• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.71-72
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• 2020

본 논문에서는 자동차 블랙박스를 사용하여 촬영된 비디오에서 자동차 사고 발생 여부를 판단하는 방법을 제안한다. 제안한 방법은 우선 객체 추적 과정에서 구한 조감도 좌표를 사용하여 각 차량 사이의 거리에 기반을 두고 교통사고 여부를 판단한다. 그런데 거리만을 사용하여 사고 여부를 판단하는 경우 자동차가 밀집된 주·정차 환경에서는 오검출의 확률이 높아질 수 있다. 이를 위해 각 차량에 대한 움직임 벡터를 계산하고 벡터 간의 정보(사잇각과 크기 등)를 사용하여 차량의 주·정차 여부를 판단한 후 사고 검출 대상에서 배제할 수 있도록 한다. 주·정차 판단 여부를 통해 사고 검출의 정확도를 향상할 수 있는 것을 실험적으로 확인하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.233-240
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• 2024

In this study, we introduce a system for real-time monitoring of field conditions within an industrial complex using a 5G network UAV (: Unmanned Aerial Vehicle). When a monitoring event occurs in a sensor mounted on a UAV (detection of fire, harmful gas, or industrial disaster type human accident), key information from the sensor is transmitted to the UAS (: Unmanned Aerial System) application server. As a result of this information transmission and processing, managers or operators of the Industrial Complex Corporation were able to secure legal basis data for fatal accidents, fires, and detection of harmful gases at sites within the Industrial Complex Corporation through trigger processing for each accident risk situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2423-2428
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• 2010

The number of motor vehicle registrations in Korea is increasing steadily each year, driven by industry development and economic growth. The number of traffic accidents is also rapidly increasing. Korea has a relatively high number of traffic accidents among OECD member countries, and it ranks among the highest in traffic accident death rates. This death rate is higher compared to death rates as a proportion of the number of traffic accidents in each country. It is very common for drivers to lose consciousness in traffic collisions, which leads to a failure to carry out early emergency measures. In order to prevent such situations as well as hit-and-runs and people left uncared for after traffic accidents, there is a need for motor vehicle black boxes and accident report systems. This study addressed the need for an emergency evacuation system for people injured in traffic accidents and a secondary traffic accident prevention system by developing a motor vehicle emergency situation detection and report system combined with a black box, and materializing it as an actual system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.200-202
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• 2010

The number of motor vehicle registrations in Korea is increasing steadily each year, driven by industry development and economic growth. The number of traffic accidents is also rapidly increasing. Korea has a relatively high number of traffic accidents among OECD member countries, and it ranks among the highest in traffic accident death rates. This death rate is higher compared to death rates as a proportion of the number of traffic accidents in each country. It is very common for drivers to lose consciousness in traffic collisions, which leads to a failure to carry out early emergency measures. In order to prevent such situations as well as hit-and-runs and people left uncared for after traffic accidents, there is a need for motor vehicle black boxes and accident report systems. This study addressed the need for an emergency evacuation system for people injured in traffic accidents and a secondary traffic accident prevention system by developing a motor vehicle emergency situation detection and report system combined with a black box, and materializing it as an actual system.

• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.119-134
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• 2014

Financial companies are providing electronic financial transactions through a variety of user terminals for non-face-to-face services such as Internet banking, smart phone banking, or etc. However, in these services users' security awareness and the limitations of technical responses has frequently caused the financial loss so that fundamental protection measures are required from financial authorities. Accordingly, financial industry is planning and establishing systems that block unusual financial transactions by comprehensively analyzing and detecting user's electronic information, access information, transaction information, and so on in accordance with "Guide for building Unusual financial transactions detection system" to prevent the financial loss that happens in electronic financial transactions. In this paper, we analyze case studies of unusual financial transactions detection and prevention system that is built and operated in financial companies and current operating status and propose effects of the accident prevention and security measures later.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.3
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• pp.376-382
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• 2014

E-Actuator is an essential part of an eVGT, it receives the command from the main ECU and controls the vane. An e-Actuator failure can cause an abrupt change in engine output and it may induce an accident. Therefore, it is required to detect anomalies in the e-Actuator in real time to prevent accidents. In this paper, an e-Actuator fault detection method using on-line parameter identification is proposed. To implement on-line fault detection algorithm, many constraints are considered. The test input and sampling rate are selected considering the constraints. And new recursive system identification algorithm is proposed which reduces the memory and MCU power dramatically. The relationship between the identified parameters and real elements such as gears, spring and motor are derived. The fault detection method using the relationship is proposed. The experiments with the real broken gears show the effectiveness of the proposed algorithm. It is expected that the real time fault detection is possible and it can improve the safety of eVGT system.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.282-292
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• 2020

In order to minimize casualties from marine vessel accidents that occur frequently at home and abroad, it is important to ensure the safety of the passengers aboard the vessel in the event of an accident. There is an EPIRB system as a system for disaster preparedness in the marine situation currently on the market, but there is a problem that the price is very expensive. In order to overcome the cost problem, which is a disadvantage of previous system, LoRaWAN-based communication is used. LoRaWAN communication-based vessel positioning and risk detection system based on LoRaWAN communication transmits measurement data of each module using two Beacon and GPS modules to stably perform position measurement for both indoor and outdoor situations. The rider danger situation detection system can detect the safety status of the rider using the 3-axis acceleration sensor, collect data from the rider positioning system and the rider safety status detection system, and send to server using LoRa communication. When conducting communication experiments in the long-distance maritime situation and actual communication experiments using the implemented system, it was found that the two experiments showed over 90% communication success rate on average.

• Journal of Satellite, Information and Communications
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• v.12 no.2
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• pp.99-103
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• 2017

Recently, acccording to price decline and miniaturization of drone, it is increased dramatically that drone usage in various category including military and private sectors. In accordance with popular usage, There is a increasing risk of safety accident, national security and public privacy problem. Hence there is a high demand for study and analysis applicable to the related technology and anti-drone method including drone detection and jamming. In general, it is extremely difficult to detect and recognize drones using conventional sensors. In this paper, we classify drone detection technology and Drone detection experiments are performed using CW RADAR to obtain and analyze micro-doppler pattern. This preliminary study aims to provide fundamental theory on radar drone detection and experimental test results such that in-depth anti-drone technology can be established in future.

• The Journal of Bigdata
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• v.7 no.1
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• pp.15-27
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• 2022

In the past five years, the fatality rate of single-vehicle accidents has been 4.7 times higher than that of all accidents, so it is necessary to establish a system that can detect and respond to single-vehicle accidents immediately. The IoT(Internet of Thing)-based real-time traffic accident recognition system proposed in this study is as following. By attaching an IoT sensor which detects the impact and vehicle ingress to the guardrail, when an impact occurs to the guardrail, the image of the accident site is analyzed through artificial intelligence technology and transmitted to a rescue organization to perform quick rescue operations to damage minimization. An IoT sensor module that recognizes vehicles entering the monitoring area and detects the impact of a guardrail and an AI-based object detection module based on vehicle image data learning were implemented. In addition, a monitoring and operation module that imanages sensor information and image data in integrate was also implemented. For the validation of the system, it was confirmed that the target values were all met by measuring the shock detection transmission speed, the object detection accuracy of vehicles and people, and the sensor failure detection accuracy. In the future, we plan to apply it to actual roads to verify the validity using real data and to commercialize it. This system will contribute to improving road safety.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.3
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• pp.255-263
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• 2014

Today, a number of CCTV on the highway is to observe the flow of traffics. There have been a number of studies where traffic data (e.g., the speed of vehicles and the amount of traffic on the road) are transferred back to the centralized server so that an appropriate action can be taken. This paper introduces a system that detects the changes of traffic flows caused by an accident or unexpected stopping (i.e., vehicle remains idle) by monitoring each lane separately. The traffic flows of each lane are level spacing curve that shows Wigner distribution for location vector. Applying calogero-moser system and Hamiltonian system, probability equation for each level-spacing curve is derived. The high level of modification of the signal means that the lane is in accident situation. This is different from previous studies in that it does more than looking for the signal from only one lane, now it is able to detect an accident in entire flow of traffic. In process of monitoring traffic flow of each lane, when camera recognizes a shadow of vehicle as a vehicle, it will affect the accident detecting capability. To prevent this from happening, the study introduces how to get rid of such shadow. The system using Basian network method is being compared for capability evaluation of the system of the study. As a result, the system of the study appeared to be better in performance in detecting the modification of traffic flow caused by idle vehicle.