• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3672-3679
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• 2012

Vehicle Ad hoc Network (VANET) is next-generation network technology to provide various services using V2V (Vehicle-to-Vehicle) and V2I (Vehicle-to-Infrastructure). In VANET, many researchers proposed various studies for the safety of drivers. In particular, using the emergency message to increase the efficiency of traffic safety have been actively studied. In order to efficiently transmit to moving vehicle, to send a quick message to as many nodes is very important via broadcasting belong to communication range of vehicle nodes. However, existing studies have suggested a message for transmission to the communication node through indiscriminate broadcasting and broadcast storm problems, thereby decreasing the overall performance has caused the problem. In addition, theses problems has decreasing performance of overall network in various form of road and high density of vehicle node as urban area. Therefore, this paper proposed Clustering based Routing Algorithm (CBRA) to efficiently transmit emergency message in high density of vehicle as urban area. The CBRA managed moving vehicle via clustering when vehicle transmit emergency messages. In addition, we resolve linkage problem between vehicles according to various form of road. The CBRA resolve link brokage problem according to various form of road as urban using clustering. In addition, we resolve broadcasting storm problem and improving efficacy using selection flooding method. simulation results using ns-2 revealed that the proposed CBRA performs much better than the existing routing protocols.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.213-224
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• 2009

This paper presents a new algorithm for estimating a driver's physical condition using real-time vision system and performs experimentation for real facial image data. The system relies on a face recognition to robustly track the center points and sizes of person's two pupils, and two side edge points of the mouth. The face recognition constitutes the color statistics by YUV color space together with geometrical model of a typical face. The system can classify the rotation in all viewing directions, to detect eye/mouth occlusion, eye blinking and eye closure, and to recover the three dimensional gaze of the eyes. These are utilized to determine the carelessness and drowsiness of the driver. Finally, experimental results have demonstrated the validity and the applicability of the proposed method for the estimation of a driver's physical condition.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.387-399
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• 2009

Mobile wireless networks continue to be plagued by theft of identify and intrusion. Both problems can be addressed in two different ways, either by misuse detection or anomaly-based detection. In this paper, we propose a dissimilarity-based anomaly detection method which can effectively identify abnormal behavior such as mobility patterns of mobile wireless networks. In the proposed algorithm, a normal profile is constructed from normal mobility patterns of mobile nodes in mobile wireless networks. From the constructed normal profile, a dissimilarity is computed by a weighted dissimilarity measure. If the value of the weighted dissimilarity measure is greater than the dissimilarity threshold that is a system parameter, an alert message is occurred. The performance of the proposed method is evaluated through a simulation. From the result of the simulation, we know that the proposed method is superior to the performance of other anomaly detection methods using dissimilarity measures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.947-950
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• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Journal of KIISE:Information Networking
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• v.29 no.3
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• pp.314-323
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• 2002

The routing protocols designed for wired networks can hardly be used for mobile ad-hoc networks due to limited bandwidth of wireless transmission and unpredictable topological change. Recently, several routing protocols for mobile ad-hoc networks have been Proposed. However, when theme protocols are applied to support real time services like multimedia transmission, they still have problems in ad-hoc networks, where the topology changes drastically. In this paper, we propose a new route selection algorithm which selects the most reliable route that is impervious to route failures by topological changes by mobile hoots. For reliable route selection, the concept of virtual zone (stable zone and caution zone) is proposed. The zone is located in a mobile node'transmission range and determined by mobile node's mobility information received by Global Positioning System (GPS). The proposed algorithm is applied to the route discovery procedure of the existing on-demand routing protocol, AODV, and evaluated by simulation in various traffic conditions and mobility patterns.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.4
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• pp.315-321
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• 2017

This paper is a study on the design and realization of Pedestrian navigation service system for the visually impaired. As it is an user interface considering visually impaired, voice recognition functioned smartphone was used as the input tool and the Osteoacusis headset, which can vocally guide directions while recognizing the surrounding environment sound, was used as the output tool. Unlike the pre-existing pedestrian navigation smartphone apps, the developed system guides walking direction by the scale of the left and right stereo sound of the headset wearing, and the voice guidance about the forked or curved path is given several meters before according to the speed of the user, and the user is immediately warned of walking opposite direction or proceeding off the path. The system can acquire stable and reliable directional information using the motion tracker with the dynamic heading accuracy of 1.5 degrees. In order to overcome GPS position error, we proposed a robust trajectory planning algorithm for position error. Experimental results for the developed system show that the average directional angle error is 6.82 degrees (standard deviation: 5.98) in the experimental path, which can be stated that it stably navigated the user relatively.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.1-10
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• 1999

A mobile computing environment is one that support user's mobility through the wireless communication technology. Users access the database and get results what they want by running mobile transactions. To run the mobile transaction correctly and to maintain the consistency I database, we need a concurrency control method to schedule transactions, a caching method to manage the cache, and a recovery method to construct a fault tolerant system. A mobile computing system is based on the existing distributed system, but we can't use recovery methods of the existing distributed system directly because of the user's mobility and the features of wireless media. So this paper presents a recovery mechanism to construct a fault tolerant mobile computing systems. Especially. we develop and analyze a recovery algorithm for server failure among types of failure which can arise in mobile computing environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.962-970
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• 2021

The cause of the majority of vehicle accidents is a safety issue due to the driver's inattention, such as drowsy driving. A forward collision warning system (FCWS) can significantly reduce the number and severity of accidents by detecting the risk of collision with vehicles in front and providing an advanced warning signal to the driver. This paper describes a low power embedded system based FCWS for safety. The algorithm computes time to collision (TTC) through detection, tracking, distance calculation for the vehicle ahead and current vehicle speed information with a single camera. Additionally, in order to operate in real time even in a low-performance embedded system, an optimization technique in the program with high and low levels will be introduced. The system has been tested through the driving video of the vehicle in the embedded system. As a result of using the optimization technique, the execution time was about 170 times faster than that when using the previous non-optimized process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.111-116
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• 2021

This study is a study on improving the pedestrian Care system, which delivers jaywalking events in real time to the autonomous driving control center and Autonomous driving vehicles in operation and issues warnings and announcements to pedestrians based on pedestrian signals. In order to secure reliability of object detection method of pedestrian Care system, the inspection method combined with camera sensor with Lidar sensor and the improved system algorithm were presented. In addition, for the occurrence events of Lidar sensors and intelligent CCTV received during the operation of autonomous driving vehicles, the system algorithm for the elimination of overlapping events and the improvement of accuracy of the same time, place, and object was presented.

• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.17-25
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• 2019

Accurate tracking of the sinkholes that are appearing frequently now is an important method of protecting human and property damage. Although many sinkhole detection systems have been proposed, it is still far from completely solved especially in-depth area. Furthermore, detection of sinkhole algorithms experienced the problem of unstable result that makes the system difficult to fire a warning in real-time. In this paper, we proposed a method of sinkhole tracking by deep learning and data association, that takes advantage of the recent development of CNN transfer learning. Our system consists of three main parts which are binary segmentation, sinkhole classification, and sinkhole tracking. The experiment results show that the sinkhole can be tracked in real-time on the dataset. These achievements have proven that the proposed system is able to apply to the practical application.