• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.50-58
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• 2017

Recently, some methods of converging heterogeneous fire sensor data have been proposed for effective fire detection, but the rule-based methods have low adaptability and accuracy, and the fuzzy inference methods suffer from detection speed and accuracy by lack of consideration for images. In addition, a few image-based deep learning methods were researched, but it was too difficult to rapidly recognize the fire event in absence of cameras or out of scope of a camera in practical situations. In this paper, we propose a novel fire detection system combining a deep learning algorithm based on CNN and fuzzy inference engine based on heterogeneous fire sensor data including temperature, humidity, gas, and smoke density. we show it is possible for the proposed system to rapidly detect fire by utilizing images and to decide fire in a reliable way by utilizing multi-sensor data. Also, we apply distributed computing architecture to fire detection algorithm in order to avoid concentration of computing power on a server and to enhance scalability as a result. Finally, we prove the performance of the system through two experiments by means of NIST's fire dynamics simulator in both cases of an explosively spreading fire and a gradually growing fire.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.4
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• pp.569-579
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• 2013

Robot control and image processing using a smartphone and Wi-Fi communication is introduced. The robot has a wheel and quadruped mechanism that is transformed according to the environment and is mainly used for drug bottle delivery. The captured image on the camera is transmitted to the smartphone in the form of stream data, and the image data is processed in the smartphone to enable the robot to identify an object and to control the robot itself. A network was constructed so that only image data from the stream data was used, and an image processing scheme to identify the drug bottle and deliver it to a person using a robot arm is also presented. In this study, image processing techniques and algorithms were purely implemented on a smartphone with considerable computational power and multiple functions rather than a computer, which contributes to the intelligence and miniaturization of the robot system.

• Science of Emotion and Sensibility
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• v.21 no.2
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• pp.137-144
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• 2018

The study figured out the operational conditions of a two-way movement actuator made of one-way shape memory alloy (OWSMA) for versatile ventilation intelligent garments. To develop a low-power actuator that consumes energy only when a garment changes its form such as opening and closing, multiple channels of OWSMA were used, and optimum diameter of the wires was examined. For the switch device, optimum voltage application unit time was determined. Optimum diameter of OWSMA wire was determined by applying 3.7V to the pre-determined candidate diameters, which demonstrated two-way operation in previous studies. In order to evaluate the optimum voltage application time, the internal diameter of the actuator was measured while increasing and decreasing by 50 ms from the unit time of voltage application. Delay time under two-way operation of the actuator was measured to minimize interference caused by heat between channels. Power of 3.7V was applied to OWSMA for assessment of optimal time, and the whole process from heating to cooling was video-recorded with a thermal image camera to determine the point of time at which the temperature of OWSMA wire dropped below the phase transformation temperature. The results showed that $0.4{\Phi}$ was the most suitable diameter, and the optimum unit time of voltage applied to open and close the actuator was 4100ms. It was also shown that the delay time should be more than 1.8 seconds between two-way operations of the actuator.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.546-554
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• 2019

Typically, closed-circuit television (CCTV) monitoring is mainly used for post-processes (i.e. to provide evidence after an incident has occurred), but by using a streaming video feed, machine-based learning, and advanced image recognition techniques, current technology can be extended to respond to crimes or reports of missing persons in real time. The multi-CCTV cooperation technique developed in this study is a program model that delivers similarity information about a suspect (or moving object) extracted via CCTV at one location and sent to a monitoring agent to track the selected suspect or object when he, she, or it moves out of range to another CCTV camera. To improve the operating efficiency of local government CCTV control centers, we describe here the partial automation of a CCTV control system that currently relies upon monitoring by human agents. We envisage an integrated crime prevention service, which incorporates the cooperative CCTV network suggested in this study and that can easily be experienced by citizens in ways such as determining a precise individual location in real time and providing a crime prevention service linked to smartphones and/or crime prevention/safety information.

• Spatial Information Research
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• v.23 no.5
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• pp.9-19
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• 2015

The popularity of smart devices and Location Based Services (LBSes) is increasing in part due to users demand for personalized information associated with their location. These services provide intuitive and realistic information by adopting Augmented Reality (AR) technology. This technology utilizes various sensors embedded in the mobile devices. However, these services have inherent problems due to the devices small screen size and the complexity of the real world environment; overlapping content on a small screen and placing icons without considering the user's possible movement. In order to solve these problems, this paper proposes a Mobile Augmented Reality Model with the application of Street Data. The model consists of two layers: "Real Space" and "Information Space". In the model, a user creates a query by scanning the nearby street with a camera in real space and searches accessible content along the street through the use of the information space. Furthermore, the results are placed on both sides of the street to solve the issue of Overlapping. Also, the proposed model is implemented for region "Aenigol", and the efficiency and usefulness of the model are verified.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.199-205
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• 2017

In this study, the design analysis and the explosion welding were made into a clad sheet by the convergence method in order to solve the problem of heat transfer to the guide due to the heating of the 3D printer heating block. The shear strength of the clad plate material was tested and the results were analyzed by thermal analysis, thermal conductivity and thermal imaging. The following conclusions were obtained. 3D modeling of the heating block made of copper and titanium clad plate material The thermal analysis showed that the surface temperature of the filament guide area was lower than the heating block surface temperature. The average shear strength of copper and titanium clad plate material was measured and the average value of 195.6MPa was obtained. The thermal conductivity of the heating block made of copper and titanium clad plate material was measured three times and the average value was $62.52W/m{\cdot}K$. The surface temperature of the heating block made of copper and titanium clad plate material was measured by a thermal imaging camera at a maximum of $107.3^{\circ}C$ and $183.2^{\circ}C$ at the filament guide. The temperature distribution was $89^{\circ}C$ lower than that of the existing filament.

• Korean Institute of Interior Design Journal
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• v.26 no.1
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• pp.33-42
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• 2017

Interior design especially the design developments for commercial spaces should ensure the economy of spaces. This is the marketing for space. It is necessary to understand the design elements of commercial space for the efficient using of digital media of space marketing. In this research decided to design application schemes for shopping mall by searching fashion shopping behaviors of users with persona-base scenario approach. Collected the information of users behavior base on case analysis of advance research to make personas. And develop scenario base personas for knowing the needs of users. And then made 4 schemes as the solution. Scheme 1. Customers can get the information and communication with the staff through with media screen in one room of shopping mall. The data of customers can be recorded for providing information or product recommendation personality. Forecast to preferred by group trip or customers that don't like walking around in shopping mall. Scheme 2. Install a media screen at entrance of a store in shopping mall and show special effect to raise customers' attention who walk through from the front of the store. Through with this customers will stay for long time and raise curiosity to get in the store. And the media screen also provide information of store and products. Scheme 3. Customers can get the information of products with using smart phone to scan QR cord in labels of products and record. Customers can finish whole shopping behaviors without the help of store staff. And can make buying decision even have left shopping mall as a online mode. Scheme 4. Store managers can record the products and the environment of store with 360 camera and update to website. Then customers can browse the virtual space with VR glasses. That make customers can have the real shopping experience without being in the store. In this study, have presented schemes of digital media in commercial space. But there are various of commercial space. In this study was presented schemes for shopping mall by searching fashion shopping behaviors of users. And look forward the researches about specific space setting and other type of commercial space for space development.

• Smart Structures and Systems
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• v.24 no.6
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• pp.769-781
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• 2019

Dynamic displacement response of civil structures is an important index for in-construction and in-service structural condition assessment. However, accurately measuring the displacement of large-scale civil structures such as high-rise buildings still remains as a challenging task. In order to cope with this problem, a vision-based system with the use of industrial digital camera and image processing has been developed for long-distance, remote, and real-time monitoring of dynamic displacement of supertall structures. Instead of acquiring image signals, the proposed system traces only the coordinates of the target points, therefore enabling real-time monitoring and display of displacement responses in a relatively high sampling rate. This study addresses the in-situ experimental verification of the developed vision-based system on the Canton Tower of 600 m high. To facilitate the verification, a GPS system is used to calibrate/verify the structural displacement responses measured by the vision-based system. Meanwhile, an accelerometer deployed in the vicinity of the target point also provides frequency-domain information for comparison. Special attention has been given on understanding the influence of the surrounding light on the monitoring results. For this purpose, the experimental tests are conducted in daytime and nighttime through placing the vision-based system outside the tower (in a brilliant environment) and inside the tower (in a dark environment), respectively. The results indicate that the displacement response time histories monitored by the vision-based system not only match well with those acquired by the GPS receiver, but also have higher fidelity and are less noise-corrupted. In addition, the low-order modal frequencies of the building identified with use of the data obtained from the vision-based system are all in good agreement with those obtained from the accelerometer, the GPS receiver and an elaborate finite element model. Especially, the vision-based system placed at the bottom of the enclosed elevator shaft offers better monitoring data compared with the system placed outside the tower. Based on a wavelet filtering technique, the displacement response time histories obtained by the vision-based system are easily decomposed into two parts: a quasi-static ingredient primarily resulting from temperature variation and a dynamic component mainly caused by fluctuating wind load.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.127-133
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• 2021

A recent study of people physically falling focused on analyzing the motions of the falls using a recurrent neural network (RNN) and a deep learning approach to get good results from detecting 2D human poses from a single color image. In this paper, we investigate a detection method for estimating the position of the head and shoulder keypoints and the acceleration of positional change using the skeletal keypoints information extracted using PoseNet from an image obtained with a low-cost 2D RGB camera, increasing the accuracy of judgments about the falls. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion-analysis method. A public data set was used to extract human skeletal features, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than a conventional, primitive skeletal data-use method.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.67-75
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• 2022

Medical information is variously generated not only from medical devices but also from electronic devices. Recently, related convergence technologies from big data collection in healthcare to medical AI products for patient's condition analysis are rapidly increasing. However, there are difficulties in applying them because of independent developmental procedures. In this paper, we propose an intelligent hospital information system (iHIS) model to simplify and integrate research, development and application of medical AI technology. The proposed model includes (1) real-time patient data management, (2) specialized data management for medical AI development, and (3) real-time monitoring for patient. Using this, real-time biometric data collection and medical AI specialized data generation from patient monitoring devices, as well as specific AI applications of camera-based patient gait analysis and brain MRA-based cerebrovascular disease analysis will be introduced. Based on the proposed model, it is expected that it will be used to improve the HIS by increasing security of data management and improving practical use through consistent interface platformization.