A Context-Aware Model For Smart Space And Application Research For Smart Factory

Context-aware is the key part of pervasive computing research area, it aims to make computer system sensing the context through sensors and respond to the highly dynamic environment. Users in context aware environment can receive the personized service "anywhere anytime". Smart space is a typical application of pervasive computing and ideal for testing pervasive computing technology. Since smart space is a dynamic, open, intelligent environment, an appropriate context model is required to describe the different entity in smart space environment. The main work of this thesis is to use ontology to build a context-aware model which enable knowledge sharing and knowledge reuse for smart space application such as smart factory. Implicit context in space is inferred and personized service is realized through rule-based context reasoning method.Nowadays most of the existing smart space context models are for specific applications. A common context architecture is missing which is harmful to knowledge sharing and reuse. The majority of the so-called smart devices in market requires for human control and can’t proactively provide personized service for human. From the above issues, this thesis proposes a hierarchical ontology model to decouple the application with context model, realizing the reuse and rapid development of the model. Implicit context information are obtained and personized service is realized by using rule-based reasoning. According to the data characteristic of smart space, a context reasoning method which based on Rete algorithm is proposed to speed up the context reasoning and improve the operating efficiency of the system.This thesis aims to build a common context model for smart space. Knowledge sharing and reuse problem is solved through hierarchical ontology model. Proposed context model is verified by using smart factory as an example. An intelligent fault detection service in smart factory is realized to proactively provide personized service for human. On this basis, Rete algorithm is used to optimize the reasoning process.