• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1505-1515
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• 2016

The age of autonomous vehicles has come according to development of high performance sensing and artificial intelligence technologies. And importance of the vehicle's surrounding environment sensing and observation is increasing accordingly because of its stability and control efficiency. In this paper we propose an integrated platform for efficient networking, analysis and monitoring of multiple sensing data on the vehicle that are equiped with various automotive sensors such as GPS, weather radar, automotive radar, temperature and humidity sensors. From simulation results, we could see that the proposed platform could perform realtime analysis and monitoring of various sensing data that were observed from the vehicle sensors. And we expect that our system can support drivers or autonomous vehicles to recognize optimally various sudden or danger driving environments on the road.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1674-1688
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• 2019

As environmental pollution and fossil fuel energy problems from fuel vehicle have occurred, the interest of electric vehicle(EV) has increased. EV industry and energy industry have grown dynamically in these days. It is expected that the next generation of primary transportation will be EV, and it is necessary to prepare EV infra and efficient energy management such as EV communication protocol, EV charge station, and smart grid. Those EV and energy industry fields are now on growth. Also, the study and development of them are now in progress. In this paper, distributed charge signal processing software for smart slow and quick EV charge is proposed and designed for dealing with EV charge demand. The software consists of smart slow and quick EV charge schedule engine and EV charge power distribution core. The software is designed to support two charge station types. One is normal EV charge station and the other is bus garage EV charge station. Both two types collect the data from EV charge stations, and then analyze the collected data. The software suggests optimized EV charge schedule and deliveries EV charge power distribution information to power switchboard system, and the designed software is implemented on embedded system. It is expected that the software provides efficient EV charge schedule.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.3
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• pp.9-15
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• 2014

In the ubiquitous computing environment, a ubiquitous vehicle will be a communication node in the vehicular network as well as the means of ground transportation. It will make humans and vehicles seamlessly and remotely connected. Especially, one of the prominent services in the ubiquitous vehicle is the vehicle remote operation. However, mutual-collaboration with the in-vehicle communication network, the vehicle-to-vehicle communication network and the vehicle-to-roadside communication network is required to provide vehicle remote operation services. In this paper, an Internet-based human-vehicle interfaces and a network architecture is presented to provide remote vehicle control and diagnosis services. The performance of the proposed system is evaluated through a design and implementation in terms of the round trip time taken to get a vehicle remote operation service.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.317-324
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• 2016

This paper proposes a message transfer application using smartphone with NFC(Near Field Communication) and GCM(Goolge Cloud Messaging) technology for prevention of personal information leakage. In implementing for the proposed system, we design a NFC-based vehicle status alerts service which make it possible to communicate with smartpone message without phone-number between a car driver and an unspecified person. The application provides message communication mechanism without exposing the real phone number, using the NFC tag written with the driver's smartphone device ID and GCM push messages. Through the evaluation result of the actual implemented application, the proposed system can be efficient technology in protection for leakage of personal information such as personal phone- number in daily life.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.9-14
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• 2018

A road recognition system or Lane departure warning system is an early stage technology that has been commercialized as early as 10 years but can be optional and used as an expensive premium vehicle, with a very small number of users. Since the system installed on a vehicle should not be error prone and operate reliably, the introduction of robust feature extraction and tracking techniques requires the development of algorithms that can provide reliable information. In this paper, we investigate and analyze various real-time road detection algorithms based on color information. Through these analyses, we would like to suggest the algorithms that are actually applicable.

• Journal of Korea Multimedia Society
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• v.22 no.8
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• pp.930-939
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• 2019

High-Level Architecture(HLA)/Run-Time Infrastructure(RTI) are standards for distributed simulation systems and offer a technology to interconnect them and form one single simulation system. In defense domain, M&S is the only way to prove effectiveness of weapon systems except for Live Fire Testing (LFT). This paper focuses on guided missile simulations in weapon systems for engagement analyses and proposes the integrated flying vehicle model that is based on HLA/RTI. There are a lot of missiles in real world; therefore, we should develop each missile models in M&S in order to apply battlefield scenarios. To deal with the difficulties, in this paper, firstly, I classify these missiles into three models: ballastic, cruise, and surface-to-air missile models, and then I design each missile model and integrates them into a single model. This paper also offers a case study with my integrated flying vehicle model. At the conclusion, this paper presents contributions of this paper.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.235-238
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• 2019

In real world object detection is an active research topic for understanding different objects from images. There are different models presented in past and had significant results. In this paper we are presenting vehicle logo detection using previous object detection models such as You only look once (YOLO) and Faster Region-based CNN (F-RCNN). Both the front and rear view of the vehicles were used for training and testing the proposed method. Along with deep learning an image pre-processing algorithm called perspective transformation is proposed for all the test images. Using perspective transformation, the top view images were transformed into front view images. This algorithm has higher detection rate as compared to raw images. Furthermore, YOLO model has better result as compare to F-RCNN model.

• Journal of Multimedia Information System
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• v.7 no.1
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• pp.45-54
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• 2020

This paper presented a brief introduction along with various wireless standards which provide an interactive way of interaction among the vehicles and provides effective communication in VANET. Security issues such as confidentiality, authenticity, integrity, availability and non-repudiation, which aims to secure communication between vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). A detailed discussion and analysis of various possible attacks based on security services are also presented that address security and privacy concern in VANETs. Finally a general analysis of possible challenges is mentioned. This paper can serve as a source and reference in building the new technique for VANETs.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.888-896
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• 2018

In this paper, we report detection and recognition of vehicle logo from images captured from street CCTV. Image data includes both the front and rear view of the vehicles. The proposed method is a two-step process which combines image preprocessing and faster region-based convolutional neural network (R-CNN) for logo recognition. Without preprocessing, faster R-CNN accuracy is high only if the image quality is good. The proposed system is focusing on street CCTV camera where image quality is different from a front facing camera. Using perspective transformation the top view images are transformed into front view images. In this system, the detection and accuracy are much higher as compared to the existing algorithm. As a result of the experiment, on day data the detection and recognition rate is improved by 2% and night data, detection rate improved by 14%.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1166-1174
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• 2017

In general, the detection of the vehicle license plate is a previous step of license plate recognition and has been actively studied for several decades. In this paper, we propose an algorithm to detect a license plate area of a moving vehicle from a video captured by a fixed camera installed on the road using the Convolution Neural Network (CNN) technology. First, license plate images and non-license plate images are applied to a previously learned CNN model (AlexNet) to extract and classify features. Then, after detecting the moving vehicle in the video, CNN detects the license plate area by comparing the features of the license plate region with the features of the license plate area. Experimental result shows relatively good performance in various environments such as incomplete lighting, noise due to rain, and low resolution. In addition, to protect personal information this proposed system can also be used independently to detect the license plate area and hide that area to secure the public's personal information.