• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.97-100
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• 2010

Lately, becausing Life, property loss from car accident, vehicles have been used vehicle blackbox like blackbox by airplane. when the accident happened, existing car blackbox that was stored external image or video of vehicle don't know the vehicle's driving conditions. For knowing vehicle's driving conditions, vehicle is loaded sensors for Variety of measurement and control. the sensors is controlled by ECU(Electronic Control Unit) and all vehicles is used Mandatory OBD2(On-board diagnostics) protocol for communication between ECUs since 2006. Using ODB2 protocol, driver use blackbox data by various driving data to occur vehicle' ECU and can be obtained more definitive information. In this paper, there implement smart blackbox system to use exact vehicle's data using OBD2 protocol rather than blackbox to store external image or video.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1762-1769
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• 2021

The final goal of this study is to develop a system that can analyze whether a wanted vehicle is a criminal vehicle from images collected from black boxes, smartphones, CCTVs, and so on. Data collection was collected using a self-developed black box. The used data in this study has used a total of 83,753 cases such as the eight vehicle types(truck, RV, passenger car, van, SUV, bus, sports car, electric vehicle) and 434 vehicle models. As a result of vehicle recognition using YOLO v5, mAP was found to be 80%. As a result of identifying the vehicle model with ReXNet using the self-developed black box, the accuracy was found to be 99%. The result was verified by surveying field police officers. These results suggest that improving the accuracy of data labeling helps to improve vehicle recognition performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1290-1293
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• 2021

Currently, blind people are experiencing a lot of inconvenience in their daily lives. In order to provide helpful service for the visually impaired, this study was carried out to make a new smart glasses that transmit information monitoring walking environment in real-time object recognition. In terms of object recognition, YOLOv4 was used as the artificial intelligence model. The objects, that should be identified during walking of the visually impaired, were selected, and the learning data was populated from them and re-learning of YOLOv4 was performed. As a result, the accuracy was average of 68% for all objects, but for essential objects (Person, Bus, Car, Traffic_light, Bicycle, Motorcycle) was measured to be 84%. In the future, it is necessary to secure the learning data in more various ways and conduct CNN learning with various parameters using darkflow rather than YOLOv4 to perform comparisons in the various ways.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.208-210
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• 2021

As the number of objects connected to the Internet increases rapidly, intelligent device development projects are gradually expanding that provide direct value to humans, away from simple monitoring functions, including sensors and communication functions, or delivery to servers.It is expected that the device will develop a technology that analyzes surrounding sensing information and changes the surrounding environment in consideration of users' preferences or safety. By establishing a biosignal measurement system in a developed product that can bring various effects using air, it will be possible to grasp the user's condition through a pattern of change in pressure distribution when seated. This paper proposes a construction system that enhances the comfort of using an air car seat through contact between a temperature measurement sensor and a user, and enables effective management of measured biosignals by linking them with an air pump control system.

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.320-327
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• 2023

In this study, an FPGA-based sealer inspection system was developed to inspect the sealer applied to install vehicle glass on a car body. The sealer is a liquid or paste-like material that promotes adhesion such as sealing and waterproofing for mounting and assembling vehicle parts to a car body. The system installed in the existing vehicle design parts line does not detect the sealer in the glass rotation section and takes a long time to process. This study developed a line laser camera sensor and an FPGA vision signal processing module to solve this problem. The line laser camera sensor was developed such that the resolution and speed of the camera for data acquisition could be modified according to the irradiation angle of the laser. Furthermore, it was developed considering the mountability of the entire system to prevent interference with the sealer ejection machine. In addition, a vision signal processing module was developed using the Zynq-7020 FPGA chip to improve the processing speed of the algorithm that converted the profile to the sealer shape image acquired from a 2D camera and calculated the width and height of the sealer using the converted profile. The performance of the developed sealer application inspection system was verified by establishing an experimental environment identical to that of an actual automobile production line. The experimental results confirmed the performance of the sealer application inspection at a level that satisfied the requirements of automotive field standards.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.29-43
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• 2019

The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.152-164
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• 2015

A rapid development of semiconductors, sensors and mobile network technologies has enable that the embedded device includes high sensitivity sensors, wireless communication modules and a video processing module for vehicular environment, and many researchers have been actively studying the smart car technology combined on the high performance embedded devices. The vehicle is increased as the development of society, and the risk of accidents is increasing gradually. Thus, the advanced driver assistance system providing the vehicular status and the surrounding environment of the vehicle to the driver using various sensor data is actively studied. In this paper, we design and implement the smart vehicular camera device providing the V2X communication and gathering environment information. And we studied the method to create the metadata from a received video data and sensor data using video analysis algorithm. In addition, we invent S-ROI, D-ROI methods that set a region of interest in a video frame to improve calculation performance. We performed the performance evaluation for two ROI methods. As the result, we confirmed the video processing speed that S-ROI is 3.0 times and D-ROI is 4.8 times better than a full frame analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.941-947
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• 2018

Station transfers for smart card based railway networks refer to transfer pedestrian movements that occur at the origin and destination nodes rather than at a middle station. To calculate the optimum path for the railway network, a penalty for transfer pedestrian movement must be included in addition to the cost of within-car transit time. However, the existing link label-based path searching method is constructed so that the station transfer penalty between two links is detected. As such, station transfer penalties that appear at the origin and destination stations are not adequately reflected, limiting the effectiveness of the model. A ghost node may be introduced to expand the network, to make up for the station transfer penalty, but has a pitfall in that the link label-based path algorithm will not hold up effectively. This research proposes an optimal path search algorithm to reflect station transfer penalties without resorting to enlargement of the existing network. To achieve this, a method for applying a directline transfer penalty by comparing Ticket Gate ID and the line of the link is proposed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.24-30
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• 2021

In this study, an augmented reality (AR) app that detects the screw-assembly state of a car valve-body and assists the assembly work is developed and the effectiveness of the app is shown through testing. The app creates the contents indicating the screw-assembly position and order, and the screw-assembly state. Then, the contents are registrated onto the valve-body image on a smart-phone screen to be shown to the worker during assembly. To this end, the features are extracted from the 2D image of the valve-body and the location of the valve-body is tracked. By extracting the areas where the screws are to be assembled, and periodically determining the luminance of these areas, it is checked whether the screws are assembled in order at the predetermined position of the valve-body. When an error is detected during assembly, a warning sound is notified to the worker, and the worker can check the assembly state on the smart-phone screen and handle the error, immediately. Study results found that it takes about 65 ms to detect the assembly state of the five screws, and the assembly state is detected without error for 1 hour.