• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.151-161
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• 2024

In this paper, we develop 'the Danger Map' of a workplace to identify risk and harmful factors by analyzing images of each process within the manufacturing plant site using artificial intelligence (AI). We proposed a system that automatically derives 'the risk and safety levels' based on the frequency and intensity derived from this Danger Map in accordance with actual field conditions and applies them to similar manufacturing industries. In particular, in the traditional evaluation method of manually evaluating the risk of a workplace using Excel, the risk level for each risk and harmful factor acquired from the video is automatically calculated and evaluated to ensure safety through the system and calculate the safety level, so that the company can take appropriate actions accordingly. and measures were prepared. To automate safety calculation and evaluation, 'Heinrich's law' was used as a model, and a 5X4 point evaluation scale was calculated for risky behavior patterns. To demonstrate this system, we applied it to a casting factory and were able to save 2 people the time and labor required to calculate safety each month.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.49-55
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• 2016

In this study, we proposed the social map system prototype for intelligent crime prevention. For developing the social map system prototype, functional requirements were derived through the analysis of related cases and preceding studies. Derived requirements are providing a variety of map-based safety information, using crowdsourcing data such as SNS, connecting to intelligent CCTV. To satisfy these requirements, the prototype is developed with four main menus: the integrated search menu including social media data, the safety map menu providing a variety of safety and danger information, the community map menu to collect safety and danger information from users, and the CCTV menu providing the link to intelligent CCTV. The social map for intelligent crime prevention in this study is expected to greatly enhance the safety of local community with the provision of prompt response to risk information, safe route, etc. through actual service and user participation.

• Journal of The Geomorphological Association of Korea
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• v.24 no.4
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• pp.75-89
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• 2017

Sinkholes are key karst landforms that primarily evolve through the dissolution of limestone, and it posing a significant threat to roads, buildings, and other man-made structures. This study aims to analyze the area susceptible to sinkhole development using GIS and to identify potential danger area from sinkholes. Eight sinkhole related factors (slope angle, distance to caves, distance to faults, bedrock lithology, soil depth, drainage class, distance to mines, and distance to traffic routes) were constructed as spatial databases with sinkhole inventory. Based on the spatial database, sinkhole susceptibility maps were produced using nearest neighbor distance and frequency ratio models. The maps were verified with prediction rate curve and area under curve. The result indicates that the nearest neighbor distance and frequency ratio models predicted 95.3% and 94.4% of possible sinkhole locations respectively. Furthermore, to identify potential sinkhole danger area, the susceptibility map was compared with population distribution and land use map. It has been found that very highly susceptible areas are along Osipcheon and southeast southwest part of Hajang-myeon and south part of Gagok-myeon of Samcheok-si. Among those areas, it has been identified that potential sinkhole danger areas are Gyo-dong, Seongnae-dong, Jeongna-dong, Namyang-dong and Dogye-eup. These results can be useful in the aspects of land use planning and hazard prevention and management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.8
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• pp.5310-5317
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• 2014

Landslides occur in Korea every year because it has numerous mountainous regions and approximately two-thirds of the annual rainfall falls in Summer. Therefore, it is important to predict potential areas of landslides and minimize the damage in advance to protect property and human life. Therefore, in the present study, the potential danger areas were extracted from a digital map, digital forest map, digital forest site environmental map, and digital geologic map to estimate the landslide hazard. In addition, the assessment of landslide danger was analyzed by first and second estimations based on the criteria from the Korea Forest Research Institute using a GIS technique, which was finally judged by a field investigation.

• Journal of Korean Society of societal Security
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• v.2 no.1
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• pp.75-80
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• 2009

The objectives of this research are to develop hazard prediction map S/W for mountain river road. This mountain river road disaster happens by debris flow, landslide, debris accumulation and this cause are locally rainfall and heavy rainfall. System is constructed to GIS base. This research app lied to Kangwondo. We developed protocol to analyze calamity danger in mountain district area and examined propriety system. Furthermore examined the DB required and expression plan for hazard map creation SW construction by mountain rivers road.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.2
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• pp.125-132
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• 2017

The slope of the road in the forest area has a characteristic of steep slope, so natural disasters such as slope collapse occur. The slope displacement observation technique according to landslide is being studied as a method to observe a wide area and a method to observe a small area. This is a study on high-precision digital map generation using ground LiDAR. It is possible to create a high - precision digital map by minimizing the US side using the 3D LiDAR in the steep slope area where the GPS and Total Station measurement are difficult in the maintenance of the danger slope area. It is difficult to objectively evaluate whether the contour lines generated by LiDAR are correct and it is considered necessary to construct a test bed for this purpose. Based on this study, if terrain changes such as landslides occur in the future, it will be useful for measuring slope displacement.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.101-106
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• 2019

In this paper, we investigate the patient fall prevention system to prevent the patient from falling out of the bed unintentionally on the bed of the bed. Patients stay in bed for many hours of hospitalization. During the hospitalization period, patients have low controllability of the body, as compared with normal persons, and fall due to intentional movements, resulting in a fall of the patient, can be a fatal threat to the patient. Therefore, an efficient fall prevention system is required. In this paper, the distance map to the patient is generated by the distance measuring sensor on the bed of the patient, and the risk is determined by estimating the position of the patient based on the distance map. As a result, when the distance map of the dangerous area is 150 mm or more, it is determined to be dangerous, and good results are obtained.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.237-238
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• 2016

This paper describes Web-based information sharing mechanism in our hazard map creation support system. This system aims at collecting the unique information received from residents and raising resident's consciousness to disasters by recording hazardous locations where residents feel danger in case of disasters. We have implemented a mechanism to share and integrate data of each terminal through a Web server. We expect that this information sharing effects scalability and usefulness of our system by utilizing collected local hazard information of each district.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1847-1859
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• 2022

Wildfires in North Korea can have a directly or indirectly affect South Korea if they go south to the Demilitarized Zone. Therefore, this study calculates the regional optimized Forest Fire Danger Index (FFDI) based on Local Data Assessment and Prediction System (LDAPS) weather data to obtain forest fire risk in North Korea, and applied it to the cases in Goseong-gun and Cheorwon-gun, North Korea in April 2022. As a result, the suitability was confirmed as the FFDI at the time of ignition corresponded to the risk class Extreme and Severe sections, respectively. In addition, a qualitative comparison of the risk map and the soil moisture map before and after the wildfire, the correlation was grasped. A new forest fire risk index that combines drought factors such as soil moisture, Standardized Precipitation Index (SPI), and Normalized Difference Water Index (NDWI) will be needed in the future.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.480-484
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• 1990

A simple time-delay method for avoiding collisions between two articulated robot manipulators is proposed. Links of robot are approximated by polyhedra and the danger of collision between two robots is expressed by distances between the robots. An algorithm, which can fast obtain the minimum time-delay value needed for collision avoidance, using scheme of following the boundary contour of collision region in the collision map which has information about collisions between two robots, is described.