• Nuclear Engineering and Technology
• /
• v.43 no.2
• /
• pp.99-104
• /
• 2011

A Structure Health Monitoring (SHM) system needs a real-time remote data acquisition system to monitor the status of a structure from anywhere via Internet access. In this paper, we present a data acquisition system that monitors up to 40 Fiber Bragg Grating Sensors remotely in real-time. Using a TCP/IP protocol, users can access information gathered by the sensors from anywhere. An experiment in laboratory conditions has been done to prove the feasibility of our proposed system, which is built in special-purpose monitoring system.

• Journal of Sensor Science and Technology
• /
• v.23 no.1
• /
• pp.7-14
• /
• 2014

Noncontact electrocardiogram (ECG) measurement using capacitive-coupled technique is a very reliable long-term noninvasive health-care remote monitoring system. It can be used continuously without interrupting the daily activities of the user and is one of the most promising developments in health-care technology. However, ECG signal is a very small electric signal. A robust system is needed to separate the clean ECG signal from noise in the measurement environment. Noise may come from many sources around the system, for example, bad contact between the sensor and body, common-mode electrical noise, movement artifacts, and triboelectric effect. Thus, in this paper, the extended Kalman filter (EKF) is applied to denoise a real-time ECG signal in capacitive-coupled sensors. The ECG signal becomes highly stable and noise-free by combining the common analog signal processing and the digital EKF in the processing step. Furthermore, to achieve ubiquitous monitoring, android-based application is developed to process the heart rate in a realtime ECG measurement.

• Smart Structures and Systems
• /
• v.4 no.6
• /
• pp.759-777
• /
• 2008

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

• Safety and Health at Work
• /
• v.13 no.1
• /
• pp.40-50
• /
• 2022

Background: Underground mines have several hazards that could lead to serious consequences if they come into effect. Acquiring, evaluating, and using the real-time data from the atmospheric monitoring system and miner's positional information is crucial in deciding the best course of action. Methods: A graphical user interface-based software is developed that uses an AutoCAD-based mine map, real-time atmospheric monitoring system, and miners' positional information to guide on the shortest route to mine exit and other locations within the mine, including the refuge chamber. Several algorithms are implemented to enhance the visualization of the program and guide the miners through the shortest routes. The information relayed by the sensors and communicated by other personnel are collected, evaluated, and used by the program in proposing the best course of action. Results: The program was evaluated using two case studies involving rescue relating to elevated carbon monoxide levels and increased temperature simulating fire scenarios. The program proposed the shortest path from the miner's current location to the exit of the mine, nearest refuge chamber, and the phone location. The real-time sensor information relayed by all the sensors was collected in a comma-separated value file. Conclusion: This program presents an important tool that aggregates information relayed by sensors to propose the best rescue strategy. The visualization capability of the program allows the operator to observe all the information on a screen and monitor the rescue in real time. This program permits the incorporation of additional sensors and algorithms to further customize the tool.

• International journal of advanced smart convergence
• /
• v.12 no.3
• /
• pp.104-108
• /
• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.

• Journal of Environmental Health Sciences
• /
• v.43 no.4
• /
• pp.267-272
• /
• 2017

Objectives: The purposes of the study were to analyze the temporal variation of carbon dioxide ($CO_2$) and particulate matter (PM) in daycare centers and evaluate the appropriateness of the official test method of one-time measurement. Methods: Indoor air quality in 46 daycare centers in the Seoul Metropolitan Area was measured as specified in the official test method of Indoor Air Quality Management law. In addition, indoor air quality in the 46 daycare centers was measured over 37 days using a real-time monitor (AirGuard K). Results: The daily means of $CO_2$ and PM in the 46 daycare centers were $1042.74{\pm}134.45ppm$ and $67.60{\pm}18.25{\mu}g/m^3$, respectively. Indoor air quality in the daycare centers showed significant temporal fluctuation. Measurements for single days were significantly different from the 37-day average exposure. Relative error of short term exposure decreased with an increase in the number of sampling days. The noncompliance rate for $CO_2$ using the official testing method was 2.17%, and none exceeded the $PM_{10}$ standard of $100{\mu}g/m^3$. With monitoring over 37 days, the daily noncompliance rate for $CO_2$ was 50.4% and the daily noncompliance rate for PM was 13.8%. Conclusions: When the official test method evaluates the indoor air at daycare centers one day per year, the results may not represent actual indoor air quality over a longer period of time. Real-time monitoring devices could be an alternative for managing indoor air quality.

• Structural Engineering and Mechanics
• /
• v.15 no.3
• /
• pp.285-297
• /
• 2003

Complementing recent advances made in the field of structural health monitoring and damage detection, the concept of a wireless sensing network with distributed computational power is proposed. The fundamental building block of the proposed sensing network is a wireless sensing unit capable of acquiring measurement data, interrogating the data and transmitting the data in real time. The computational core of a prototype wireless sensing unit can potentially be utilized for execution of embedded engineering analyses such as damage detection and system identification. To illustrate the computational capabilities of the proposed wireless sensing unit, the fast Fourier transform and auto-regressive time-series modeling are locally executed by the unit. Fast Fourier transforms and auto-regressive models are two important techniques that have been previously used for the identification of damage in structural systems. Their embedment illustrates the computational capabilities of the prototype wireless sensing unit and suggests strong potential for unit installation in automated structural health monitoring systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.05a
• /
• pp.308-311
• /
• 2015

Because worldwide interest in the health is increased, the real-time health monitoring system has been demanded to be more convenient non-contact and precise medical devices than conventional. Therefore we developed the blood pressure monitoring system using UWB(Ultra Wide Band) radio wave which contact to the human body through the radar and continuously collect a movement signal of the blood vessel. Then the collected data including pulse rate, systolic blood pressure, diastolic blood pressure is processed in real time. The system monitors and controls through a program-based embedded LCD(Liquid Crystal Display) using Qt GUI(Graphic User Interface) to be displayed in real time. We implement the system as a embedded system because of reducing the size of the limited resources. Existing PC GUI design mode is used relatively large memory, therefore it requires more CPU(Central Processing Unit) capacity and processing time.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.29 no.6
• /
• pp.306-315
• /
• 2017

This study introduces a software for real-time assessment of combustion stability for utility gas turbines. The software was written with LabView, and implemented the time-domain kurtosis as a parameter to proactively access the instantaneous combustion stability during operation of the industrial gas turbine. The simple time-domain assessment algorithm incorporated in the software is advantageous over conventional frequency-domain signal processing of dynamic pressure signal since it reduces the computational cost, thereby making the algorithm more appropriate for real-time monitoring of combustion stability. Benchmark data obtained from a model gas turbine combustor were used for the reproducibility test of the software. The assessment obtained from the software agreed well with previously published results, indicating that incorporation of the software could enhance the performance of systems monitoring the combustion stability for gas turbines during power generation.

• Journal of Microbiology and Biotechnology
• /
• v.22 no.9
• /
• pp.1301-1306
• /
• 2012

We combined real-time RT-PCR and real-time PCR (R/P) assays using a hydrolysis probe to detect Mycobacterium tuberculosis complex (MTBC)-specific 16S rRNA and its rRNA gene (rDNA). The assay was applied to 28 non-respiratory and 207 respiratory specimens from 218 patients. Total nucleic acids (including RNA and DNA) were extracted from samples, and results were considered positive if the repeat RT-PCR threshold cycle was ${\leq}35$ and the ratio of real-time RT-PCR and real-time PCR load was ${\geq}1.51$. The results were compared with those from existing methods, including smear, culture, and real-time PCR. Following resolution of the discrepant results between R/P assay and culture, the overall sensitivity, specificity, positive predictive values (PPV), and negative predictive values (NPV) of all samples (including non-respiratory and respiratory specimens) were 98.2%, 97.2%, 91.7%, and 99.4%, respectively, for R/P assay, and 83.9%, 89.9%, 72.3%, and 94.7%, respectively, for real-time PCR. Furthermore, the R/P assay of four patient samples showed a higher ratio before treatment than after several days of treatment. We conclude that the R/P assay is a rapid and accurate method for direct detection of MTBC, which can distinguish viable and nonviable MTBC, and thus may guide patient therapy and public health decisions.