Abstract
A smart home can be realized by the provision of services, such as building control, automation and security implemented in accordance with a user’s request. One of the important issues is how to respond quickly and appropriately to a user’s request in a “dynamic environment”. An intelligent agent infers the user’s intention and provides the intact service. This paper proposes a smart home agent system based on a hierarchical hybrid architecture of a user intention model, which models the user intention as a hierarchical structure and implements it in a dynamic environment. The conventional rule-based approach needs to obtain all information before it is executed, which requires a large number of rules and is hardly scalable as the control objects are increasing. On the other hand, the proposed system consists of several modules that construct a hierarchical user intention model. The smart home system needs to take account of the information, such as time, state of device and state of the home, in addition to users’ intention. We evaluate the performance of the proposed system in a dynamic environment and conduct a blind test with seven subjects to measure the satisfaction of service, resulting in the average score of 81.46.
Highlights
The advent of the smart grid, advanced communication infrastructures and energy storage systems is revolutionizing the patterns of electricity usage and energy conservation
Zhou et al presented an overview of the architecture and functional modules of a smart home energy management system that takes account in the autonomous responsive demand and cyber-physical energy systems with renewable and stored energy sources [1]
We propose a smart home agent system with a hierarchical hybrid architecture to work out these problems of rule-based systems
Summary
The advent of the smart grid, advanced communication infrastructures and energy storage systems is revolutionizing the patterns of electricity usage and energy conservation. A large number of rules is required in accordance with all the changeable states of the environment and the user’s intention. We propose a smart home agent system with a hierarchical hybrid architecture to work out these problems of rule-based systems. The response model for private goals is realized to construct the sequence of the immediate goals by considering the hierarchical characteristics of the intention. This modular approach of behavior selection networks makes the system scalable. Experimental results confirm the superior reliability of the proposed system compared to the rule-based system.
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