• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.799-810
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• 2023

This paper analyzed changes in population mobility characteristics based on emergency disaster messages related to wildfires that occurred in 2022, using mobile data. The primary wildfires under analysis are the ones that occurred in Donghae City and Miryang City. Donghae City sent a total of six evacuation messages in response to the wildfire incidents, and all of the message contents specified particular evacuation locations. As a result, it was analyzed that there was a significant impact on changes in population mobility characteristics. On the other hand, in the case of Miryang City, a total of five evacuation messages were sent during the wildfire period, but not all messages specified a clear evacuation location,such as "A safe place". As a result, it was observed that there was minimal change in population mobility due to the lack of clear evacuation locations specified in the messages. These analysis results suggest the need for institutional improvements such as the standardization and specification of emergency alert message content when wildfires or similar disasters occur in different regions.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.753-762
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• 2024

Tunnels have limited evacuation areas, and It is difficult for cars coming from behind to recognize the accident situation in front. Since an accident is very likely to lead to a serious secondary accident, a IoT-based smart tunnel accident warning system was studied to prepare for traffic accidents that occur in tunnels. If the measured values from the flame detection sensor, gas detection sensor, and shock detection sensor in the tunnel exceed the standard, it is judged to be an emergency situation and an alert system is designed to operate. The accident information message was designed to be displayed on the LCD and transmitted to drivers inside and outside the tunnel through a Wi-Fi communication network. A performance test system was established and performance evaluation was performed for several accident scenarios. As a result of the test, it was confirmed that the accident alert system can accurately detect accidents based on given reference values, perform alert procedures, and transmit alert messages to smart phones through Wi-Fi wireless communication. And through this, its effectiveness could be confirmed.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.9
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• pp.211-216
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• 2016

Worldwide casualties caused by earthquakes, floods, fire or other disaster has been increasing. So many researchers are being actively done technical studies to ensure golden-time. In this paper if a disaster occurs, use the IoT technologies in order to secure golden-time and transmits the message after to find the user of the accident area first. When the previous job is finished, gradually finds a user of the surrounding area and transmits the message. For national emergency information, OPEN API of Korea Meteorological Administration was used. To collect detailed information on a relevant area in real time, this study established the system that connects and integrates Crowd Sensing technology with BLE (Bluetooth Low Energy) Beacon technology. Up to now, the CBS based on base station has been applied. However, this study designed and mapped DB in the integration of Beacon based user positioning and national administrative address system in order to estimate local users. In this experiment, the accuracy and speed of information dif6fusion algorithm were measured with a rise in the number of users. The experiments were conducted in a manner that increases the number of users by one thousand and was measured the accuracy and speed of the message spread transfer algorithm. Finally, became operational in less than one second in 20,000 users, it was confirmed that the notification message is sent.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.293-296
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• 2016

In case of an emergency on a busy road of a city, drivers should make way for special vehicles such as police cars, fire engines, or ambulance as soon as possible. If road infrastructures recognize the movements of special vehicles, and transfer alert message to traffic signal controllers and normal cars through wireless network such as WAVE or TPEG, normal cars can prepare to make way in advance. As a result, it help special vehicles move faster. In this paper, we install a roof mark on the roof of a special vehicle, detect the mark through a mark recognition algorithm which includes perspective transformation, and get the inner information by decoding the digital pattern on it. The experiment results show that mark can be recognized 100% and 93.3% of inner digital data of the mark can be recognized, when the size of a mark is larger than $88cm{\times}88cm$ and the mark moves at a speed of 50km/s.