• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.21-31
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• 2018

In Hyper-Connected Society, IoT-based Lifelog data is used throughout the Internet and is an important component of customized services that reflect user requirements. Also, Users are using social network services to easily express their interests and feelings, and various life log data are being accumulated. In this paper, Intelligent characters using IoT based lifelog data have been developed and qualitative/quantitative data are collected and analyzed in order to systematically grasp emotions of users. For this, qualitative data through the social network service used by the user and quantitative data through the wearable device are collected. The collected data is verified for reliability by comparison with the persona through esnography. In the future, more intelligent characters will be developed to collect more user life log data to ensure data reliability and reduce errors in the analysis process to provide personalized services.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1259-1265
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• 2022

Recently, AI, big data, and IoT technologies are being used in various solutions such as fire detection and gas or dangerous substance detection for safety accident prevention. According to the status of occupational accidents published by the Ministry of Employment and Labor in 2021, the accident rate, the number of injured, and the number of deaths have increased compared to 2020. In this paper, referring to the dataset construction guidelines provided by the National Intelligence Service Agency(NIA), the dataset is directly collected from the field and learned with YOLOv4 to propose a collision risk object detection system through object detection. The accuracy of the dangerous situation rule violation was 88% indoors and 92% outdoors. Through this system, it is thought that it will be possible to analyze safety accidents that occur in industrial sites in advance and use them to intelligent platforms research.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.253-259
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• 2018

The Korea Convergence Society. Recently, as the 4th industrial revolution is rising, there are many changes in various field of industries. Among these industries, autonomous vehicles based on artificial intelligence, big data and internet of things is one of the most promising industry. Autonomous vehicle stray from classical car domain of manufacturers and suppliers, IT/Electronics suppliers and communication companies are widen their business area to autonomous vehicle technology. In this paper, we analysis the state of art of autonomous vehicle technology and development direction of industries/research institute. Finally, we discuss the social/economic effects of autonomous vehicle.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.2
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• pp.82-85
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• 2014

It is helpful to use Intelligent Video Surveillance to replace and supplement the demerit which can possibly occur due to the mistake that can be made by human management. To accomplish this, it is essential that the system should digitalize image information from surveillance camera so that the system, itself, can be able to locate a object and to analyze the pattern of the object. Also, it is imperative that the system should have ability to operate a alarm and a entrance blocking system and to notify a situation to a security manager. Zooming a small object form a screen, however, requires a exact zooming ratio of the object and a shift of centric coordinate. In this paper, It is able to locate and observe closely a object from flexible background, regardless of the distance, by calculating a zooming ratio according to object moment, pan coordinate, and tilt coordinate.

• Journal of Service Research and Studies
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• v.2 no.1
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• pp.61-68
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• 2012

Much technologies building cloud computing environment and supporting sevices on the cloud computing have been developing. Through the environment, accessing new services and sharing knowledge become easy. So far, they have just focused on companies which can support services and people who can use those services. In other words, the environment and models for cloud computing are the most important issue. However, the environment changes rapidly, mobile devices that are connected with each other not only will replace the computing environment based on desktop, but also can create Big data. Therefore, technologies and models are need to follow the trend including mobile based cloud computing environment. In this paper, we explain the cloud computing technologies and trend. Also we address Machine to Machine(M2M) technology and Web of things(WoT) in order to apply those into the cloud computing environment because these two concepts will enhance effectiveness and service reusability in the coming days.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.661-667
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• 2018

Recently, the smart home market is growing due to the development of wireless communication technology and sensor devices, and various devices are being utilized. Such an IoT environment collects various vast amount of device information for intelligent services, receives services based on user information, controls various devices, and provides communication between different types of devices. However, with this growth, various security threats are occurring in the smart home environment. In fact, Proofpoint and HP warned about the cases of damage in a smart home environment and the severity of security vulnerabilities, and cases of infringement in various environments were announced. Therefore, in this paper, we have studied secure mutual authentication method between smart nodes used in smart home to solve security problems that may occur in smart home environment. In the case of the proposed thesis, security evaluations are performed using random numbers and frequently updated session keys and secret keys for well-known vulnerabilities that can occur in IoT environments and sensor devices such as sniffing, spoofing, device mutual authentication, And safety. In addition, it is confirmed that it is superior in security and key management through comparison with existing smart home security protocol.

• Journal of Digital Convergence
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• v.13 no.10
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• pp.343-351
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• 2015

With the diverse services of the current M2M environment being expanded to the organizations, the corporations, and the daily lives, the possibility of the occurrence of the vulnerabilities of the security of the related technologies have become an issue. In order to solve such a problem of the vulnerability of the security, this thesis proposes the technique for applying the cryptography algorithm for the protection of the device key of the M2M environment. The proposed technique was based on the elliptic curve cryptography Through the key exchange and the signature exchange in the beginning, the security session was created. And the white box cipher was applied to the encryption that creates the white box table using the security session key. Application results cipher algorithm, Elliptic Curve Cryptography provides a lightweight mutual authentication, a session key for protecting the communication session and a conventional white-box cipher algorithm and was guaranteed the session key used to encrypt protected in different ways. The proposed protocol has secure advantages against Data modulation and exposure, MITM(Man-in-the-middle attack), Data forgery and Manipulation attack.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.738-747
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• 2021

Today, with the improvement of deep learning technology, computer vision areas such as image classification, object detection, object segmentation, and object tracking have shown remarkable improvements. Various applications such as intelligent surveillance, robots, Internet of Things, and autonomous vehicles in combination with deep learning technology are being applied to actual industries. Accordingly, the requirement of an efficient compression method for video data is necessary for machine consumption as well as for human consumption. In this paper, we propose an object-based compression of thermal infrared images for machine vision. The input image is divided into object and background parts based on the object detection results to achieve efficient image compression and high neural network performance. The separated images are encoded in different compression ratios. The experimental result shows that the proposed method has superior compression efficiency with a maximum BD-rate value of -19.83% to the whole image compression done with VVC.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.93-94
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• 2015

최근 산업 현장에서 재해는 설비의 다양화, 인적 구성의 복잡성, 작업환경의 변화 등으로 다양하게 발생되고 있다. 특히 경제적 자립도가 취약한 중소기업에서는 관리능력이 미흡하여 안전에 대한 조직 및 관리, 교육 등이 큰 문제점으로 대두되고 있다. 우리나라의 안전관리의 현실은 대기업 중심으로 이루어지고 있는 실정이나 재해율은 일본 등 주변국보다 2~4배 높은 수준으로 선진국에 비해 아직도 매우 심각한 문제이다. 한편, 환경과 재난방지, 헬스케어 등과 같은 분야에 널리 활용되고 있는 고도화된 IoT 기술은 최근 빌딩, 도시 관제 시스템뿐만 아니라 산업 현장의 설비와 인력관리 등 IoT 기술의 활용이 활발해지는 추세다. 본 논문에서는 IoT를 활용한 기술 개발을 통해 다양한 분야의 산업현장에 산재하고 있는 각종 위험인자를 포함하여 작업자의 근로 환경 정보를 영상 및 센싱 데이터를 이용하여 인지하고 작업자에게 현장 위해요인을 파악함으로써 합리적인 대책의 마련을 통해 작업자의 안전을 보장하고, 이와 더불어 업무지원 정보를 실시간으로 제공하여 인명피해의 감소, 작업능률과 생산성 향상을 야기할 수 있는 스마트 안전제어 및 원격 업무 지원을 위한 지능형 산업안전 관리 시스템을 개발하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.59-64
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• 2020

In the Paris Climate Agreement, Korea submitted an ambitious goal of reducing the greenhouse gas emission forecast (BAU) by 37% by 2030. And as one of the countermeasures, a smart grid, an intelligent power grid, was presented. In order to apply the smart grid, EMS(Energy Management System) needs to be installed and operated in various fields, and the supply is delayed due to the lack of awareness of users and the limitations of system ROI. Therefore, recently, various data analysis and control technologies have been proposed to increase the efficiency of the installed EMS. In this study, we present a measurement control algorithm that analyzes and predicts big data collected by IoT using a SARIMA model to check and operate energy consumption of public sports facilities.