In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. T

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.

사법인공지능화는 이미 법원의 주요 과제가 되었다. 현재 각 지역의 각급 법원들은 스마트화와 그와 관 련된 시스템 및 플랫폼 구축의 요구에 직면해 있다. 사법정보의 수집과 교환, 심판관리감독보조와 심판 결정 정당성확보 등의 방면에서 이러한 작업 성과는 중요한 효과를 발휘하리라 기대된다. 하지만 사법 인공지능화는 아직 여전히 기술적으로 사법체계에 부작용을 발생시킬 가능성도 존재한다. 사법인공지 능화와 사법정의실현, 그리고 사법개혁목표에는 상호모순점이 존재하고 있고, 사법인공지능화과정은 고급데이터의 부족·알고리즘의 불완전성과 전산하드웨어기술의 한계 등의 문제를 안고 있다. 사법정의 의 관점에서 볼 때, 사법인공지능화의 예상치 못한 결과를 반성해야 하며, 법관의 주체성과 인간이 주 체가 된 최종심판은 계속 유지되어야 할 것이다. 그리고 지속적으로 엄격한 사법적 규율하에서 데이터 베이스와 알고리즘이 개선되어야 하며, 사법본질의 보존을 통해서 인공지능의 사법운용에서 발생할 수 있는 기술적 역효과를 방지해야 할 것이다.

In this paper, And improve the performance of the current bridge inspection systems Intelligent sensor platform of the bridge, Bridges Management and Control, U- disaster warning, Intelligent prevention, etc. The intelligence to maximize the capabilities of the existing bridge inspection systems It proposes an efficient management plan through a ubiquitous sensor network. Since these services are very important to minimize situations where the bridge disaster casualties. Through RFID, RTLS and smartphones, IT technology and sensor fusion, etc. Build bridges to the entire inspection time and unattended automated disaster detection system minimizes the time to invest in bridge inspection and efficiency is to be maximized.

The paper proposes a human-following behavior of mobile robot and an intelligent space (ISpace) is used in order to achieve these goals. An ISpace is a 3-D environment in which many sensors and intelligent devices are distributed. Mobile robots exist in this space as physical agents providing humans with services. A mobile robot is controlled to follow a walking human using distributed intelligent sensors as stably and precisely as possible. The moving objects is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Uncertainties in the position estimation caused by the point-object assumption are compensated using the Kalman filter. To generate the shortest time trajectory to follow the walking human, the linear and angular velocities are estimated and utilized. The computer simulation and experimental results of estimating and following of the walking human with the mobile robot are presented.

The Intelligent Space(ISpace) provides challenging research fields for surveillance, human-computer interfacing, networked camera conferencing, industrial monitoring or service and training applications. ISpace is the space where many intelligent devices, such as computers and sensors, are distributed. According to the cooperation of many intelligent devices, the environment, it is very important that the system knows the location information to offer the useful services. In order to achieve these goals, we present a method for representing, tracking and human following by fusing distributed multiple vision systems in ISpace, with application to pedestrian tracking in a crowd. And the article presents the integration of color distributions into particle filtering. Particle filters provide a robust tracking framework under ambiguity conditions. We propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Comparative results on real video sequences show the advantage of our method for multi-object tracking. Also, the method is applied to the intelligent environment and its performance is verified by the experiments.