In the future, it is expected that the IoT-based hybrid measurement system will contribute to the improvement of structural safety by enabling real-time structural health monitoring when applied to various measurement sites.

A Development of Maintenance Decision Support System for Gas Turbine Engine (가스터빈 엔진 정비 의사결정 지원시스템 개발)

  • Ki, Ja-Young;Kang, Myoung-Cheol;Lee, Myung-Kuk;Rho, Hong-Suk
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2012.05a
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    • pp.586-591
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    • 2012
  • The solution of maintenance decision support system for the gas turbine engine, which is currently operating in GUNSAN combined cycle power plant, was developed and is consist of online monitoring module, periodic performance trending module, optimal compressor washing interval analysis module and hot component management module. Also, GUI platform was applied to this solution for the user to monitoring the analyzed result of engine performance condition and then to make a decision of the consequent maintenance action. In online condition monitoring module, the performance degradation of engine is provided by the analysis of difference between the real time measurement data compared to exist engine performance. The optimal compressor washing interval module produced the washing interval of maximum net profit value by researching the maintenance expense and the loss profit value corresponds to the performance degradation with economic assessment algorithm. Thus, this solution support the user to enable the optimal maintenance and operation of gas turbine engine with overall analysis of engine condition and main information.

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Partially Observable Markov Decision Processes (POMDPs) and Wireless Body Area Networks (WBAN): A Survey

  • Mohammed, Yahaya Onimisi;Baroudi, Uthman A.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.5
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    • pp.1036-1057
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    • 2013
  • Wireless body area network (WBAN) is a promising candidate for future health monitoring system. Nevertheless, the path to mature solutions is still facing a lot of challenges that need to be overcome. Energy efficient scheduling is one of these challenges given the scarcity of available energy of biosensors and the lack of portability. Therefore, researchers from academia, industry and health sectors are working together to realize practical solutions for these challenges. The main difficulty in WBAN is the uncertainty in the state of the monitored system. Intelligent learning approaches such as a Markov Decision Process (MDP) were proposed to tackle this issue. A Markov Decision Process (MDP) is a form of Markov Chain in which the transition matrix depends on the action taken by the decision maker (agent) at each time step. The agent receives a reward, which depends on the action and the state. The goal is to find a function, called a policy, which specifies which action to take in each state, so as to maximize some utility functions (e.g., the mean or expected discounted sum) of the sequence of rewards. A partially Observable Markov Decision Processes (POMDP) is a generalization of Markov decision processes that allows for the incomplete information regarding the state of the system. In this case, the state is not visible to the agent. This has many applications in operations research and artificial intelligence. Due to incomplete knowledge of the system, this uncertainty makes formulating and solving POMDP models mathematically complex and computationally expensive. Limited progress has been made in terms of applying POMPD to real applications. In this paper, we surveyed the existing methods and algorithms for solving POMDP in the general domain and in particular in Wireless body area network (WBAN). In addition, the papers discussed recent real implementation of POMDP on practical problems of WBAN. We believe that this work will provide valuable insights for the newcomers who would like to pursue related research in the domain of WBAN.

Overall damage identification of flag-shaped hysteresis systems under seismic excitation

  • Zhou, Cong;Chase, J. Geoffrey;Rodgers, Geoffrey W.;Xu, Chao;Tomlinson, Hamish
    • Smart Structures and Systems
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    • v.16 no.1
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    • pp.163-181
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    • 2015
  • This research investigates the structural health monitoring of nonlinear structures after a major seismic event. It considers the identification of flag-shaped or pinched hysteresis behavior in response to structures as a more general case of a normal hysteresis curve without pinching. The method is based on the overall least squares methods and the log likelihood ratio test. In particular, the structural response is divided into different loading and unloading sub-half cycles. The overall least squares analysis is first implemented to obtain the minimum residual mean square estimates of structural parameters for each sub-half cycle with the number of segments assumed. The log likelihood ratio test is used to assess the likelihood of these nonlinear segments being true representations in the presence of noise and model error. The resulting regression coefficients for identified segmented regression models are finally used to obtain stiffness, yielding deformation and energy dissipation parameters. The performance of the method is illustrated using a single degree of freedom system and a suite of 20 earthquake records. RMS noise of 5%, 10%, 15% and 20% is added to the response data to assess the robustness of the identification routine. The proposed method is computationally efficient and accurate in identifying the damage parameters within 10% average of the known values even with 20% added noise. The method requires no user input and could thus be automated and performed in real-time for each sub-half cycle, with results available effectively immediately after an event as well as during an event, if required.

Wireless sensor networks for permanent health monitoring of historic buildings

  • Zonta, Daniele;Wu, Huayong;Pozzi, Matteo;Zanon, Paolo;Ceriotti, Matteo;Mottola, Luca;Picco, Gian Pietro;Murphy, Amy L.;Guna, Stefan;Corra, Michele
    • Smart Structures and Systems
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    • v.6 no.5_6
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    • pp.595-618
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    • 2010
  • This paper describes the application of a wireless sensor network to a 31 meter-tall medieval tower located in the city of Trento, Italy. The effort is motivated by preservation of the integrity of a set of frescoes decorating the room on the second floor, representing one of most important International Gothic artworks in Europe. The specific application demanded development of customized hardware and software. The wireless module selected as the core platform allows reliable wireless communication at low cost with a long service life. Sensors include accelerometers, deformation gauges, and thermometers. A multi-hop data collection protocol was applied in the software to improve the system's flexibility and scalability. The system has been operating since September 2008, and in recent months the data loss ratio was estimated as less than 0.01%. The data acquired so far are in agreement with the prediction resulting a priori from the 3-dimensional FEM. Based on these data a Bayesian updating procedure is employed to real-time estimate the probability of abnormal condition states. This first period of operation demonstrated the stability and reliability of the system, and its ability to recognize any possible occurrence of abnormal conditions that could jeopardize the integrity of the frescos.

Pulse wave analysis system using wrist type oximeter for u-Health service (u-Health 서비스 지원을 위한 착용형 옥시미터를 이용한 맥파 분석 시스템)

  • Jung, Sang-Joong;Seo, Yong-Su;Chung, Wan-Young
    • Journal of Sensor Science and Technology
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    • v.19 no.1
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    • pp.17-24
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    • 2010
  • This paper describes a real time reliable monitoring method and analysis system using wrist type oximeter for ubiquitous healthcare service based on IEEE 802.15.4 standard. Photoplethysmograph(PPG) is simple and cost effective technique to measure blood volume change. In order to obtain and monitor physiological body signals continuously, a small size and low power consumption wrist type oximeter is designed for the measurement of oxygen saturation of a patient unobtrusively. The measured data is transferred to a central PC or server computer by using wireless sensor nodes in wireless sensor network for storage and analysis purposes. LabVIEW server program is designed to monitor stress indicator from heart rate variability(HRV) and process the measured PPG to accelerated plethysmograph(APG) by appling second order derivatives in server PC. These experimental results demonstrate that APG can precisely describe the features of an individual's PPG and be used as estimation of vascular elasticity for blood circulation.

Development of Personalized Respiratory Training Device with Real-time Feedback for Respiratory Muscle Strengthening

  • Merve Nur Uygun;Yeong-geol Bae;Yejin Choi;Dae-Sung Park
    • Physical Therapy Rehabilitation Science
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    • v.12 no.3
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    • pp.251-258
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    • 2023
  • Objective: The practice of breathing exercises involves altering the depth and frequency of respiration. Strengthening respiratory muscles plays a crucial role in maintaining overall health and well-being. The efficiency of the respiratory system affects not only physical activity but also various physiological processes including cardiovascular health, lung function, and cognitive abilities. The study evaluated the reliability of the developed device for inspiratory/expiratory training using pressure sensors and Bluetooth connectivity with a smartphone application. Design: Design & development research Methods: The research methodology involved connecting a custom-made respiratory sensor to an IMT-PEP BIC Breath device. Various pressure conditions were measured, and statistical analyses were performed to assess reliability and consistency. Results showed high Intraclass Coefficient Correlation (ICC) values for both inspiratory and expiratory pressures, indicating strong test-retest reliability. The device was designed for ease of use and wireless monitoring through a smartphone app. Results: This study conducted at expiratory pressure confirmed the proper operation of the IMT/PEP breathing trainer at the specified pressure setting in the product. The pressure sensor demonstrated high test-retest reliability with an ICC value of 0.999 for both expiratory and inspiratory pressure measurements. Conclusions: The developed respiratory training device measured and monitored inspiratory and expiratory pressures, demonstrating its reliability for respiratory training. The system could be utilized to record training frequency and intensity, providing potential benefits for patients requiring respiratory interventions. Further research is needed to assess the full potential of the device in diverse populations and applications.

Indoor Air Quality Monitoring Systems in the IoT Environment (IoT 기반 실내 공기질 모니터링 시스템)

  • Oh, Chang-Se;Seo, Min-Seok;Lee, Jung-Hyuck;Kim, Sang-Hyun;Kim, Young-Don;Park, Hyun-Ju
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.5
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    • pp.886-891
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    • 2015
  • Recently, The World Health Organization announced that harms human health because of air pollution that are emerging as threats to human health worldwide. according to the, Seoul, 2011 According to a July 2014 - Public Facilities indoor air quality measurements, were examined to be in violation of indoor air pollution standards in most multi-use facility. Indoor air pollution resulting from this is present in the paper, and cause disease, such as pulmonary disease, asthma, bronchitis and to In this connection, the measurement of indoor air quality by using the environment sensor, analyzing the measured data to generate an actuator signal required for ventilation and improve indoor air quality by implementing a monitoring system with real-time measurement, autonomously managing the air quality in our lives so that it can be.

A study on the recognition of odor in Wonju traditional market, Gangwon-do

  • Jung, Min-Jae;LEE, Woo-Sik;JEONG, Tae-Hwan;Kim, Su-Hye
    • Journal of Wellbeing Management and Applied Psychology
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    • v.5 no.3
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    • pp.43-49
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    • 2022
  • Purpose: This study aims to study the perception of merchants and customers about the odor problem of traditional markets in Wonju, Gangwon-do. Research design, data and methodology: A survey was conducted to investigate the perception. The survey consisted of 11 questions for merchants and 12 questions for customers. Results: In a survey of merchants - The question 'What kind of smell did you smell at the traditional market?' was investigated with multiple responses. Regarding the odor experience, unclean odor was the highest with 105 votes (36%), followed by rotting odor with 82 votes (28.1%) and other odors with 44 votes (15.1%). In a survey of customers - The question 'What kind of smell did you smell at the traditional market?' was investigated with multiple responses. As a result of the survey, filthy smell was the highest with 98 votes (43.2%). Next, rotten smell was found with 60 votes (26.4%) and others with 31 votes (13.7%). Conclusions: If the odor problem in the traditional market is solved, the economic and health damage to the merchants will be reduced. Further, it will help to revitalize traditional markets by increasing customer visits. As a solution, it is judged that it is good to study the direction of the establishment of a real-time monitoring system and the preparation and application of odor removal measures.