• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.4
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• pp.173-179
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• 2017

Autobike is insufficient of car navigation informations and high of accident dangerousness comparing to car. So if a system providing autobike driver's driving information and e-call function is developed using smart helmet consisting of collision perception sensor, rear camera, bluetooth communication module, MCU and HUD, It is very useful and can decrease of person's damage and handle expeditious traffic accident during autobike accident. In this paper, when this, "Providing system of autobike driver's information and e-call function", software is developed, a proper analysis and design method for practical affairs try to be presented due to showing software development analysis method, architecture of hardware block-diagram, flowchart and UI design.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.5
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• pp.9-15
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• 2013

In this paper, automatic recognition of an accident and whether service delivery and risk driving through the giving of the driver to correct driving habits before and after the accident to reproduce highly scalable video Smart Mobile Blackbox DVR (SMBD, Smart Mobile Blackbox DVR) Computer of the model was designed. SMBD on embedded systems equipped with wireless capabilities to sleep in the car accident point and the image information by wireless communications, by notification in the control center, 24-hour emergency rescue service and traffic information can be provided. The vehicle ECU (Electronic Control Unit) of the vehicle information and sensor data in conjunction with wireless eCall (Emergency Call) services can be realized.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.325-328
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• 2010

In this paper, To overcome expression limit of Normal LCD(Seg) for Car audio, We research using Smart phone(Iphone) LCD to overcome weakness of seg LCD, We can express detail LCD DISPLAY using Smartphone(iphone), We can call Car to phone, Smartphone(Iphone) Display can Normal Car audio function Display, using phone Application for car to phon.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.159-163
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• 2004

현재 복수개의 엘리베이터를 최적 제어하기 위해서 엘리베이터 군 제어 시스템이 사용되고 있다. 일반적인 엘리베이터 군 제어 시스템에서는 임의의 층에서의 호출(Hall Call)에 대해 복수개의 엘리베이터로부터 정보를 받는다. 다음으로 각 엘리베이터의 매력함수값을 산출, 매력함수들을 비교 한 후 가장 큰 값을 갖는 엘리베이터를 호출한 층으로 보내는 작업을 수행한다. 본 논문에서는 16개의 엘리베이터와 정렬 네트워크(Sorting Network)를 이용하여 각 엘리베이터들의 매력함수값의 비교를 수행하는 엘리베이터 군 제어부를 설계한다. 이를 통해 제어부에서 매력함수값들의 비교 연산에 소요되는 처리속도를 향상시킬 수 있다.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.81-85
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• 1997

In a virtual environment, agents must demonstrate some degree of realism and interactivity. This paper discusses the algorithm that enables agents to navigate a virtual road network realistically and interactively. The road description files written in this language provide the information of road environments to the navigating agents and the scene visualizer. We call this navigating agent in the road an ambient car. The ambient cars must follow the traffic rules as human does. To do this, the ambient car should continuously check its circumstances, such as, the traffic lights, lanes, road signs, and other ambient cars. Because of the huge scale of road network and the large number of ambient cars, the algorithm considers only the area where the participant is currently located. By this locality, the performance of the whole system does not fluctuate much in different situations. The behavior of ambient cars according to the predefined rules may appear monotonous. We added probability distribution functions to introduce some randomness. We implemented the above idea on silicon Graphics Indigo 2 workstation. The ambient car exhibited its awareness of lanes, traffic lights, and other cars. The participants could hardly distinguish between a human-controlled car and computer-controlled ambient car generated by the algorithm.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1113-1118
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• 2002

In recognition system of the car license plate, the most important is to extract the image of the license plate from a car image. In this paper, we use ACL (Adaptive Color Luminance) algorithm to extract the license plate image from a car image. The ACL algorithm that uses color and luminance information of a car image is used to extract the image of the license plate. In this paper, color, luminance and other related information of a car image are used to extract the image of the license plate from that of a car. In this reason, we call it the ACL algorithm. The ACL algorithm uses color, luminance information and other related information of a license plate. These informations are avaliable to exact the image of the license plate. The rate of extracting the image of the license plate from a car is 97%. The experimental result of the ACL algorithm for the character region is 92%.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.301-303
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• 2012

In this Paper, we are implemented position awareness system based on one-pass tag. This system are combined ZigBee and RFID technology. We developed the solution to detect of user's position using position awareness receiver and repeater. This location recognition includes parked car location tracking, coming in and out car, automation of immigration control, enhanced security through emergency call, and automatic invocation elevator control and etc.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.346-348
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• 2002

차량 항법 시스템(Car Navigation System)은 요즘 많은 발전을 거듭하여 차량 이용시 사용자가 가고자하는 목적지까지의 길을 쉽게 안내하고 있다. 이런 기술의 발전은 단순한 정적인 길 안내(Static Route Guidance) 뿐만 아니라. 동적인 길 안내(Dynamic Route Guidance)를 함으로써 자동차 운전자가 쉽고 빠른 길을 안내 받을 수 있게 되었다. 그러나 이러한 교통정보는 매우 변화가 심하므로 최초로 경로를 전송 받은 후 그 경로상에 교통정보가 변화하였다면, 이미 전송 받은 경로는 실시간으로 적극적으로 대응할 수 없고 실제 막히는 길로 안내할 수 있다. 목적지까지의 거리가 먼 경우 이런 현상이 더욱 심하게 나타날 수 있다. 이런 경우 운전자는 실제로는 막히는 길로 안내 받을 수 밖에 없다. 이런 문제점을 해결하기 위해 교통정보를 수집하는 기존의 시스템에 Ad Hoc 네트워킹이 가능한 시스템을 탑재한 교통정보 수집 차량(Probe Car)을 이용한다. 정보 수집 차량이 극심한 정체를 발견하면 근처를 지나는 경로를 가진 차량에게 이를 전달하여 새로운 경로를 다운받을 수 있도록 한다. 이런 방법은 Ad Hoc Relaying System〔l〕을 이용하여 가능하며, 센터에 수집되고 가공되는 시간을 최대한 줄일 수 있으며, 센터의 통신 오버헤드를 최소화할 수 있다. 또한 기지국에 호가 집중되어 call blocking이 발생함 경우에 이를 해결할 수 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.1-12
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• 2008

In this paper, we described about core technologies required for the seamless service implementation and the communication system structure conceiving required for call & response services in order that the real-time traffic information service is consecutively provided to the vehicle moving at high speed. The SMART highway service is the information communication environment build-up concept which the real-time C&R service is comprised of the vehicle moving with 160km/h above. It was possible in case of being the low speed car in the DSRC system structure. However, there is a limit in the high speed environment as the DSRC system like a convention. In this paper, we proposed the structure of fitting for the SMART highway environment using the hand-over technique compositing the base station and several repeaters of DSRC system.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.99-120
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• 2010

Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.