• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.78-84
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• 2017

Because the 'Internet of Things' and sensor network technology have become a new generation industry competitiveness with a development of Information Communication Technology, each local autonomous entity is trying to adopt a Smart City quickly. This requires an integrated platform inside of a smart city operation center. Established Smart City platform provides various services using CCTV information and ITS transportation information based on a two-dimensional map. The provision of advanced Smart City services will necessitate three-dimensional map information, building and facilities unit information, linked information with public data portal for service to the public. In this paper, the authors reviewed development trends of Smart City integrated platform and proposed mashup methods between BIM/GIS interoperability platform and external open data. BIM/GIS platform can provide spatial information services for indoor and outdoor seamlessly because it was developed based on GIS spatial data with BIM data. The linked external open data are V-World data, Seoul Open Data, and Architectural Data Open. Finally, the authors proposed the direction of development for BIM/GIS integrated platform to provide advanced Smart City services.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.519-524
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• 2006

This paper describes an application of information presentation based geographic map for maritime information, including navigation information. The work is motivated by the need to prepare maritime information representation and distribution for future generation Web network technology. This works consist of map generation using GML and application to maritime information. GML 3.0 became an adopted specification of the Open Geospatial Consortium(OGC) in January 2003, and is rapidly emerging as the world standard for the encoding, transport and storage of all forms of geographic information. This paper looks at the application of GML to one of the more challenging areas of maritime information. Specific features of GML of interest to maritime information provider are discussed and then illustrated through a series of maritime information case studies. The first phase of the work consists of the construction of GML application schema for using as a base map of maritime information. Maritime information is acquired from multiple sources, including standards documents, database schemas, lexicons, collections of symbol definition. The sources of GML ontological knowledge and the contribution of each source to the overall ontology are described in this paper. In the second phase, the prepared GML is used to create a prototype of the mixed maritime information as a base map - for tagging documents within the maritime domain. An overview of this prototype is included. One application area for these information elements described here is the integrated retrieval of maritime information from diverse sources, ranging from Web sites to nautical chart databases and text documents.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.511-517
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• 2006

Flood damage is one of the most important and influential natural disaster which has an effect on human beings. Local concentrated heavy rainfall in urban area yields flood damage increase due to insufficient capacity of drainage system. When the excessive flood occurs in urban area, it yields huge property losses of public facilities involving roadway inundation to paralyze industrial and transportation system of the city. To prevent such flood damages in urban area, it is necessary to develop adequate inundation analysis model which can consider complicated geometry of urban area and artificial drainage system simultaneously. In this study, an urban flood analysis model adopting the unstructured computational grid was developed to simulate the urban flood characteristics such as inundation area, depth and integrated with subsurface drainage network systems. By the result, we can make use of these presented method to find a flood hazard area and to make a flodd evacuation map. The model can also establish flood-mitigation measures as a part of the decision support system for flood control authority.

• Journal of Korean Society of Transportation
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• v.22 no.2 s.73
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• pp.145-154
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• 2004

The growing demand for customer-responsive, made-to-order manufacturing is stimulating the need for improved dynamic decision-making processes in commercial fleet operations. Moreover, the rapid growth of electronic commerce through the internet is also requiring advanced and precise real-time operation of vehicle fleets. Accompanying these demand side developments/pressures, the growing availability of technologies such as AVL(Automatic Vehicle Location) systems and continuous two-way communication devices is driving developments on the supply side. These technologies enable the dispatcher to identify the current location of trucks and to communicate with drivers in real time affording the carrier fleet dispatcher the opportunity to dynamically respond to changes in demand, driver and vehicle availability, as well as traffic network conditions. This research investigates key aspects of real time dynamic routing and scheduling problems in fleet operation particularly in a truckload pickup-and-delivery problem under various settings, in which information of stochastic demands is revealed on a continuous basis, i.e., as the scheduled routes are executed. The most promising solution strategies for dealing with this real-time problem are analyzed and integrated. Furthermore, this research develops. analyzes, and implements hybrid algorithms for solving them, which combine fast local heuristic approach with an optimization-based approach. In addition, various partitioning algorithms being able to deal with large fleet of vehicles are developed based on 'divided & conquer' technique. Simulation experiments are developed and conducted to evaluate the performance of these algorithms.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.147-158
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• 2004

A class of SWP(Stochastic Wane Propagation) models microscopically mimics individual vehicles' stochastic behavior and traffic jam propagation with simplified car-following models based on CA(Cellular Automata) theory and macroscopically captures dynamic traffic flow relationships based on statistical physics. SWP model, a program-oriented model using both discrete time-space and integer data structure, can simulate a huge road network with high-speed computing time. However, the model has shortcomings to both the capturing of low speed within a jam microscopically and that of the density and back propagation speed of traffic congestion macroscopically because of the generation of spontaneous jam through unrealistic collision avoidance. In this paper, two additional rules are integrated into the NaSch model. The one is SMR(Stopping Maneuver Rule) to mimic vehicles' stopping process more realistically in the tail of traffic jams. the other is LAR(Low Acceleration Rule) for the explanation of low speed characteristics within traffic jams. Therefore, the CA car-following model with the two rules prevents the lockup condition within a heavily traffic density capturing both the stopping maneuver behavior in the tail of traffic jam and the low acceleration behavior within jam microscopically, and generates more various macroscopic traffic flow mechanism than NaSch model's with the explanation of propagation speed and density of traffic jam.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6604-6610
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• 2015

In this paper, an efficient Wireless Access in Vehicular Environment (WAVE) packet transmission scheme for railroad communication is proposed. WAVE communication is a wireless local area network (WLAN) based communication and it is developed to be suitable for vehicular communication. There has been a lot of study on WAVE's applicability to Intelligent Transport System (ITS). As one of main transportation methods, by using WAVE, quality of railroad communication including WLAN based Communication Based Train Control (CBTC) can be enhanced and variety of railroad communication systems can be integrated into WAVE. However, there are technical challenges to adopt WAVE in railroad communications. For the simplest single-PHY WAVE, time division alternation of 50ms between Control Channel (CCH) and Service Channel (SCH) is required. Since there are delay sensitive railroad traffic types, alternation operation of CCH and SCH may cause performance degradation. In this paper, after identifying a couple of problems based on detailed analysis, a novel packet transmission scheme under railroad environment is proposed. In order to verify if the proposed scheme meets the requirement of railroad communication, WAVE transmission is mathematically modeled.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1701-1708
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• 2011

A typical day in the subway transportation is used by hundreds of thousands are also concerned about the safety of the various workrooms with high underground fire or other less than in the subway users could be damaging even to be raised and there. In 2010, in fact, room air through vents in the fire because smoke and toxic gas accident victims, and train service suspended until such cases are often reported. In response to these incidents in subway stations, even if the latest IT technology, wireless sensor network technology and intelligent video surveillance technology by integrating fire and structural integrity, such as a comprehensive integrated surveillance system to monitor the development of intelligent urban transit system and are under study. In this study, prior to the application of the monitoring system into the field stations, authors carried out the ZigBee-based wireless sensor networks performance analyzation in the Chungmuro station. The test results at a communications room and ventilation room of the station are summarized and analyzed.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.