Abstract

The goal of the MavHome project is to create a home that acts as a rational agent. The agent seeks to maximize inhabitant comfort and minimize operation cost. To achieve these goals, the agent must be able to predict the mobility patterns and device usages of the inhabitants. We introduce the MavHome project and its underlying architecture. The role of prediction algorithms within the architecture is discussed, and three prediction algorithms that are central to home operations are presented. We demonstrate the effectiveness of these algorithms on synthetic and/or actual smart home data.

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