• Journal of Information Technology Services
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• v.16 no.2
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• pp.111-127
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• 2017

Computing Performance, sensor, storage, memory, and network costs have been steadily declining, and IoT services have recently become more active. The Internet of Things is linked with Big Data to create new business, and public institutions and corporations are hurry to import Internet of things. As the importance of the Internet of things has increased, the number of devices supporting the IoT has rapidly increased. With the development of the Internet of Things, various types of Internet services are being developed. For this reason, there is an increasing demand for IoT service designers and developers for IoT service case automatic search technology. IoT service designers can avoid duplication with existing services through service case retrieval and developers can save cost and time by combining existing reusable service equipment. This paper proposes IoT-Lite ontology for IoT and Semantic Web service to solve the above-mentioned problems. The existing ontologies for IoT, despite its many advantages, are not widely used by developers because it has not overcome the relatively slow drawbacks of increasing complexity and searching for development. To complement this, this study uses the IoT-Lite ontology introduced by W3C as a model and a semantic web service for automatic system retrieval. 3D camera, GPS, and 9-axis sensor, and IoT-Lite designed by IoT-Lite technique are integrated with the semantic technique and implemented directly.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.818-826
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• 2015

This paper presents a novel methodology for estimating vehicle ego-motion, i.e. tri-axis linear velocities and angular velocities by using stereo vision sensor and 2G1Y sensor (longitudinal acceleration, lateral acceleration, and yaw rate). The estimated ego-motion information can be utilized to predict future ego-path and improve the accuracy of 3D coordinate of obstacle by compensating for disturbance from vehicle movement representatively for collision avoidance system. For the purpose of incorporating vehicle dynamic characteristics into ego-motion estimation, the state evolution model of Kalman filter has been augmented with lateral vehicle dynamics and the vanishing point estimation has been also taken into account because the optical flow radiates from a vanishing point which might be varied due to vehicle pitch motion. Experimental results based on real-world data have shown the effectiveness of the proposed methodology in view of accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5276-5298
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• 2019

Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.558-567
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• 2017

In this research, we developed an efficient real-time human exercise pose estimation system using multiple Kinects. The main objective of this system is to measure and recognize the user's posture (such as knee curl or lunge) more accurately by employing Kinects on the front and the sides. Especially it is designed as an extensible and modular method which enables to support various additional postures in the future. This system is configured as multiple clients and the Unity3D server. The client processes Kinect skeleton data and send to the server. The server performs the multiple-Kinect calibration process and then applies the pose estimation algorithm based on the Kinect-based posture recognition model using feature extractions and the weighted averaging of feature values for different Kinects. This paper presents the design and implementation of the human exercise pose estimation system using multiple Kinects and also describes how to build and execute an interactive Unity3D exergame.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1071-1080
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• 2017

Recently, the terms of the 4th Industrial Revolution and the Smart Factory are often heard through news and media. But most of the companies that are parties are not interested. Because there is no specific guidance on how to build Smart Factory and information about Smart Factory. The built of the Smart Factory should be carried out in accordance with the size of the company considering the purpose of the introduction. In the existing study, they analyzed successful cases of building Smart Factory in Korea As a result, in the case of large-size firms, it is an effective strategy that expanding from a model factory to whole factory for successful Smart Factory building. In addition, in the case of medium and small-size firms, it is an effective strategy that upgrading from low-level step to high-level step for successful Smart Factory building. In this study, selecting medium and small-size firms, and bottleneck section and processes requiring improvement are identified through 3D virtual process design, and then install sensors. Finally, after analyzing the data collected through the sensor, we will improve the process and build Smart Factory with improved productivity.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.09a
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• pp.11-18
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• 2005

Filament inversion routines are highly effective for target definition whenever total-field DHTEM vectors can be obtained using three-component logging tools. However most cross-hole components contain significant noise related to sensor design and errors in observation of probe rotation. Standard stacking methods can be used to improve data quality but additional statistical methods based on cross-correlation and spatial averaging of orthogonal components may be required to ensure a consistent vector migration path. Apart from assisting with spatial averaging, multiple filaments generated for successive time-windows can provide additional imaging information relating to target geometry and current migration. New digital receiver systems provide additional time-windows to provide better tracking options necessary for high-resolution imaging of this type.

• KIEAE Journal
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• v.8 no.3
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• pp.101-106
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• 2008

The use of daylighting has been increased recently due to energy and visual comfort. The aims of interior daylighting are to adequately illuminate visual tasks, to create an attractive visual environment, and to save electrical energy. Lightpipe can improve the distribution of light to interior spaces. This study aims to evaluate the comparative daylighting performance of lightpipe under different sky conditions with mock-up model, sized $6m{\times}6m{\times}4m$ ($w{\times}d{\times}h$). For the purpose, perpendicular lightpipe system was designed as 650 diameter, with an aspect ratio of 2. Totally 49 measuring points of and two of outdoor illuminance on the horizontal plane were monitored from 09:00 to 18:30 on April 29 and May 15 2008. Agilent data logger and photometric sensor were used. Light factor were used to analyse daylight performance under different sky condition. Under overcast sky condition and clear sky condition, the lightpipe system is suitable for KS recommendation level of illuminance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7902-7909
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• 2015

The needs for smart city management technology has been increased for efficiently managing huge and complex social infrastructures. Thus, this research introduces smart bridge facility management system based on sensor and BIM technologies so that the inadequacy of current facility maintenance system and the limitations of data objectivity, consistency and expandability can be improved. For which, current trends on sensor and BIM technologies and standard information system were investigated to derive system develop requirements, and a scenario was suggested to discuss how to utilize the suggested system. Research outcomes are expected to be utilized as a preliminary research for developing the real application framework for bridge facility management.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1770-1776
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• 2011

In this study, a new method that can estimate ICG data from a subject's both hands to measure Cardiac Output under convenient sensor environment. With this aim, a grip-type electrode was implemented to measure ICG. To improve the accuracy of measurement, the regression equation was extracted using multiple bio-parameters and our result was compared with the thoracic ICG equipment(Physio Flow$^{(R)}$, PF104D, Manatec Biomedical, France), which is being used in clinics. The subjects consist of 26 men and 4 women(age in $22.0{\pm}3.32$). They are no cardiac disease. Parameters available for regression model were used gender, BMI, MBP, LVET, dZ/dt(max), distance between the measured electrodes, body impedance, and PTT. As a result of analyzing the ICG measurement value on thorax and both hands, the correlation with stroke volume, heart rate, and cardiac output was $R^2$=0.853, $R^2$=0.958 and $R^2$=0.899, respectively.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1295-1295
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• 2024

As extreme weather events such as heavy snowfall and typhoon become more frequent, climate change significantly impacts across various worldwide industries. With demands for dealing with this phenomenon, continuous achievements in safety diagnosis have been announced for large structures. Conversely, in agricultural infrastructures having lower risk to human life, there is lack of established safety diagnosis methods. However, considering expansion of high-value smart farm, the importance of plastic greenhouse cannot be overlooked. Therefore, this study aimed to develop on-site diagnosis technique for structural safety of steel structure greenhouse. To build an analysis model, we generated point cloud data of on-site greenhouse using a camera with LiDAR sensor. Subsequently, we extracted points corresponding to pipes using a pre-trained semantic segmentation model, achieving a pipe segmentation accuracy of 78.1%. These points were then converted into 3D frame model, with a location coordinate error of 5.4 cm for nine reference points, as measured by an on-site survey. In FEM structural analysis, nonlinearity of pipe connection was reflected. The loads were determined based on expected wind speed and snow depth in Korea. The structural safety of on-site model was diagnosed more vulnerable with 10.3% higher maximum axial stress, compared with standard model. Through this research, we expect the quantitative safety diagnosis of predicting greenhouse collapse risk. In addition, this technique will enable localized reinforcement strategies within the structure.