• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.873-878
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• 2008

The wild animal warning post and the echo-bridge on the road are widely used as a popular roadkill prevention system. The warning post shows a one way warning message to drivers and is not effective to prevent animals from being killed. In the case of echo-bridge, the construction cost is very high such that we could not build sufficient number of the echo bridges on the road. Therefore, we have proposed a new roadkill prevention system which is designed and implemented to warn both of drivers and animals. This system is composed with sensor, speaker, web server, and navigation system and the software is designed to use web services on the web under the. Net environment.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.2
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• pp.25-31
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• 2019

As artificial intelligence technology has been developed rapidly, many researchers who are interested in next-generation vehicles have been studying on applying the artificial intelligence technology to advanced driver assistance systems (ADAS). In this paper, a method of applying deep learning algorithm to the lane departure warning system which is one of the main components of the ADAS was proposed. The performance of the proposed method was evaluated by taking a comparative experiments with the existing algorithm which is based on the line detection using image processing techniques. The experiments were carried out for two different driving situations with image databases for driving on a highway and on the urban streets. The experimental results showed that the proposed system has higher accuracy and precision than the existing method under both situations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.3
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• pp.439-448
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• 2018

Conventional Earthquake Early Warning System (EEWS) detects the propagated P-wave from epicenter which should be achieved within 5 seconds to provide seconds to minutes of warning, allowing people to prepare for protective actions. EEWS in Korea is currently capable of providing a warning within 50 seconds after the primary P-wave detection, however, it is well-known that earthquake warning systems operating around Korean National Parks (KNP) have limited capability to fully monitor earthquake events. This study, therefore, presents a strategy to quantify the potential vulnerability to earthquake hazards by superimposing the distribution of Korea Integrated Seismic System (KISS) and the discretized map of KNP. Total 22 national parks are evaluated, and the results suggest that the improvement of the on-site systems should be necessitated for Gyoengju, Gyeryongsan, Songnisan, Gayasan, and Deogyusan national parks, whereas enhancement of regional systems is required for Bukhansan national park.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.296-301
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• 2021

This study is a study dealing with the empirical test of standardized multimedia disaster warning broadcasting linked with the next-generation prediction and warning platform and the disaster warning additional data service of terrestrial UHD broadcasting. The next-generation prediction and warning platform used in the demonstration test complies with the CAP-based TTA standardization standard, and the UHD disaster warning additional data service complies with the AEAT standard. As a result of the experiment, when a standardized CAP disaster warning message is issued and delivered to a broadcasting company, a system was established so that it is automatically converted to AEAT, a UHD disaster warning additional data message, and transmitted. The receiver unit was configured by connecting a set-top capable of receiving disaster alert data and a TV with an HDMI cable. When a disaster is announced, the set-top displays the AEAT message on the TV broadcasting screen, customized to the priority of the disaster and the area where it is issued. In addition, incoming messages are displayed in a language suitable for user settings among 5 languages. Additional multimedia functions such as images and alarm sounds could also be linked. In particular, it was confirmed that the receiver message was displayed within 3 seconds of issuing the disaster alert, enabling prompt delivery of the disaster alert.

• Journal of Broadcast Engineering
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• v.20 no.3
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• pp.440-448
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• 2015

A pedestrian collision warning system which makes a judgement of pedestrian's intention to help avoiding hitting accidents is proposed. This system uses the image sequences obtained from a car black box as well as vehicle's speed obtained from a GPS. It detects pedestrians, if any, based on the Histogram of Gradient method and extracts several information such as the pedestrian's relative positions, the direction of motion vectors, and distance between vehicle and pedestrian . A fuzzy logic based on these extracted information is applied to analyze the pedestrian's safety levels. When the safety level is determined to be danger, an alarm is triggered to the driver. The performance of the proposed algorithm is tested under various driving scenarios, which shows it works successfully in real-time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.4
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• pp.1203-1222
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• 2012

To provide active notification and enhance drivers'awareness of their surroundings, a vision-based collision warning system that detects and monitors surrounding vehicles is proposed in this paper. The main objective is to prevent possible vehicle collisions by monitoring the status of surrounding vehicles, including the distance to the other vehicles in front, behind, to the left and to the right sides. In addition, the proposed system collects and integrates this information to provide advisory warnings to drivers. To offer the correct notification, an algorithm based on features of edge and morphology to detect vehicles is also presented. The proposed system has been implemented in embedded systems and evaluated on real roads in various lighting and weather conditions. The experimental results indicate that the vehicle detection ratios were higher than 97% in the daytime, and appropriate for real road applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.223-229
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• 2008

In this paper. we propose the real-time vision system which judges drowsiness driving based on levels of drivers' fatigue. The proposed system is to prevent traffic accidents by warning the drowsiness and carelessness using face-image analysis and fuzzy logic algorithm. We find the face position and eye areas by using fuzzy skin filter and virtual face model in order to develop the real-time face detection algorithm, and we measure the eye blinking frequency and eye closure duration by using their informations. And then we propose the method for estimating the levels of drivel's fatigue based on measured data by using the fuzzy logic and for deciding whether drowsiness driving is or not. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.123-126
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• 2017

The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver 's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper, we propose a method to implement a multi-function camera driving safety system that notifies a pedestrian and lane departure warning without using a radar sensor or a stereo video image, and a study on the analysis of a lane departure alarm software result.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.18-20
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• 2019

In this paper, in order to prevent accidents when deviating from the lane during high-speed self-driving, we are going to design a warning system that will sound an alarm after recognizing the surrounding situation with a $360^{\circ}$ camera. Accidents often occur while driving on self-driving cars because they try to change lanes excessively or fail to recognize people, animals and objects that appear suddenly when driving at high speeds. The government wants to identify the surrounding situation with cameras when driving off a lane during high-speed autonomous driving, and to create a car that sounds a warning system through a lane departure sensor on the underside of the vehicle to reduce various accidents that occur during self-driving and to have a safer driving system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.195-202
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• 2017

This study aims to suggest the basics for the implementation of the farmstead-specific early warning system (FEWS) for weather risk management nationwide. A survey by questionnaire was conducted to examine farmer's response, and a cost-benefit analysis was made to examine the effect of the FEWS on the economy. The farmers who volunteered to participate in this survey responded that they were generally satisfied with the FEWS, and that they used it well for farming. Willingness to pay (WTP) for the early warning service was estimated to be 8,833 KRW per month by survey respondents. If the early warning service is extended to nationwide and 50% of farmers use it for six months, then the ratio of benefit to cost will be 2.2, indicating that nationwide expansion of the FEWS is very feasible.