An Activity Recognition-Assistance Algorithm Based on Hybrid Semantic Model in Smart Home

Wireless smart home system is to facilitate people's lives and it trends to adopt a more intelligent way to provide services. It is beneficial to design an intelligent smart home (SH) to precisely recognize users' behaviors and automatically responsd with the corresponding activities to satisfy users' actual demands. However, activity models in the existing approaches are usually constructed separately through statistic probability. These models cannot recognize the user's dynamical intentions accurately. To address the problem, we propose a new SH architecture with smart device enabled sensor networks and develop the prototype system. Moreover, we propose the hybrid semantic model based on the statistic probability model and the semantic association model, and an assistance algorithm is presented. In our prototype system, the smart devices are described by semantic models. When the user needs assistance, smart gateway can provide appropriate services according to the inference results of the algorithm. The algorithm has been implemented and the results show that the accuracy of the algorithm based on the hybrid model is higher than the statistic probability model.