• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.5
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• pp.531-538
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• 2016

Driving behaviors such as speeding and illegal u-turn which violate traffic rules are main causes of car accidents, and they can lead to serious accidents. Bus drivers are less aware of dangers of illegal u-turn, and infrastructures such as traffic enforcement equipment and watchmen are deficient. This research aims to develop technology for estimating driving behaviors based on map-matching in order to prevent illegal u-turns. For this research, 23,782 of u-turn permit data and 146,000 of speed limit data are collected nationwide, and an estimation algorithm is built with these data. Then, an application based on android is developed, and finally, tests are conducted to assess the accuracy in data computations and GPS data map-matching, and to extrapolate driving behavior. As a result of the tests, the accuracy results in the map-matching is 86% and the assessment of driving behavior is 83%, while the display of the data output yielded 100% accuracy. Additional research should focus on improvement in accuracy through the development of a robust monitoring system, and study of service scenarios for technology application.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.774-784
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• 2021

The object detection and recognition process is a very important task in the field of computer vision, and related research is actively being conducted. However, in the actual object recognition process, the recognition accuracy is often degraded due to the resolution mismatch between the training image data and the test image data. To solve this problem, in this paper, we designed and developed an integrated object recognition and super-resolution framework by proposing an image super-resolution technique to improve object recognition accuracy. In detail, 11,231 license plate training images were built by ourselves through web-crawling and artificial-data-generation, and the image super-resolution artificial neural network was trained by defining an objective function to be robust to the image flip. To verify the performance of the proposed algorithm, we experimented with the trained image super-resolution and recognition on 1,999 test images, and it was confirmed that the proposed super-resolution technique has the effect of improving the accuracy of character recognition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1486-1494
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• 2021

Character recognition is a technology required in various platforms, such as smart parking and text to speech, and many studies are being conducted to improve its performance through new attempts. However, with low-quality image used for character recognition, a difference in resolution of the training image and test image for character recognition occurs, resulting in poor accuracy. To solve this problem, this paper designed an end-to-end learning neural network that combines image super-resolution and character recognition so that the character recognition model performance is robust against various quality data, and implemented an alternative whole learning algorithm to learn the whole neural network. An alternative end-to-end learning and recognition performance test was conducted using the license plate image among various text images, and the effectiveness of the proposed algorithm was verified with the performance test.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8940-8947
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• 2015

Mixed-model assembly line has been widely used in automotive assembly industry to quickly respond the diverse product demands. But, this model can lead to part confusion, which is a source for assembly errors when parts are physically interchangeable in a mixed-model assembly line. With the recent application of new technologies such as radio frequency identification (RFID) and ZigBee wireless sensor network (WSN) to the assembly process, real-time information has become available in this manufacturing systems through IT infrastructures. At first, this paper presents an RFID application for assembly processes, specifically, for a mixed-model assembly line. Thus, to ensure that parts be picked accurately, each cockpit module on the assembly line is attached with a RFID tag and the tag is scanned using a RFID reader and recognizes the vehicle, and each part of the cockpit module is attached with a barcode and the barcode is scanned by a barcode reader and each part is identified correctly for the vehicle. Second, this paper presents a ZigBee wireless sensor network (WSN) protocol-based application for a reconfigurable mixed-model assembly line of cockpit module to reduce the assembly errors and the cost of the change/reconfiguration on the assembly lines due to the various orders and new models from the motor company, avoiding the wiring efforts and inconvenience by wiring between the several RFID devices and the IT server system. Finally, we presents the operation results for several years using this RFID/ZigBee wireless sensor network (WSN) protocol-based cockpit module assembly line.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.149-155
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• 2013

Recently, automobile traffic systems are evolving toward Intelligent Traffic Systems(ITS) with smart sensor technology and collaboration between traffic systems and external ones. On the contrary, Korean ITS services have little improvement comparing with other communication services. The main causes of this phenomenon are due to already allocation of ITS recommended frequency band to broadcasting services, and also dedication of DSRC frequency band over ISM band resulting in interferences. This paper provides the analysis of current Korean ITS technology status, and two suggestions to activate the ITS industry. First, need to fix the ITS standard combining WAVE and DSRC specifications soon. Second, ITS frequency allocation to complete its standard implementation in near time frame.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1D
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• pp.21-27
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• 2008

To respond to years-long economic decline in the downtown Seoul, it is necessary to lay out a scheme revitalizing downtown economy. It is called Wanavi and Shonavi system. When customers do shopping, it is the "Shonavi" that provides shopping information such as popular shop name, location, and commodity price to walkers in a real-time base. In addition, the walking navigation system called "Wanavi" is designed to provide access information for walking shoppers, the function of which is similar to car navigation system. The "Wanavi" can help walkers find the fastest, comfortable and attractive pedestrian route and public transportation information reaching to the destination in the downtown. In this study, we propose GPA & RFID mixed system as a communication technique to activate "Shonavi" and "Wanavi" system. The "Shonavi" and "Wanavi" system will be one of the ways to revitalize depressed downtown economy in Seoul.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.630-633
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• 2021

Microphones can convert received voice signals to electric signals. They have been widely used in various industries such as radios, smart devices and vehicles. Recently, the demands for small size and high sensitive microphones are increased according to the minimization of wireless earphone with the development of smart phone. A MEMS system is a good candidate for an ultra-small size microphone of a next generation and a read out IC for high sensitive MEMS sensor is researched from many industries and academies. Since the microphone system has a high sensitivity from environment noise and electric system noise, the system requires a low noise power supply and some low noise design techniques. In this paper, a low noise LDO is presented for small size MEMS microphone systems. The input supply voltage of the LDO is 1.5-3.6V, and the output voltage is 1.3V. Then, it can support to 5mA in the light load condition. The integrated output noise of proposed LDO form 20Hz to 20kHz is about 1.9uV. These post layout simulation results are performed with TSMC 0.18um CMOS technology and the size of layout is 325㎛ × 165㎛.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.71-78
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• 2012

The digital tachograph is a device that automatically records speed and distance of a vehicle, together with the driver's activity and vehicle status at an accident. It records vehicle speed, break status, acceleration, engine RPM, longitude and latitude of GPS, accumulated distance, and so on. European Commission regulation made digital tachographs mandatory for all trucks from 2005. Republic of Korea made digital tachographs mandatory for all new business vehicles from 2011 and is widening the range of vehicles that must install digital tachographs year by year. This device is used to analyze driver's daily driving information and car accidents. Under a car accident that makes the device reliability unpredictable, it is very important to store driving information with maximum reliability for its original mission. We designed and implemented a practical digital tachograph. This paper presents a storage scheme that consists of a first storage device with small capacity at a high reliability and a second storage device with large capacity at a low cost in order to reliably records data with a hardware at a low cost. The first storage device records data in a SLC NAND flash memory in a log-structured style. We present a reverse partial scan that overcomes the slow scan time of log-structured storages at the boot stage. The scheme reduced the scan time of the first storage device by 1/50. In addition, our design includes a scheme that fast stores data at a moment of accident by 1/20 of data transfer time of a normal method.