Research On Key Technologies Of Interlligent Interaction Of Internet Of Things Based On Context-Aware

Intelligent Interaction is one of the most important constituent parts of computer science and automatic control. With the advent of the era of Internet of things, the ternary world of the human society, the information space and the physical world will be fully connected and amalgamated. This brings new requirements for the Intelligent Interaction of Internet of things. On one hand, the things of Internet are from different manufacturers, and adopting diverse system platform, it leads to the various structures of the information that acquired from the things, and it is difficult to achieve interaction of them. So a uniform interaction information model of the ternary world of human, computers and things is required to make them capable of recognition and spontaneous interaction with each other. On the other hand, the information exchange and communication of Internet of things are multi-sourced and isomerous, lots of uncertain awareness information appears in the interaction process, and so new method is needed to improve the accuracy of uncertain awareness information. Thirdly, the dynamics of physical world determines the interaction environment is inconstant, and how to adapt to it rapidly, accurately brings a new problem for intelligent interaction.This paper considers the intelligent interaction problem of Internet of things based on context awareness. The current status of the research on intelligent interaction and its existing problem is analyzed, and then a context awareness method to solve the intelligent interaction problem of Internet of things is proposed. The intelligent interaction context description model of Internet of things is constructed. After using the cluster analysis method to discretize the original samples, the attributes of the sample decision table are refined by using rough sets theory to obtain corresponding learning sample sets that cover the original data features with the lowest condition attributes. And then reason out the rules through pattern recognition based on neural networks. According to the rules the interactive contexts are fused to improve the precision of the uncertain sensory information in the process of interaction. Therefore the rule based context is robust to the change of the physical world, and the adaptability of the proposed Intelligent Interaction system of Internet of things is improved.Finally, an intelligent power grid system model is built up with the proposed framework and method. And the context of the interactions is established and made accurate by context fusion. The result shows that the proposed framework and method are effective.