• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.413-414
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• 1998

This paper presents a real-time Spatial Decision Support System(SDSS) for security camera image monitoring. Other SDSSs are not real-time systems, i.e., they show the images that are already transformed into data format such as virtual reality. In our system, the image is broadcasted in real-time since the purpose of the security camera needs to do it in real-time. With these real-time images, other systems do not add up anything more; the screen just shows the images from the camera. However in our system, we created a motion detection system so that the supervisor(Judge) of a sec.urity monitoring system does not have to pay attention to it constantly. In other words, we created a judge advising system for the supervisor of the security monitoring system. Most of small objects do not need the supervisor's attention since they could be birds, cats, dogs, etc. if they show up in the screen image. In this new system the system only report the unusual change to the supervisor by calculating the motion and size of objects in the screen. Thus the supervisor can be liberated from the 24-hour concentration duty; instead he/she can be only alerted when the real security threat such as a big moving object like an human intruder appears. Thus this system can be called a real-time Spatial DSS. The utility of this system is proved mathematically by using the concept of entropy. In other words, big objects like human intruders increase the entropy of the screen images significantly therefore the supervisor must be alerted. Thus by proving its utility of the system theoretically, we can claim that our new real-time SDSS is superior to others which do not use our technique.hnique.

• Journal of Korean Society of Transportation
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• v.35 no.5
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• pp.409-422
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• 2017

TOD (Transit-Oriented Development) is one of the urban structure concentrated on the multifunctional space/district with public transportation system, which is introduced for maintaining sustainable future cities. With such trends, the project of building complex transferring centers located at a urban railway station has widely been spreaded and a comprehensive and systematic analytical framework is required to clarify and readily understand the complicated procedure of estimation with the large scale of the project. By doing so, this study is to develop a comprehensive analytical framework for estimating a pedestrian OD matrix using a spatial information and an integrated smart card data, which is so called a data depository and it has been applied to the Samseong station for the model validation. The proposed analytical framework contributes on providing a chance to possibly extend with digitalized and automated data collection technologies and a BigData mining methods.

• The Korean Journal of Applied Statistics
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• v.29 no.6
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• pp.1107-1116
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• 2016

Recent astronomical survey observations have produced substantial amounts of data as well as completely changed conventional methods of analyzing astronomical data. Both classical statistical inference and modern machine learning methods have been used in every step of data analysis that range from data calibration to inferences of physical models. We are seeing the growing popularity of using machine learning methods in classical problems of astronomical data analysis due to low-cost data acquisition using cheap large-scale detectors and fast computer networks that enable us to share large volumes of data. It is common to consider the effects of inhomogeneous spatial and temporal coverage in the analysis of big astronomical data. The growing size of the data requires us to use parallel distributed computing environments as well as machine learning algorithms. Distributed data analysis systems have not been adopted widely for the general analysis of massive astronomical data. Gathering adequate training data is expensive in observation and learning data are generally collected from multiple data sources in astronomy; therefore, semi-supervised and ensemble machine learning methods will become important for the analysis of big astronomical data.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.449-452
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• 2008

The building heights of big cities which charged with most space are 3-D information as relative vertical distance from ground control points, but they didn't know the heights using contour with maps as lose of skyline or building heights for downtown, practically continuously developed of many technology methods for implementation of 3-D spatial earth. So, For the view as stereos of variety earth form generated 3-D spatial and made terrain perspective map, 3-D simulated of regional and urban space as aviation images. In this papers, it composited geospatial informations and images by DEM generation, and developed and presented for techniques overlay of CAD data and photos captured at our surroundings uses. Particularly, The airborne LiDAR surveying which are very interesting trend have laser scanning sensor and determine the ground heights through detecting angle and range to the grounds, and then designated 3-D spatial composite and simulation from urban areas. Therefore in this papers are suggested ease selections on the users situation by compare as various simulations that its generation of 3-D spatial image by collective for downtown space and urban sub, and the implementation methods for more accurate, more select for the best images.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.161-171
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• 2018

This study set out to identify crime vulnerable areas with the GIS spatial analysis technique for the prediction of crimes. Crime vulnerable areas were extracted from the statistics of crimes with the GIS hotspot analysis technique and the inverse distance weighted(IDW) method applied to different crimes according to places and use districts. The scope of surveillance and weight were calculated for each of CPTED surveillance elements including CCTV, streetlamp, patrol division, and police substation. Maps of crime vulnerable areas were overlapped one after another to make a CPTED-based one expressed in four grades(safety, attention, warning, and risk).

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.19-33
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• 2024

CCTV for crime prevention is expanding; however, due to the absence of guidelines for determining installation locations, CCTV is being installed in locations unrelated to areas with frequent crime occurrences. In this study, we developed a CCTV Priority Installation Index and applied it in a case study area. The index consists of crime vulnerability and surveillance vulnerability indexes, calculated using machine learning algorithms to predict crime incident counts per grid and the proportion of unmonitored area per grid. We tested the index in a pilot area and found that utilizing the Viewshed function in CCTV visibility analysis resolved the problem of overestimating surveillance area. Furthermore, applying the index to determine CCTV installation locations effectively improved surveillance coverage. Therefore, the CCTV Priority Installation Index can be utilized as an effective decision-making tool for establishing smart and safe cities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1670-1675
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• 2021

The adoption of smart construction technology in the construction industry is progressing rapidly. By utilizing smart construction technologies such as BIM (Building Information Modeling), drones, artificial intelligence, big data, and Internet of Things technology, it has the effect of lowering the accident rate at the construction site and shortening the construction period. In order to introduce a digital twin platform for construction site management, real-time construction site management is possible in real time by constructing the same virtual space. The digital twin virtual space construction method collects and processes data from the entire construction cycle and visualizes it using a 3D model file. In this paper, we introduce a modeling automation technique that constructs an efficient digital twin space by automatically generating 3D modeling that composes a digital twin space based on 3D spatial data.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2005.10a
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• pp.479-484
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• 2005

A GIS-based integrated system for reuse of effluent from wastewater treatment plants was developed in this study. The GIS-supported program classified attribute data which the effluent's quantity and quality and agricultural thematic map data according to the 5 big river basin area. From the database, showing the spatial variation of the water quality of the effluent, thereby proposing proper mitigation strategies over the watershed. Also, this system enables the users who is going to reuse the reclaimed water for their paddies to provide of all the wastewater treatment plant data and agricultural structures and thematic map data.

• Spatial Information Research
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• v.23 no.2
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• pp.21-29
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• 2015

Recently, according to the increasingly populated data, many media and organizations focus on big data, data visualization, information visualization and infographics. Domestically, Chosun.com and Hankyoreh online have improved on the data visualization field and internationally, the Guardian, Wall Street Journal, and New York Times are the leading companies on that area. Until now, many people have recognized infographics as a design-oriented product in Korea. However, one of significant data visualization programs, Tableau Public, can visualize data more efficiently. In this paper, Data Visualization Methods Quadrant for Policy Making is defined, and data analysis and producing infographics are executed. As used data, World Bank open source was adopted and using the number of passenger cars per 1,000 people, two analysis results are extracted. First, in high income group, the more GNI per capita, the lesser Slope is represented and in mid income group, the more GNI per capita positively affects to Slope. Second, in the global finance crisis, the car ownership rate was about 1.7 times than the usual state in the global economy. Through the case study, this paper suggests that the direction of producing infographics should be changed from design-oriented to data-oriented. Moreover, the data-oriented infographics should be propagated as means of scientific research and policy making.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.72-81
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• 2014

As big data are one of main issues in the recent days, the interests on their technologies are also increasing. Among several technological bases, this study focuses on data visualization and R based on open source. In general, the term of data visualization can be summarized as the web technologies for constructing, manipulating and displaying various types of graphic objects in the interactive mode. R is an operating environment or a language for statistical data analysis from basic to advanced level. In this study, a web application with these technological aspects and components is newly implemented and exemplified with data visualization for geo-based open data provided by public organizations or government agencies. This application model does not need users' data building or proprietary software installation. Futhermore it is designed for users in the geo-spatial application field with less experiences and little knowledges about R. The results of data visualization by this application can support decision making process of web users accessible to this service. It is expected that the more practical and various applications with R-based geo-statistical analysis functions and complex operations linked to big data contribute to expanding the scope and the range of the geo-spatial application.