• 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.

• 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.

• Magazine of the Korean Society of Hazard Mitigation
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• v.2 no.1 s.4
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• pp.12-16
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• 2002

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.504-514
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• 2009

Recently, fire monitoring application systems have been an active research area due to the safety of industries, historical monuments and so on. The fire monitoring application systems can reduce the damage of properties by providing earlier warning for possible fire situation. However, the existing systems have a drawback that they detect fire with delay due to their uniform epoch in fire detection algorithm. Moreover, they do not provide user-friendly graphical user interfaces in their fire monitoring systems. To resolve the problems, First, we propose a new fire detection algorithm (Early Fire Detection Fire Algorithm) which uses the distribution of sensing data for early fire detection. Our fire detection algorithm is better in terms of fire detection time than the existing work because it can set a start time of fire detection epoch dynamically based on data distribution. Second, we develop a fire monitoring application system which provides users with both a user-friendly graphical user interface and a fire alarm message when fire occurs. Finally, we show from our experiment that our developed system is effectively used for early fire warning in a variety of fire situations.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.25-41
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• 2024

For the scenario of open pit mining, at present, manual periodic verification is mainly carried out in China with the help of video surveillance, which requires continuous investment in labor cost and has poor timeliness. In order to solve this difficult problem of early warning and monitoring, this paper researches a spatialized algorithmic model and designs an early warning system for open-pit mine transboundary mining, which is realized by calculating the coordinate information of the mining and extracting equipments and comparing it with the layer coordinates of the approval range of the mines in real time, so as to realize the determination of the transboundary mining behavior of the mines. By taking the Pingxiang area of Jiangxi Province as the research object, after the field experiment, it shows that the system runs stably and reliably, and verifies that the target tracking accuracy of the system is high, which can effectively improve the early warning capability of the open-pit mines' overstepping the boundary, improve the timeliness and accuracy of mine supervision, and reduce the supervision cost.

• Journal of the Korean Institute of Gas
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• v.17 no.2
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• pp.28-35
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• 2013

The number of large and complex buildings is growing and they are usually concentrated in metropolitan cities. There is a possibility in such buildings that a small accident can expand to a massive disaster since their scale and complexity. To deal with this issue, a research on gas sensors which can detect multiple gases and early-warning systems has been conducted. Proper criteria or standards are necessary for effective application and operation of such sensor-based disaster monitoring system. In this study, we have proposed the alarm criteria of concentration of hazardous gases for the detection and the alarm release. For each alarm level, systematic disaster response plans consist of responsive actions and information delivery have been prepared. These disaster monitoring criteria can help the detection of hazardous gas-related disaster in the early stage of accident and the provision of appropriate emergency responses.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.356-365
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• 2021

The nationwide expansion of the agricultural early warning service for agrometeorological disaster would require assessment of geographical and agricultural environmental characteristics by individual region. The development of an efficient computing environment would facilitate such services for the area of study region to deal with various crops and varieties for many farms. In particular, the design of the computing environment would have a considerable impact on the service quality of agriculture meteorology when the scale of computing environments increases for extended service areas. The objectives of this study were to derive the issues on the current computing environment under which services are provided by each region and to seek the solutions to these problems. The self-evaluation through experimental operation for about a year indicated that integration of the early warning service system distributed over different regions would reduce redundant computing procedures and ensure efficient storage and comprehensive management of data. This suggested that the early warning service for agrometeorological disaster would become more stable even when the service areas are to be expanded to the national scale. This would contribute to higher quality services for individual farmers.

• Convergence Security Journal
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• v.6 no.1
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• pp.1-11
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• 2006

The exponential increase of malicious and criminal activities in cyber space is posing serious threat which could destabilize the foundation of modem information society. In particular, unexpected network paralysis or break-down created by the spread of malicious traffic could cause confusion and disorder in a nationwide scale, and unless effective countermeasures against such unexpected attacks are formulated in time, this could develop into a catastrophic condition. As a result, there has been vigorous effort and search to develop a functional state-level cyber-threat early-warning system however, the efforts have not yielded satisfying results or created plausible alternatives to date, due to the insufficiency of the existing system and technical difficulties. The existing cyber-threat forecasting and early-warning depend on the individual experience and ability of security manager whose decision is based on the limited security data collected from ESM (Enterprise Security Management) and TMS (Threat Management System). Consequently, this could result in a disastrous warning failure against a variety of unknown and unpredictable attacks. It is, therefore, the aim of this research to offer a conceptual design for "Knowledge-based Real-Time Cyber-Threat Early-Warning System" in order to counter increasinf threat of malicious and criminal activities in cyber suace, and promote further academic researches into developing a comprehensive real-time cyber-threat early-warning system to counter a variety of potential present and future cyber-attacks.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.63-77
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• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.

• Nuclear industry
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• v.7 no.6 s.52
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• pp.112.1-112.1
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• 1987