• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.1-6
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• 2014

Color image processing based on smoke detection is suitable detecting target to early detection of fire smoke. A method for detecting the smoke is processed in the pre-processing movement and color. And Next, characteristics of smoke such as diffusion, texture, shape, and directionality are used to post-processing. In this paper, propose the detection method of density distribution characteristic in characteristics of smoke. the generate a candidate regions by color thresholding image in Detecting the movement of smoke to the 10Frame interval and accumulated while 1second image. then check whether the pattern of the smoke by candidate regions to applying OBTP(Object Block Ternary Pattern). every processing is Block-based processing, moving detection is decided the candidate regions of the moving object by applying an adaptive threshold to frame difference image. The decided candidate region accumulates one second and apply the threshold condition of the smoke color. make the ternary pattern compare the center block value with block value of 16 position in each candidate region of the smoke, and determine the smoke by compare the candidate ternary pattern and smoke ternary pattern.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.91-96
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• 2017

In this paper, we aim to respond efficiently to crime by using Arduino and smartphone apps in response to increasing number of house-breaking crimes. It receives the signal of the sensor installed in the house and connects it with the app of the smartphone. To use the app, you can download the app from the user's smartphone, launch the app, and operate the operation outside the home, not only inside the house, by linking the executed app. Among the sensors installed in the house, the movement detection sensor is used to enhance the security, and the gas leakage sensor and the flame detection sensor can be used to easily detect the risk of fire and to prevent the fire early. Security is further enhanced by the ability to remotely control the front door with a smartphone. After that, various sensors can be added and it can be developed as a WiFi module in addition to the Bluetooth module.

• Design & Manufacturing
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• v.16 no.4
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.74-83
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• 2018

It is very crucial activities that Korean army have to detect and recognize enemy's locations and types of weapon of their artillery firstly for effective operation of friendly force's artillery weapons during wartime. For these activities, one of the most critical artillery weapon systems is the anti-artillery radar (hereafter; radars) for immediate counter-fire operations against the target. So, in early wartime these radar's roles are very important for minimizing friendly force's damage because arbiters have to recognize a several enemy's artillery positions quickly and then to take an action right away. Up to date, Republic of Korea Army for tactical artillery operations only depends on individual commander's intuition and capability. Therefore, we propose these radars allocation model based on integer programming that combines ArcGIS (Geographic Information System) analysis data and each radar's performances which include allowable specific ranges of altitude, azimuth (FOV; field of view) and distances for target detection, and weapons types i.e., rocket, mortars and cannon ammo etc. And we demonstrate the effectiveness of their allocation's solution of available various types of radar asset through several experimental scenarios. The proposed model can be ensured the optimal detection coverage, the enhancement of artillery radar's operations and assisting a quick decision for commander finally.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.499-504
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• 2006

터널 내 화재 발생 시 대규모의 인명, 재산 피해가 발생하는데 이러한 상황을 조기에 탐지함으로써 피해를 최소화하기 위한 시스템이 필요하다. 또한 터널 내 설치된 CCTV를 사람이 24시간 감시하기에는 너무 어려운 점이 많다. 이에 따라 적절한 영상 처리를 통한 화염 및 연기 검출 시스템을 통해 경보를 알려줄 경우, 보다 편리하고 사람이 모니터 앞에 없을 때 화재 발생 시 화재를 검출할 수 있어 피해를 최소화 할 수 있다. 본 논문에서는 영상처리 기법을 이용하여 터널 안에서 발생한 화재 및 연기를 고속으로 탐지하기 위한 알고리즘을 제안하였다. 터널 안에서의 화재 탐지는 차량 조명 및 터널내의 조명등과 같은 여러 가지 상황에 의해 산불 탐지 알고리즘과 다른 독자적인 알고리즘의 개발이 요구된다. 본 논문에서 제시한 두 가지 알고리즘은 기존 알고리즘보다 정확한 위치 탐지와 초기 단계에서의 탐지가 가능하도록 되었다. 또한 우리는 실험 결과를 통해 각각의 성능을 비교함으로써 제시한 알고리즘의 타당성을 보여주었다.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.719-720
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• 2006

Ad hoc networks does not need any wired network infrastructure. Therefore, they have been developed in temporary networks or mainly in military networks. Infostations offer geographically intermittent coverage at high speeds. Up-to-date there have been frequent big forest fires in Korea mountain areas. It is very important to detect them early to prevent them from being big disasters. In this paper, we propose a disaster emergency management system using sensor attached wild boars' mobility combined with infostation system. We also make a numerical analysis of the performance of the system.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.660-661
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• 2020

본 논문에서는 기존 인공 신경망 기반 시계열 학습 기법인 Recurrent Neural Network (RNN)의 많은 연산량 및 고 사양 시스템 요구를 개선하기 위해 랜덤 포레스트 (Random Forest)기반의 새로운 시계열 학습 기법을 제안한다. 기존의 RNN 기반 방법들은 복잡한 연산을 통해 높은 성능을 달성하는 데 집중하고 있다. 이러한 방법들은 학습에 많은 파라미터가 필요할 뿐만 아니라 대규모의 연산을 요구하므로 실시간 시스템에 적용하는데 어려움이 있다. 따라서 본 논문에서는, 효율적이면서 빠르게 동작할 수 있는 시계열 다층 랜덤 포레스트(Time series Multilayered Random Forest)를 제안하고 산불 조기 탐지에 적용해 기존 RNN 계열의 방법들과 성능을 비교하였다. 다양한 산불화재 실험데이터에 알고리즘을 적용해본 결과 GPU 상에서 방대한 연산을 수행하는 RNN 기반 방법들과 비교해 성능적인 한계가 존재했지만 CPU 에서도 빠르게 동작 가능하므로 성능의 개선을 통해 다양한 임베디드 시스템에 적용 가능하다.

• Research in Plant Disease
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• v.26 no.4
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• pp.239-249
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• 2020

To find out the cause of the fire blight outbreak in apples and pears of Korea in 2019, we investigated disease appearing situation of thirty fire blight infected orchards, and interviewed farmers to determine the cultivation characteristics. Fire blight occurred mostly in orchards that had infected more than 2 years before. The cause of this were as follows: farmers did not know the symptoms of the disease properly. It is presumed that it has spread from the first occurrence to the surrounding orchards by flower-visiting insects or farmers and to a short distance or a long distance by the same cultivator or co-farmer. These series of processes repeated in the newly spreading area, and then disease reports increased as farmers became aware of fire blight. To minimize the spread of fire blight in Korea, it suggested that thorough education of farmers for early diagnosis and quantitative detection technology that can diagnose even in no symptom showing plants. And chemical or biological spraying systems suitable for domestic cultivation methods, which are producing large fruits, and molecular epidemiological studies of pathogens.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.96-110
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• 2020

Recently, due to global warming, it is easily exposed to various disasters such as fire, flood, and earthquake. In particular, large-scale disasters have continuously been occurring in crowded areas such as traditional markets, facilities for the elderly and children, and public facilities where various people stay. Purpose: This study aims to detect a fire occurred in crowded facilities early in the event to analyze and provide an optimal evacuation route using big data and advanced technology. Method: The researchers propose a new algorithm through context-aware 3D object model technology and A* algorithm optimization and propose a scenario-based optimal evacuation route selection technique. Result: Using the HPA* E algorithm, the evacuation simulation in the event of a fire was reproduced as a 3D model and the optimal evacuation route and evacuation time were calculated for each scenario. Conclusion: It is expected to reduce fatalities and injuries through the evacuation induction technique that enables evacuation of the building in the shortest path by analyzing in real-time via fire detection sensors that detects the temperature, flame, and smoke.

• The Korean Journal of Emergency Medical Services
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• v.24 no.2
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• pp.27-38
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• 2020

Purpose: Stroke is a time-sensitive disease that could have reduced complications and mortality with timely diagnosis and treatment. This study aimed to analyze the causes of delay in detecting the clinical signs and symptoms of stroke. Methods: This retrospective observational study analyzed the emergency medical services reports of suspected stroke patients with positive predictive values on the Cincinnati Prehospital Stroke Scale. The study was conducted in Daejeon, Republic of Korea from January 1, 2016 through December 31, 2017. Results: Prolonged prehospital time was associated with high blood pressure, history of cerebrovascular disease, and incidences during daily activities, and sleep. High blood pressure and complications from a previous stroke strongly associated with the prolonged stroke-detection phase (p<.05). Total prehospital time was shortened when patients had evident stroke symptoms, such as decreased level of consciousness, dysarthria, and hemiplegia (p<.05). There was no significant difference in gender or age as a factor that delayed the total prehospital time of the suspected stroke patients. Conclusion: Many patients did not recognize the early clinical symptoms and signs of a stroke. Furthermore, risk factors, such as high blood pressure and history of stroke, prolonged the total prehospital time. Therefore, we need targeted interventions that educate about warning symptoms of stroke, along with emphasis on the importance of emergency calls to substantially reduce the prehospital delays.