• 산업융합연구
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• 제22권7호
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• pp.1-13
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• 2024

전자정부 서비스 중 지능형 CCTV 관제 플랫폼은 인공지능을 활용하여 사람, 자동차 등 주요 객체가 CCTV상에 나타났을 경우, 관제요원에게 표출해 주는 선별 관제 서비스이다. 지능형 CCTV 관제 플랫폼을 운영할 경우 비상 상황 발생 시 신속한 대처가 가능하고 민원 해결 증가로 시민들의 삶의 질 제고가 가능할 것으로 기대를 모으고 있다. 이에 본 연구는 비(非)시장재화인 지능형 CCTV 관제 플랫폼의 편익을 선택실험기법인 조건부가치측정법(CVM)을 적용하여 가구당 평균 지불의사액을 추정하고, 이를 토대로 사회적 편익을 계산하였다. 분석 결과 가구의 평균 지불의사액은 연간 6,908원, 국가 전체의 경제적 편익은 연간 약 1,504억 원으로 추정되었다. 본 연구는 그간 환경·공공재의 적용되던 CVM의 적용 범위를 지능형 전자정부 서비스 분야로 확장한 점에서 학술적 의의가 있다. 나아가, 지능형 CCTV 관제 플랫폼 도입이 활발하게 논의되는 현 상황에서, 이에 대한 편익을 화폐가치로 추정하였다는 점에서 실무적 시사점을 지닌다.

• 한국가정과교육학회지
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• 제29권3호
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• pp.89-104
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• 2017

본 연구는 제4차 산업혁명시대를 맞이하며 소비생활 측면에서 지능정보기술이 가져올 변화와 영향력을 살펴보고, 가정교과의 소비자교육 역할에 대해서 살펴보았다. 본 연구의 목적은 소비생활 측면에서 제4차 산업혁명에 대한 이해를 높여 주체적인 소비자로서 현명하게 미래 소비사회에 대응하기 위한 이론적 기초를 제공하고자 함이다. 먼저 제4차 산업혁명에서의 소비패러다임 변화에 대한 부분에서 생산과 소비는 초연결 플랫폼을 통해 실시간으로 공유되면서 융합되고 있다. 소비의 의미는 정신적 경험과 체험이 중요시 되고 있으며, 소유보다는 사용과 공유가 부각되고 있다. 주요 소비생활의 변화에 있어서는 더욱 편리해지는 스마트한 소비생활이 나타날 것이며, 개인별 수요에 최적화된 개인 맞춤형 소비가 가능해 질 것이다. 또한 지속가능한 환경친화적 소비가 더욱 증가할 것으로 예견되며, 급변하는 소비트렌드의 변화는 소비자중심으로 빠르게 진행될 것이다. 다음으로 제4차 산업혁명에서 예견되는 소비생활에서의 문제점에 대해 살펴보면, 지능정보기술 권력중심으로 인한 불평등적 소비가 나타날 것이며, 개인정보 데이터의 활용 및 관리 문제가 나타날 것이다. 또한 신기술 도입에 대한 윤리적 문제가 대두될 것이며, 궁극적으로 소비의 행복에 대한 문제점이 제기된다. 이러한 새로운 패러다임의 변화에 현명하게 대처하기 위해서 가정교과 소비자 영역에서는 우선적으로 가치 중심교육이 이루어질 필요가 있다. 소비의 윤리적 측면이 고려되어져야 하며, 소비생활에서 신뢰와 상호 협력이 이루어져야 한다. 아울러 창의적 융합이 가능하도록 소비자교육이 진행되어져야 한다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.249-255
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• 2001

Different kinds of information are used when solving tasks that arise in the life cycle of an applied knowledge based system (KBS). Many of these tasks are still under investigation. Their solving methods are often researched independently of each other due to complexity of the tasks. As a result, systems that realize these methods turn out to be incompatible and therefore could not be used together in the lifecycle of a KBS. The following problem arises here: how to support the full life cycle of a KBS. This paper introduces a class of computer knowledge banks that are intended to support the full life cycle of KBSs. Primary tasks that arise in the full life cycle of a KBS are analyzed. The architecture of a knowledge bank of the introduced class is presented, including an Information Content, a Shell of the Information Content and a Software Content. General requirements on these components are formulated on the basis of the analysis. These requirements depend on the current state of understanding in the life cycle of KBSs.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2731-2736
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• 2003

In highly informative, perception-rich environments that we call Omniscient Spaces, robots interact with physical objects which in turn afford robots the information showing how the objects should be manipulated. Object manipulation is commonly believed one of the most basic tasks in robot applications. However, no approaches including visual servoing seem satisfactory in unstructured environments such as our everyday life. Thus, in Omniscient Spaces, the features of the environments embed themselves in every entity, allowing robots to easily identify and manipulate unknown objects. To achieve this end, we propose a new paradigm of the interaction through Radio Frequency Identification (RFID). The aim of this paper is to learn about RFID and investigate how it works in object manipulation. Specifically, as an innovative trial for autonomous, real-time manipulation, a likely mobile robot equipped with an RFID system is developed. Details on the experiments are described together with some preliminary results.

• 제어로봇시스템학회논문지
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• 제13권10호
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• pp.983-989
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• 2007

Most of life thing including human being have tendency of reaction with inherently their own pattern against environmental change caused by such as light, sound, smell etc. Especially, a sense of direction often works as a very important factor in such reaction. Actually, human or animal lift that can react instantly to a stimulus determine their action with a sense of direction to a stimulant. In this paper, we try to propose how to give a sense of direction to a robot using sound being representative stimulant, and tracking sensors being able to detect the direction of such sound source. We also try to propose how to determine the relative directions among devices or robots using the digital compass and the RSSI on wireless network.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.232-235
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• 2003

In this paper, we implemented a FIPA-OS multi-agent framework bundle in OSGi Service Platform. FIPA-OS is an open agent platform for constructing FIPA compliant agent using mandatory components that required by all FIPA-OS agents to execution and optional components that FIPA-OS agent car optionally use. The platform supports communication between multiple agents and communication language which conforms to the FIPA standards. FIPA-OS framework bundle is composed of DE(Directory Facilitator), AMS(Agent Management System), ACC(Agent Communication Channel) and MTS(Message Transport System) bundle. These bundles installed in the OSGi service platform and their life cycle can be managed by the framework.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.652-655
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• 2003

The human being receives a new information from outside and the information shows gradual oblivion with time. But it remains in memory and isn't forgotten for a long time if the information is read several times over. For example, we assume that we memorize a telephone number when we listen and never remind we may forget it soon, but we commit to memory long time by repeating. If the human being received new information with strong stimulus, it could remain in memory without recalling repeatedly. The moments of almost losing one's life in on accident or getting a stroke of luck are rarely forgiven. The human being can keep memory for a long time in spite of the limit of memory for the mechanism mentioned above. In this paper, we will make a model explaining that mechanism using a neural network Adaptive Resonance Theory.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.170-175
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• 1998

Transporting a large table using multiple robotic agents requires at least two group behaviors of homing and herding which are to bo coordinated in a proper sequence. Existing GP methods for multi-agent learning are not practical enough to find an optimal solution in this domain. To evolve this kind of complex cooperative behavior we use a novel method called fitness switching. This method maintains a pool of basis fitness functions each of which corresponds to a primitive group behavior. The basis functions are then progressively combined into more complex fitness functions to co-evolve more complex behavior. The performance of the presented method is compared with that of two conventional methods. Experimental results show that coevolutionary fitness switching provides an effective mechanism for evolving complex emergent behavior which may not be solved by simple genetic programming.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.181-184
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• 1998

CAM-Brain is a model to develop neural networks based in cellular automata by evolution, and finally aims at a model as and artificial brain,. In order to show the feasibility of evolutionary engineering to develop an artificial brain we have attempted to evolve a module of CAM-Brain for the problem to control a mobile robot, In this paper, we present some recent results obtained by analyzing the behaviors of the evolved neural module. Several experiments reveal a couple of problems that should be solved when CAM-Brain evolves to control a mobile robot. so that some modification of the original model is proposed to solve them. The modified CAM-Brain has evolved to behave well in a simulated environment, and a thorough analysis proves the power of evolution.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.308-313
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• 1998

In this paper we will discuss a type of inductive learning called learning from examples, whose task is to induce general description of concepts from specific instances of these concepts. In many real life situations, however, new instances can be added to the set of instances. It is first proposed within the framework of rough set theory, for such cases, an algorithm to find minimal set of rules for decision tables without recalculation for overcall set of instances. The method of learning presented here is base don a rough set concept proposed by Pawlak[2][11]. It is shown an algorithm to find minimal set of rules using reduct change theorems giving criteria for minimum recalculation with an illustrative example. Finally, the proposed learning algorithm is applied to fuzzy system to learn sampled I/O data.