• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.29 no.5
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• pp.284-288
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• 2016

Among the various physiological information that could be obtained from human body, heartbeat rate is a commonly used vital sign in the clinical milieu. Photoplethysography (PPG) sensor is incorporated into many wearable healthcare devices because of its advantages such as simplicity of hardware structure and low-cost. However, healthcare device employing PPG sensor has been issued in susceptibility of light and motion artifact. In this paper, to develop the real-time heart rate measurement device that is less sensitive to the external noises, we have fabricated an ultra-small wireless LC resonant pressure sensor by MEMS process. After performance evaluation in linearity and repeatability of the MEMS pressure sensor, heartbeat waveform and rate on radial artery were obtained by using resonant frequency-pressure conversion method. The measured data using the proposed heartbeat rate measurement system was validated by comparing it with the data of an commercialized heart rate measurement device. Result of the proposed device was agreed well to that of the commercialized device. The obtained real time heartbeat wave and rate were displayed on personal mobile system by bluetooth communication.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.11a
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• pp.64-64
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• 2009

As the advanced packaging technology developing, Copper electro-plating processing has be wildly utilized in the semiconductor interconnect technique. Chemical solution monitoring methods, including PH and gravity measurement exist in industry, but economical and practical real-time monitoring has not been achieved yet. Red-green-blue (RGB) color sensor can successfully monitor the condition of $CuSO_4$ solution during electric copper plating process. Comparing the intensity variations of the RGB data and optical spectroscopy data, strong correlation between two in-situ sensors have shown.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.31-37
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• 2015

Data generated from sensors are exploding with recent development of IoT. This paradigm shift requires various industry fields that demand instant actions to analyze the arising data on a real-time basis, along with the real-time visualization analysis. As the existing visualization systems, however, perform visualization after storing data, the response time of the server cannot guarantee the ms-level processing that is close to real-time. They also have a problem of destroying data that can be major resources as they do not possess the process resources. Therefore, a smart gardening system that applies a real-time visualization algorithm using IoT sensing data under a gardening environment was designed and implement in this study. The response time of the server was measured to evaluate the performance of the suggested system. As a result, the response speed of the suggested real-time visualization algorithm was guaranteeing the ms-level processing close to real-time.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.172-172
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• 2023

The use of low-cost IoT sensors for flow measurement in open channels has gained significant attention due to their potential to provide continuous and real-time data at a low cost. However, the accuracy and reliability of these sensors in real-world scenarios are not well understood. This study aims to compare the performance of low-cost IoT sensors in the laboratory and real-world conditions to evaluate their accuracy and reliability. Firstly, a low-cost IoT sensor was integrated with an IoT platform to acquire real-time flow rate data. The IoT sensors were calibrated in the laboratory environment to optimize their accuracy, including different types of low-cost IoT sensors (HC-SR04 ultrasonic sensor & YF-S201 sensor) using an open channel prototype. After calibration, the IoT sensors were then applied to a real-world case study in the Dorim-cheon stream, where they were compared to traditional flow measurement methods to evaluate their accuracy.The results showed that the low-cost IoT sensors provided accurate and reliable flow rate data under laboratory conditions, with an error range of less than 5%. However, when applied to the real-world case study, the accuracy of the IoT sensors decreased, which could be attributed to several factors such as the effects of water turbulence, sensor drift, and environmental factors. Overall, this study highlights the potential of low-cost IoT sensors for flow measurement in open channels and provides insights into their limitations and challenges in real-world scenarios.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.2
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• pp.96-102
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• 2011

There are many problems with the fire detection devices being used in currently, because it is difficult to find location of the source of fire and determine where devices are working or not. In this paper, we proposed fire detection and rescue system using wireless sensor network that can be real-time monitoring and determine safe exit. Fire detection and rescue system based on ubiquitous sensor network can know exactly source of fire and help determine rescue tactics using sensing data from wireless sensor nodes. Transmitted wirelessly in real-time thermal sensor and gas sensor information to analyze the GUI to monitor the status information output to the screen by use of a system implemented in everyday life, looked at the possibility.

• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.84-88
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• 2016

As good example of potential application-specific requirement, (m,k)-firm real-time streams have been recently introduced to deliver multimedia data efficiently in wireless sensor networks. In addition to stream model, communication protocols to meet specific (m,k)-firm real-time streams have been newly developed or extended from existing protocols. However, since the existing schemes for an (m,k)-firm stream have been proposed under typical flat architecture, the scalability problem remains unsolved when the number of real-time flows increases in the networks. To solve this problem, in this paper, we propose a new clustering scheme for an (m,k)-firm stream. The two different clustering algorithms are performed according to either the (m,k)-firm requirement or the deadline. Simulation results are presented to demonstrate the suitability of the proposed scheme under hierarchical architecture by showing that its performance is acceptable irrespective of the increase in the number of flows.

• The Journal of Society for e-Business Studies
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• v.13 no.2
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• pp.149-163
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• 2008

In a ubiquitous sensor network (USN) with several nodes, real-time data processing is one of important factors. In order to process data appropriately, all the nodes should transmit sensor data in time and the transmission between nodes and their server should be managed very systematically. For the purpose of systematic management of transmission in a USN, this paper proposes a system for analyzing transmission time of sensor data. To implement the proposed system, an analyzing process of data transmission time, an analyzing method of clock drift, a collecting method of data send/receive times, and calculating formulas of data transmission duration are proposed. According to the proposed process and methods, this paper presents a system for monitoring and analyzing data transmission duration, and it also shows the results of a sample case.

• Journal of Auto-vehicle Safety Association
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• v.12 no.1
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• pp.52-61
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• 2020

In recent years, the increasing interest in health-care requires the industrial products to be well-designed ergonomically. In the commercial vehicle industry, several researchers have demonstrated the driver's posture has great effect on the orthopedic desease such as fatigue, back pain, scoliosis, and so on. However, the existing sensor systems developed for measuring the driver posture in real time have suffered from inaccuracy and low reliability issues. Here, we suggest our smart vehicle seat system capable of real-time driver posture monitoring by using the air bag sensor package with high sensitivity and reliability. The ergonomic numerical model which can evaluate a driver's posture has been developed on the basis of the human body segmentation method followed by simulation-based validation. Our experimental analysis of obtained pressure distribution of a vehicle seat under the different driver's postures revealed our smart vehicle system successfully achieved the driver's real-time posture data in great agreement with our numerical model.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.253-257
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• 2004

Neural networks are works are used in the framework of sensor based tracking control of robot manipulators. They learn by practice movements the relationship between PSD(an analog Position Sensitive Detector) sensor readings for target positions and the joint commands to reach them. Using this configuration, the system can track or follow a moving or stationary object in real time. Furthermore, an efficient neural network architecture has been developed for real time learning. This network uses multiple sets of simple back propagation networks one of which is selected according to which division(corresponding to a cluster of the self-organizing feature map) in data space the current input data belongs to. This lends itself to a very training and processing implementation required for real time control.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.141-146
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• 2008

As the interest about ubiquitous environment is increasing, there are many researches about the services in this environment. These services have important issues in interpreting the users' context, using many kinds of sensors, like PDA, GPS and accelerometers. Low level raw data, which sensors like accelerometers calibrates, are hard to use, and to provide real-time services preprocessing and interpreting the data into context, in real-time, is important. This paper describes a context integrate system which can integrate these sensors and also sensors which has raw data, like accelerometers and physiological sensors, and define the context interpret rule with XML. The proposing system reduces programming operations when adding a sensor to the sensor network or modifying the context interpreting rule by using XML. By using this system, we implemented a real-time data monitoring system which can describe the numeric data into graphs, and assist the user to validate the data and results of the preprocess phase, and also support the external services and applications to use the context of the user.