Maintenance and Telepresence System

We will develop automated intelligent software for the identification task in the CDC on-board CVN-77. This intelligent identification software module (IISM) will perform as well as or better than human watch standers. We will knowledge engineer currentCDC identification experts, since it is not anticipated that identification will occur much differently than in current carriers. Based on that elicited knowledge, we will design the CDC Knowledge Representation and Execution System (CKRES). This will beused to develop the IISM in three versions. The IISM will be interfaced to the Advanced Battle Station (ABS) and other systems for demonstration of capabilities and testing. The IISM will be thoroughly validated, verified, and tested in a wide range ofsituations.To develop IISM, we will first develop CKRES which facilitates the development of any automated watchstation software module. AI and Expert System technology offer the capability of capturing human decision processes. By developing a general schema forcapturing the knowledge required for each TFCC/CDC position, the development of these TFCC/CDC automation software modules is greatly facilitated. What is needed is an integrated approach using a broad range of technologies. We will use several AItechniques such as task transition diagrams, knowledge-based representations (rules, objects), model-based reasoning, case-based reasoning, intelligent entities, tactical diagrams, constraint-satisfaction, and fuzzy logic.