Earticle

Currently, Korea government is pushing to reduce the energy of various building to meet GHG(Greenhouse Gas) reduction target. There are various methods to save energy in order to fulfill this reduction obligation. One of the ways is detection of spaces using IoT environment sensors to save energy on buildings based on monitoring. Some spaces waste the energy to meet thermal comfort level even when there is no people. In this paper, we show the practical results of our occupancy detection algorithm using IoT environment sensors to find the wasted space on the building.

지능형 시스템은 자료나 정보보다 지식을 주로 이용하는 시스템이다. 따라서 지식표현은 지능형 시스템 구 축에 있어서 중요한 요소이다. 개념그래프는 지식을 효율적으로 표현할 수 있는 그래프 형태의 논리적 지식표현 언 어이다. 하지만 개념그래프를 직접 프로그래밍에 활용하기는 쉽지 않다. 이러한 어려움을 극복하기 위하여 여러 가지 도구들이 개발되었다. 본 논문에서는 개념그래프를 이용한 지능형 시스템 구축에 활용할 수 있는 도구들에는 어떤 것들이 있는지 조사하고 그들의 기능과 특성을 비교 분석한다. 조사결과는 지능형 시스템 구축을 위한 개념그래프 활용에 큰 도움이 될 것이다.

Intelligent systems are systems that mainly use knowledge rather than data or information. Therefore, knowledge representation is an important factor for intelligent system construction. Conceptual graph is a logical knowledge representation language which has graphical form and it can represent knowledge efficiently. It is, however, cumbersome to use conceptual graphs directly for programming. Various tools were developed to overcome this difficulties. In this paper, we survey on functions and characteristics of conceptual graph tools that can be utilized for constructing intelligent systems by using conceptual graphs. The result of this survey will be very helpful to use conceptual graphs for development of intelligent systems.

The e-Government in Korea has made such good results as improvement of official work productivity and citizen service quality. However, e-Government in Korea involves many problems and subjects to must solve, especially, at the side of citizen services. Every public organization as supplier provides each service of themselves to the civilians. Citizens feel inconvenience yet, because they must visit and are supplied various civil services to one public affair from several public institutions. When we consider the paradigm shift of the e-Government service, the status and problems of the e-Government in Korea required more better service model to the citizen. To realize the citizen oriented service, the integration and linkage of the system infrastructure and applications among governmental organizations are required. In this changed situation, when new one/non-stop service model of the digital government is developed and launched, the e-Government can supply better service to the citizens. In this study, the model that we suggest is among the new service models of the e-Government, named the Integrated Civil Service Model. The e-Government involving the Integrated Civil Service Model can make more outcome, such as better civil life convenience, cost-effective results by processing time and cost reduction for public affairs of citizens.

Vehicular ad hoc network (VANETs) has gained wide popularity such that it is necessary to incorporate trust among each node in the network. However, trust management among vehicles is a challenging task as malicious nodes are prone to disturb data transmission among different vehicles. The aim of this work is to establish the truth of consensus, to identify the malicious nodes with no further delay, by considering the decision of each vehicle on finding the trust values. The experimental analysis for the proposed approach done using the NS3 with CAIDA data set, the proposed scheme shows superior results compared to the other existing schemes for the detection rate of malicious nodes. It enhances the attack Detection Rate (DR) as 96.5% for the projected dual weighted trust evaluation technique. But, DR for the triumphing technique firecol is 74.9% and AODV is 60%. Thus, it is experimentally proved that dual weighted trust mechanism has high attack detection rate, comparatively. Also, proposed method outperforms very well with respect to the data transmission parameters like packet delivery ratio, energy Consumption and average latency comparatively over the existing mechanisms.

This paper introduces a portable flexible wrist rehabilitation sensor system designed to support patients with hand function impairments from stroke or injury. The system collects flexible sensor data before and after rehabilitation to train a specialized AI model, utilizing a Long Short-Term Memory (LSTM) network for real-time analysis. This model evaluates wrist rehabilitation performance and degrees of freedom, using embedded sensors to classify and predict hand movements. Additionally, a user-friendly GUI allows patients to monitor their recovery progress. Compared to traditional rigid exoskeletons, this flexible sensor system offers a comfortable, natural hand simulation, reduces costs, and enhances rehabilitation customization and market viability.

본 연구에서는 자율 주행을 위한 지능형 교통 시스템(ITS)을 최적화하는 데 있어 엣지 컴퓨팅의 혁신적인 잠재력 을 연구하였다. 방대한 양의 데이터를 로컬에서 실시간으로 처리하는 엣지 컴퓨팅의 능력은 신속한 의사 결정 및 향상된 안전 조치를 포함하여 자율주행차의 중요한 요구 사항을 해결하는 데 필수 요소이다. 엣지 컴퓨팅과 기존 ITS 인프라의 통합을 탐구하고, 현지화된 데이터 처리가 대기 시간을 크게 줄여 자율주행차의 반응성을 향상시키는 방법을 강조한다. 실시간 교통 관리, 충돌 방지 시스템 및 동적 경로 최적화를 지원하는 강력한 프레임워크를 집합적으로 형성하는 엣지 서버, 센서 및 V2X(Vehicle-to-Everything) 통신 기술의 배포를 검토한다. 또한 본 연구는 보안, 데이터 통합, 시스템 확장성 등 ITS에서 엣지 컴퓨팅을 구현하는 데 있어 가장 중요한 과제를 다루며 잠재적인 솔루션과 향후 연구 방향에 대한 통찰력을 제공한다. 이 논문은 완전 자율 주행이라는 비전을 실현하는 데 있어 엣지 컴퓨팅의 중추적인 역할을 강조 하고, 보다 안전하고 효율적이며 지속 가능한 교통 시스템을 달성하는 데 기여하는 논문이다.

In this scholarly investigation, the focus is placed on the transformative potential of edge computing in enhancing Intelligent Transportation Systems (ITS) for the facilitation of autonomous driving. The intrinsic capability of edge computing to process voluminous datasets locally and in a real-time manner is identified as paramount in meeting the exigent requirements of autonomous vehicles, encompassing expedited decision-making processes and the bolstering of safety protocols. This inquiry delves into the synergy between edge computing and extant ITS infrastructures, elucidating the manner in which localized data processing can substantially diminish latency, thereby augmenting the responsiveness of autonomous vehicles. Further, the study scrutinizes the deployment of edge servers, an array of sensors, and Vehicle-to-Everything (V2X) communication technologies, positing these elements as constituents of a robust framework designed to support instantaneous traffic management, collision avoidance mechanisms, and the dynamic optimization of vehicular routes. Moreover, this research addresses the principal challenges encountered in the incorporation of edge computing within ITS, including issues related to security, the integration of data, and the scalability of systems. It proffers insights into viable solutions and delineates directions for future scholarly inquiry.

V2X 카 융합서비스 환경에서, 인포테인먼트 서비스와 운전자 관리 서비스 가운데 주요 서비스는 드라이 버, 유지보수 관리자, 고객, 익명의 사용자의 중요한 정보를 중심으로 지원되어야 한다. 많은 소프트웨어 어플리케 이션들이 운전 관리 프로그램과 계획의 특정 요구조건을 만족하기 위해 솔루션을 고려해오고 있다. 본 논문에서는 V2X 융합서비스 환경에서 클리닉 환경설정, 클리닉, 클리닉 페이지, 맴버십, 클리닉 요청 처리, 운전자 프로파일 데이터, 클리닉 맴버십 데이터 그리고 클리닉 인증을 포함한 운전자용 차량 진단을 위한 안전한 관리 시스템의 Data flow diagram을 설명하였다. STRIDE 모델 가운데 스푸핑, 탬퍼링, 부인방지, 노출, 서비스 거부, 권한 관리 와 같은, ITS 진단 시스템의 보안 위협 이슈를 중심으로 고찰하였다.

In a V2X convergence service environment, the principal service among infotainment services and driver management services must be supported centering on critical information of the driver, maintenance manager, customer, and anonymous user. Many software applications have considered solutions to be satisfied the specific requirements of driving care programs, and plans. This paper describes data flow diagram of a secure clinic system for driving car diagnosis, which is included in clinic configuration, clinic, clinic page, membership, clinic request processing, driver profile data, clinic membership data, and clinic authentication in the V2X convergence service environment. It is reviewed focusing on security threat issue of ITS diagnostic system such as spoofing, tampering, repudiation, disclosure, denial of service, and privilege out of STRIDE model.

In order to solve the safety hazards caused by the operation failure of elevators, pump rooms, fire control facilities, access control and other equipment and facilities in colleges, this paper uses the Internet of Things technology to realize the ubiquitous access of equipment and facilities in colleges, and collect the operating status data of the equipment and facilities in real time. Establish an equipment and facility operation data center, use big data and deep learning technology to realize online monitoring and real-time early warning of equipment and facilities, and send the monitoring and early warning information to managers and equipment maintenance personnel for processing, and realize the monitoring, early warning, and processing of equipment and facilities Automated process management to build an intelligent monitoring system for college equipment and facilities.

Blockchain technology is a decentralized digital book that discloses transactions to all trading participants, unlike traditional methods of keeping records on a centralized server when trading data, it is a security technology that is virtually impossible to hack because it must forge a block chain at the same time. However, the current block chain technology is a public block chain. Anyone can join a block-chain network, view all the details, and anyone can verify transaction history. On the other hand, a private block chain or a consensus block chain refers to a block chain in which a participant is restricted to participate in building an internal network with a restricted block chain or through a separate authentication method. In the case of the bit coin using the public block chain technique, the mining process is required in the network in order to prevent the Sybil attack (DDoS attack) which takes over the network by the number of nodes. If Blockchain is used in IoT environment, then IoT sensor node is adaptable for Blockchain because of decentralized network. There are many application areas. The disadvantage of mining a few network seizures while granting proof rights to the computing power, but not the number of nodes, is a catastrophic idea, but the cost of network maintenance is very high. However, if the only entity that proves the transaction is a bank, the Sybil attack itself is impossible and the network maintenance cost is zero. Therefore, a consortium Blockchain can solve this public Blockchain, and it will be able to contribute the development of an intelligent IoT and FinTech system technology as well.

본 연구에서는 사물인터넷에 인공지능 기술을 융합하여 사물인 자율주행 자동차와 커넥티드 자동차들이 스스로 정보를 수집하고 분석하여 의사결정을 하도록 돕는 연구이다. 이에 CIoT를 이용한 지능형교통시스템을 연구하여 교통 효율성과 안전성을 향상하고, 교통 상황을 실시간 수집‧분석하며, 차량 흐름을 최적화하여 교통사고 예방과 사용자의 편의성을 증대할 수 있다. 제안한 연구결과를 통하여 교통 체증을 완화하고 탄소 중립과 에너지 효율을 높일 수 있는 친환경 연구이다. 본 연구는 지능형교통시스템(ITS)에 최적화된 인지사물인터넷 연구를 통하 여 도로 안전을 강화하고, 효율성을 높이는데 기여할 수 있으며, 교통 복잡도를 개선하여, 자원을 절약하고 환경 오염을 줄일 수 있는 지속 가능한 도시 모빌리티 지원이 가능하다. 또한, ITS을 적용한 교통 인프라에 최적화된 자율주행 및 커넥티드 차량 맞춤형 교통 시스템 개발에 기여하는 연구이다.

This study aims to enhance the efficiency and safety of transportation by developing an intelligent transportation system (ITS) using the Internet of Things (IoT) and artificial intelligence (AI) technologies. The proposed system will enable self-driving and connected vehicles to autonomously collect and analyze information, make decisions, and optimize traffic flow. This will lead to reduced traffic congestion, improved traffic safety, and enhanced user convenience. Additionally, the system will contribute to achieving carbon neutrality and energy efficiency by reducing fuel consumption and emissions. Key contributions of this research include: Development of an optimized cognitive IoT for ITS to enhance road safety and efficiency. Improvement of traffic complexity, resource conservation, and environmental pollution reduction through sustainable urban mobility support. Development of a customized transportation system for self-driving and connected vehicles optimized for ITS-based traffic infrastructure. The proposed research has the potential to revolutionize transportation by making it safer, more efficient, and more sustainable.

The Common Vulnerability Scoring System (CVSS) is a well-known framework for providing the characteristics of a vulnerability and a numerical score reflecting its severity. Since the existing CVSS has been developed for an information technology (IT) environment, it is not suitable for an intelligent building (IB) environment where OT Operational Technology (OT) and Internet of Things (IoT) are integrated. For example, compared to IT systems that prioritize confidentiality, OT systems prioritize safety and have a very long lifespan. Therefore, if a vulnerable component is exploited in an intelligent building environment, the impact may be different from that in the IT environment. This paper identifies problems that may occur when applying the traditional CVSS to an intelligent building environment. We also propose an effective method to extend the CVSS for an intelligent building environment using threat intelligence and rubric.

In outdoor visible light communication channels and LED road illumination communications for the intelligent transport systems (ITS), inter symbol interference (ISI) due to multipath propagation prevents high data rate transmission. Indoor wireless optical communication systems utilizing white LED lights and on the road illumination have been studying about it. Generally, plural lights are installed in room and considered to the traffic information system using existing LED traffic lights. Therefore, their optical path difference must be considered. In this paper, the influence of an optical path difference has been investigated and two approaches against this problem are introduced. One uses on-off keying, return-to-zero (OOK-RZ) coding and the other uses optical orthogonal frequency division multiplexing(OFDM).

This paper evaluates SnapCheck.io, a smart workflow platform aimed at improving the efficiency of project management in remote work environments. Through the use of AI-driven task scheduling, smart time tracking, and real-time analytics, SnapCheck.io enhances resource utilization and lowers the waiting time for task dependency. A mixed-method study at various organizations showed an improvement in performance by 18%, which was thus corroborated by the increased rate of task completion and quicker workflow execution. The results reveal that the use of intelligent automation in SnapCheck.io not only helps in streamlining the project coordination process but also promotes the ongoing productivity and collaboration of distributed teams.

정부는 4차 산업혁명기의 전개에 따라 초연결화를 바탕으로 초지능화를 확보하여 지능정보사회를 이루고 지능형 정부를 구현하기 위한 다양한 정책을 추진하고 있다. 따라서 국가위기관리도 환경변 화에 대응하고 주요 정보통신기술(ICT)에 의한 지능화가 필요하다. 본 연구의 목적은 지능정보사회 의 전개에 따라 국가위기관리의 지능화를 위한 정책적 방안을 모색하는데 있다. 이를 위해 인공지능 (AI)을 기반으로 하는 국가위기관리의 필요성에 대하여 고찰하고, 주요 국가들의 인공지능(AI) 정책 을 살펴 본 후, 인공지능(AI) 기반의 국가위기관리체계 구축을 위한 방안을 연구하였다. 연구 결과, 위기 유형별 데이터베이스화를 통해 위기관리체제의 정보화가 우선 필요하며, 이러한 정보화를 달 성한 기관 간에 인프라를 구축하고, 구축한 인프라는 동일한 위기관리 플랫폼에서 운용되어야 하며, 이러한 플랫폼의 운용을 위한 전문 인력 양성과 조직 편성이 필요하다는 것을 알 수 있었다.

Within the fourth industrial revolution, the South Korean government has employed various policies to establish an intelligent information society and intelligent government by securing super-intelligence based on hyper-connections. National crisis management needs to respond to environmental changes and become more intelligent using ICTs. The purpose of this study is to explore policy measures for securing intelligence for national crisis management in accordance with the development of an intelligent information society. To this end, we examined the need for AI (Artificial Intelligence)-based national crisis management and developed ways to establish AI-based crisis management system based on the review of AI policies in other major countries. The findings suggest, first setting up the IT-based system of crisis management, building and operating infrastructure among the IT-based agencies within the same platforms, and training professional manpower and restructuring organization for the operation of these platforms.

The condition of the manufacturing process in a factory should be diagnosed and maintained efficiently because any unexpected disorder in the process will be reason to decrease the efficiency of the overall system. However, if an expert experienced in this system leaves, there will be a problem for the efficient process diagnosis and maintenance, because disorder diagnosis within the process is normally dependent on the expert's experience. This paper suggests a process diagnosis using data mining based on the collected data from the coil-spring manufacturing process. The rules are generated for the relations between the attributes of the process and the output class of the product using a decision tree after selecting the effective attributes. Using the generated rules from decision tree, the condition of the current process is diagnosed and the possible maintenance actions are identified to correct any abnormal condition. Then, the appropriate maintenance action is recommended using the decision network.

Recently, the exhibition industry has developed rapidly with the development of information technologies. Most exhibitors in an exhibition plan and deploy many events that may provide advantages to visitors as a method of effective promotion. The growth and propagation of wireless technologies is a powerful marketing tool for exhibitors. However, exhibitors still rely on domain experts who are costly and time consuming because of the manual knowledge input procedure. Moreover, it is prone to biases and errors and not suitable for managing fast-growing and tremendous amounts of data that far exceed a human's ability to comprehend. To overcome these problems, data mining technology may be a great alternative, but it needs to be fit to each exhibition. This study uses data mining technology with the Predictive Model Markup Language (PMML) to suggest a system that supports intelligent services and that improves stakeholder satisfaction. This system provides advantages to the exhibitor, show organizer, and system designer, and is first enhanced by integrating data mining technologies through the knowledge of exhibition experts. Second, using the PMML, the system can automate the process of applying data mining models to solve real-time processing problems in the exhibition environment.