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Smart homes integrated with sensors, actuators, wireless networks and context-aware middleware soon becomes part of our daily life. This paper describes a context-aware middleware providing an automatic home service based on a user's preference inside a smart home. The context-aware middleware includes an appliance controller, a context-aware agent and a scalable browser. The appliance controller takes charge of communication between appliances in the context-aware middleware. The context-aware middleware use OSGi (open service gateway initial) as the framework of the home network. The scalable browser recognizes the properties of all the rendering device, and it figures out their screen size. We use UlML (user interface markup language) as multiple rendering device. The context-aware agent utilizes 6 basic data values for learning and predicting the user's preference for the home appliances: the pulse, the body temperature, the facial expression, the room temperature, the time, and the location. The six data sets construct the context model and are used by the context manager module. The user profile manager maintains the history information for home appliances chosen by the user. The user-pattern learning and predicting module is based on a neural network, which predicts the proper home service for the user. The test results show that the pattern of an individual's preference can be effectively evaluated.