Intelligent machines respond to external environments on the basis of decisions that are made by sensing the changes in the environment and analyzing the obtained information. This study focuses on the construction of a knowledge base which enables decision making with that information. Approximately 70% of all errors that occur in machine tools are caused by thermal error. In order to proactive deal with these errors, a system which measures the temperature of each part and predicts and compensates the displacement of each axis has been developed. The system was built in an open type controller to enable machine tools to measure temperature changes and compensate the displacement. The construction of a machining knowledge base is important for the implementation of intelligent machine tools, and is expected to be applicable to the network based intelligent machine tools which look set to appear sooner or later.

In this study, Levee Visual Inspection and Water Level Detection System was developed to handle visual inspection information on the levee effectively by using mobile/intelligent CCTV system. This system will be used to manage levee reasonably, in order to prevent disaster in the riparian areas preemptively on the base of management task.