A context-awareness for mechanical maintenance

Ongoing development of information technology provides a fundamental environment of maintaining vast manual information in digital form. Demand of digital information increases because of easy handling and presentation of documents on various structure manner. As a result, technical documents like mechanical device maintenance manuals have numerous advantages to move from page version into electronic edition. However, it is still difficult for context-aware systems to provide information relevant to specific context because the information scatters in multiple parts of the document. The object detection techniques of context-aware systems could not recognize all objects completely. In this paper, we propose a context-aware system which can recommends relevant information through analyzing context delivered by a vedio device located in workplace around. To compare the current context with documents, three metrics are used for computing similarities between contextual information and keywords extracted from documents. For our experiments, we preprocessed hundreads of TASKs in the aircraft's maintenance manual and made several cases for context. Our experiments showed that our proposing system could provide information related with context.