• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1201-1208
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• 2008

Ubiquotuous technology should be adopted in railroad business to provide passenger's security and convenience. In this project, IT and smart sensor technologies are reviewed, benchmarked, designed, and implemented. The target system is the next generation high speed train to be developed and operated in Korea with the maximum speed of 400km/h. Wireless sensor network with smart sensors is implemented around a train car. PC-like IT terminal will be designed and implemented so an individual passenger can use it to do information retrieval through the Internet, personal data processing, the e-learning, shopping on the railroad, and so on. These provision will give comfort, convenience, and safety of a passenger during his/her trip.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.463-470
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• 2005

This paper describes a method aimed at improving dead-reckoning accuracy with gyroscopes in mobile robots. The method is a precision calibration procedure for gyroscopes, which effectively reduces the ill effects of nonlinearity of the scale-factor and temperature dependency. This paper also describes the methods of gyro data collection fur all ambient temperature$(-40^{\circ}C{\~}+80^{\circ}C)$ using cubic spline interpolation and defining the error function. The sensor used was a vibrating gyroscope called the EWTS82NA21, which is low lost and commonly used in car navigation system, made by Panasonic. This angular rate sensor utilizes Coriolis force generated by a vibrating tuning fork. The paper also provides experimental results to check the performance and the effectiveness of the proposed method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.47-53
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• 2012

Sensor networks and car networks that have different structure from that of conventional TCP/IP network require extreme network environment due to frequent change of connectivity. Because such extreme network environment has characteristics like unreliable link connectivity, long delay time, asymmetrical data transfer rate, and high error rate, etc., it is difficult to perform normally with the conventional TCP/P-based routing. DTNs (delay and disruption tolerant network) was designed to support data transfer in extreme network environment with long delay time and no guarantee for continuous connectivity between terminals. This study suggests an algorithm that limits the maximum number of copying transferred message to L by improving the spray and wait routing protocol, which is one of the conventional DTNs routing protocols, and using the azimuth and density data of the mobile nods. The suggested algorithm was examined by using ONE, a DTNs simulator. As a result, it could reduce the delay time and overhead of unnecessary packets compared to the conventional spray and wait routing protocol.

• Journal of IKEEE
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• v.23 no.1
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• pp.159-163
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• 2019

The food service industry has been grown due to improvement of living standards. In addition, the demand for frozen food delivery is increasing day by day at online/offline and the refrigerated vehicles are used in most of these food distributions. One of the most important factors in a refrigerated car is to measure the temperature accurately. Conventional temperature recording systems are generally connected directly to temperature sensor modules. Since the temperature data are transmitted to the temperature recorder by using the electric wire, there is a disadvantage that the resistance error must be compensated according to the cable length. In this paper, we propose a method to correct errors due to cable resistance using digital processing and CAN (Controller Area Network) communication. We use PT-1000 platinum sensor to increase the accuracy of the temperature measurement.

• Spatial Information Research
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• v.21 no.6
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• pp.57-67
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• 2013

GPS based car navigation systems show significant problems in such environment as a tunnel, a road surrounded by high buildings. In this study, we thus propose a method to determine positions and attitudes using only in-vehicle sensory data without a GPS. To check the feasibility of this method, we constructed a system to acquire in-vehicle sensory data and reference data simultaneously. We acquired test data using this system, estimated the trajectory based on the proposed method and evaluated the accuracy of both the sensory data and the trajectory. The speed and angular velocities provided by the in-vehicle sensors include 1.1 km/h and 0.8 deg/s RMS errors, respectively. The estimated trajectory using these data shows 20.8 m RMS errors for a 15 minute drive. In future, if we further combine additional sensors such as a camera and a GPS, we can achieve a high accurate navigation system at a low cost without an expensive high-grade external IMU.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.74-80
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• 2009

Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.2
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• pp.21-29
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• 2017

For the efficient and stable operation of autonomous vehicles or advanced driver assistance systems being actively studied nowadays, it is important to determine the positions of the vehicle accurately and economically. A satellite based navigation system is mainly used for positioning, but it has a limitation in signal blockage areas. To overcome this limitation, sensor fusion methods including additional sensors such as an inertial navigation system have been mainly proposed but the high sensor cost has been a problem. In this work, we develop a vehicle position estimation algorithm using in-vehicle sensors and a low-cost imaging sensor without any expensive additional sensor. We determine the vehicle positions using the velocity and yaw-rate of a car from the in-vehicle sensors and the position and attitude of the camera based on the single photo resection process. For the evaluation, we built a prototype system, acquired test data using the system, and estimated the trajectory. The proposed algorithm shows the accuracy of about 40% higher than an in-vehicle sensor only method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.3
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• pp.374-380
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• 2017

The Internet of Things (IoT) refers to intelligent technologies and services that connect all things to the internet so they can interactively communicate with people, other things, and other systems. The development of the IoT environment accompanies advances in network protocols applicable to more lightweight and intelligent sensors, and lightweight and diverse environments. The development of those elemental technologies is promoting the rapid progress in smart car environments that provide safety features and user convenience. These developments in smart car services will bring a positive effect, but can also lead to a catastrophe for a person's life if security issues with the services are not resolved. Although smart cars have various features with different types of communications functions to control the vehicles under the existing platforms, insecure features and functions may bring various security threats, such as bypassing authentication, malfunctions through illegitimate control of the vehicle via data forgery, and leaking of private information. In this paper, we look at types of smart car services in the IoT, deriving the security threats from smart car services based on various scenarios, suggesting countermeasures against them, and we finally propose a safe smart car application plan.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.546-548
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• 2019

In recent days, vehicle safety technologies for supporting safe vehicle driving attract public attention. This paper proposes multi-log platform based vehicle safety system (MLPVSS) that analyzes multi-log data (i.e., log-data on human, object, and place) and supports vehicle safety. The MLPVSS gathers sensor data and image data on the human, object, and place, and then generates multi-log data that are context-aware data on the human, object, and place. The MLPVSS can detect, predict, and response vehicle dangers. The MLPVSS can contribute to reduce car accidents.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.646-653
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• 2021

The medical bed developed in this study consists of N keys and each is driven vertically by an actuator. Since M sensors are mounted on each keyboard to measure body pressure, the resolution of the body pressure map is determined by the MN. A sensor controller is mounted on each keyboard, and the body pressure values measured from M sensors are transmitted to the main controller through a serial communication network such as CAN (Car Area Network). Each keyboard is equipped with a servo driver that drives a motor, and it is connected to the main controller via CAN to control the height of the keyboard according to the displacement value indicated by the main controller. In addition, the maximum body pressure value and body pressure ratio applied to each part of the keyboard are calculated and used as the basic data for controlling bed comfort by artificial intelligence. As a result, the proposed system can be a foundation that can be used for the control of body comfort and pressure sore prevention by artificial intelligence to be developed in the future.