• KIPS Transactions on Software and Data Engineering
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• v.10 no.2
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• pp.57-64
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• 2021

This study presents a method for realtime fuel consumption prediction using real data collected from OBDII. With the advent of the era of self-driving cars, electronic control units(ECU) are getting more complex, and various studies are being attempted to extract and analyze more accurate data from vehicles. But since ECU is getting more complex, it is getting harder to get the data from ECU. To solve this problem, the firmware was developed for acquiring accurate vehicle data in this study, which extracted 53,580 actual driving data sets from vehicles from January to February 2019. Using these data, the ensemble stacking technique was used to increase the accuracy of the realtime fuel consumption prediction model. In this study, Ridge, Lasso, XGBoost, and LightGBM were used as base models, and Ridge was used for meta model, and the predicted performance was MAE 0.011, RMSE 0.017.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.132-145
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• 2020

By coming of the 4th industrial revolution era, HD map have became a key infrastructure for determining precise location of autonomous driving in areas of futuristic cars, logistics and robots. Autonomous vehicles have became more dependent on HD map to determine the exact location of objects detected by various sensors such as LiDAR, GNSS, Radar, and stereo cameras as well as self-location decisions. By actualizing autonomous driving and C-ITS technologies, the demand for precise information on HD map have increased. And also the demand for the creation of new information based on the convergence of various changes and real-time information have increased. In this study, domestic and international HD map standards and related environments have analyzed. Based on this, usability has researched which comparison with standard HD map established by various institutions. Additionally, usability of standard HD map have studied for applying actual autonomous vehicles by reworking HD map. By the result of study, standard HD map have well established to use by various institutions. If further research about layer classification and definition by institutions will carried out based on this study, it has expected that and efficient establishment and renewal of HD map will take place.

• Journal of Korea Technology Innovation Society
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• v.21 no.3
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• pp.1155-1178
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• 2018

Future automobiles are evolving into movable living spaces capable of eco-friendly autonomous driving. The role of electrically processing, controlling, and commanding various information in the vehicle is essential. It is expected that the automotive semiconductor will play a key role in the future automobile such as self-driving and eco-friendly automobile. In order to foster the automotive semiconductor industry, it is necessary to grasp technology trends and to acquire technology and quality that reflects the requirements in advance, thereby achieving technological innovation with industrial competitiveness. However, there is a lack of systematic analysis of technology trends to date. In this study, we analyzed the technology trends of automotive semiconductors using patent analysis and topic model, and confirmed technologies such as electric cars, driving assistance, and digital manufacturing. The technology trends showed that element technology and technical characteristics change according to technology convergence, market needs, and government regulations. Through this research, it is expected that it will help to make R&D policy for automotive semiconductor industry and to make decision for industrial technology strategy establishment. In addition, it is expected that it will be used effectively in detail research direction and patent strategy establishment by providing detailed classification of technology and trend analysis result of technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.423-430
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• 2019

The convergence of the automotive industry and the ICT technology can be broadly divided into the commercial service sector and the Cooperative-ITS (C-ITS) service sector. The C-ITS service sector is using V2X communication technology as a field that aims to provide safer transportation, more green and efficient transportation, and more predictable and productive mobility. The recent convergence of self-driving cars and connected cars requires high data rates, low transmission delays, and low transmission error rates. Interest in comparison of performance between WAVE and C-V2X (LTE-V2X, 5G-V2X) has been amplified and application services by communication technology are being studied. In this paper, we design the application performance evaluation method of Hybrid V2X communication system and confirm that the decrease of packet error rate (PER) performance is caused by the increase of communication distance, not the vehicle speed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.19-24
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• 2019

The development of ICT technology has a huge impact on the existing closed CCTV security equipment market. With the importance of video data particularly highlighted in areas such as self-driving cars, unmanned vehicles and smart cities, various technologies using video are emerging. In this paper, we proposed a method to transmit videos and metadata as a part of smart city integration, and to solve the traffic, environment and security problems caused in urban life by utilizing the metadata instead of using CCTV videos for simple recording purposes, and reverse tunneling technique was designed and implemented as a method for accessing CCTV videos for vehicles from remote locations. Integrated management of CCTV videos and metadata for vehicles that have been used only for limited purposes in closed environments will enable efficient operation of integrated centers in real time required by smart cities, such as vehicle status check, road conditions and facility management.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.49-58
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• 2019

In this paper, we propose an edge cloud platform architecture for implementing smart factory. The edge cloud platform is one of edge computing architecture which is mainly focusing on the efficient computing between IoT devices and central cloud. So far, edge computing has put emphasis on reducing latency, bandwidth and computing cost in areas like smart homes and self-driving cars. On the other hand, in this paper, we suggest not only common functional architecture of edge system but also light weight cloud based architecture to apply to the specialized requirements of smart factory. Cloud based edge architecture has many advantages in terms of scalability and reliability of resources and operation of various independent edge functions compare to typical edge system architecture. To make sure the availability of edge cloud platform in smart factory, we also analyze requirements of smart factory edge. We redefine requirements from a 4M1E(man, machine, material, method, element) perspective which are essentially needed to be digitalized and intelligent for physical operation of smart factory. Based on these requirements, we suggest layered(IoT Gateway, Edge Cloud, Central Cloud) application and data architecture. we also propose edge cloud platform architecture using lightweight container virtualization technology. Finally, we validate its implementation effects with case study. we apply proposed edge cloud architecture to the real manufacturing process and compare to existing equipment engineering system. As a result, we prove that the response performance of the proposed approach was improved by 84 to 92% better than existing method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.742-756
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• 2022

A flood of information has occurred with the rise of the internet and digital devices in the fourth industrial revolution era. Every millisecond, massive amounts of structured and unstructured data are generated; smartphones, wearable devices, sensors, and self-driving cars are just a few examples of devices that currently generate massive amounts of data in our daily. Machine learning has been considered an approach to support and recognize patterns in data in many areas to provide a convenient way to other sectors, including the healthcare sector, government sector, banks, military sector, and more. However, the conventional machine learning model requires the data owner to upload their information to train the model in one central location to perform the model training. This classical model has caused data owners to worry about the risks of transferring private information because traditional machine learning is required to push their data to the cloud to process the model training. Furthermore, the training of machine learning and deep learning models requires massive computing resources. Thus, many researchers have jumped to a new model known as "Federated Learning". Federated learning is emerging to train Artificial Intelligence models over distributed clients, and it provides secure privacy information to the data owner. Hence, this paper implements Federated Averaging with a Deep Neural Network to classify the handwriting image and protect the sensitive data. Moreover, we compare the centralized machine learning model with federated averaging. The result shows the centralized machine learning model outperforms federated learning in terms of accuracy, but this classical model produces another risk, like privacy concern, due to the data being stored in the data center. The MNIST dataset was used in this experiment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.77-89
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• 2023

The purpose of this study is to empirically confirm what is an important variable of organizational change by intelligent technology acceptance and whether is a difference in important variables in the organization level of acceptance of intelligent technology. Recently, business models using intelligent technologies such as chat-bots, self-driving cars, credit-prevention fraud, face recognition, and health-care are emerging. External situation factors such as artificial intelligence, big data, COVID-19, and the ESG management are changing the direction of a company's management strategy. This research method established a structural equation model. As a result of the analysis, we found that the leadership, organizational culture, and organizational cooperation variables had a positive effect on human resource development variables. Human resource development found a positive effect on the performance of intelligent technology. In addition, we found the independent variables of leadership, organizational culture, and organizational cooperation had partial mediating effects on the performance of intelligent technology. Each group of levels of intelligent technology found performance differences. The organizational culture variables appeared as important variables in all groups. On the other hand, the leadership variable appeared as an important variable in the middle and lower groups of intelligent technology. The theoretical background of this study is that the business theory was updated through artificial intelligence and intelligent technology theory. As a practical implication, the organization adopting intelligent technology is necessary to prepare a systematic plan for organizational culture change.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.919-928
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• 2023

Deep learning technology is used in various fields such as self-driving cars, image creation, and virtual voice implementation, and deep learning accelerators have been developed for high-speed operation in hardware devices. However, several side channel attacks that recover secret information inside the accelerator using side-channel information generated when the deep learning accelerator operates have been recently researched. In this paper, we implemented a DNN(Deep Neural Network)-based MNIST digit classifier on a microprocessor and attempted a correlation power analysis attack to confirm that the weights of deep learning accelerator could be sufficiently recovered. In addition, to counter these power analysis attacks, we proposed a Node-CUT shuffling method that applies the principle of misalignment at the time of power measurement. It was confirmed through experiments that the proposed countermeasure can effectively defend against side-channel attacks, and that the additional calculation amount is reduced by more than 1/3 compared to using the Fisher-Yates shuffling method.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.124-130
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• 2023

Recently, fan out wafer level packaging, which enables high integration, miniaturization, and low cost, is being rapidly applied in the semiconductor industry. In particular, FOWLP is attracting attention in the mobile and Internet of Things fields, and is recognized as a core technology that will lead to technological advancements such as 5G, self-driving cars, and artificial intelligence in the future. However, as chip density and package size within the package increase, FOWLP warpage is emerging as a major problem. These problems have a direct impact on the reliability and electrical performance of semiconductor products, and in particular, cause defects such as vacuum leakage in the manufacturing process or lack of focus in the photolithography process, so technical demands for solving them are increasing. In this paper, warpage simulation according to the thickness of FOWLP material was performed using finite element analysis. The thickness range was based on the history of similar packages, and as a factor causing warpage, the curing temperature of the materials undergoing the curing process was applied and the difference in deformation due to the difference in thermal expansion coefficient between materials was used. At this time, the stacking order was reflected to reproduce warpage behavior similar to reality. After performing finite element analysis, the influence of each variable on causing warpage was defined, and based on this, it was confirmed that warpage was controlled as intended through design modifications.