摘要
Wireless smart home system is to facilitate people's lives and it trend to adopt a more intelligent way to provide services. It is very desirable in the recent SH market for the system to recognize users' behaviors and automatically response the corresponding activities to satisfy users' actual demands. However, activity models in the existing approaches are usually defined separately through knowledge-driven methods. These approaches cause that the activity models can't be matched with the services dynamically. To address the problem, we develop the semantic association model and a novel approach of activity recognition and guidance is presented. In our approach, the smart devices and users' requirements are described by semantic models. When the requirements are detected and understood, smart gateway can provide appropriate services, achieving activity assistance. The semantic association model allows all related elements in smart home connect with each other logically. The approach has been implemented and the results show that the success rate of the approach based on semantic association model is higher than 33% at average as compared to the approach based on predefined models. The proposed approach can effectively help people who are in trouble with learning or remembering in the common life.
Wireless smart home system is to facilitate people's lives and it trend to adopt a more intelligent way to provide services. It is very desirable in the recent SH market for the system to recognize users' behaviors and automatically response the corresponding activities to satisfy users' actual demands. However, activity models in the existing approaches are usually defined separately through knowledge-driven methods. These approaches cause that the activity models can't be matched with the services dynamically. To address the problem, we develop the semantic association model and a novel approach of activity recognition and guidance is presented. In our approach, the smart devices and users' requirements are described by semantic models. When the requirements are detected and understood, smart gateway can provide appropriate services, achieving activity assistance. The semantic association model allows all related elements in smart home connect with each other logically. The approach has been implemented and the results show that the success rate of the approach based on semantic association model is higher than 33% at average as compared to the approach based on predefined models. The proposed approach can effectively help people who are in trouble with learning or remembering in the common life.
基金
supported by Electric energy data mining and intelligent analysis technology research and application projects of Shenzhen Power Supply Bureau, Ltd
