A new behavior-assisted semantic recognition method for smart home

摘要

In the recent Smart Home (SH) research work, intelligent service recommendation technique based on behavior recognition, it has been extensively preferred by researchers. However, most current research uses the Semantic recognition to construct the user's basic behavior model. This method is usually restricted by environmental factors, the way these models are built makes it impossible for them to dynamically match the services that might be provided in the user environment. To solve this problem, this paper proposes a Semantic behavior assistance (Semantic behavior assistance, SBA). By joining the semantic model on the intelligent gateway, building an SA model, in this way, a logical Internet networks for smart home is established. At the same time, a behavior assistant method based on SBA model is proposed, among them, the user environment-related entities, sensors, devices, and user-related knowledge models exist in the logical interconnection network of the SH system through the semantic model. In this paper, the data simulation experiment is carried out on the method. The experimental results show that the SBA model is better than the knowledge-based pre-defined model.