Abstract
In order to solve the insufficiency of the existing smart home energy monitor ing system in autonomous adaptability, a smart home energy monitoring system based on machine learning and embedded technology is proposed. The system uses a gatewa y to collect sensor data, and then uses a cloud computing platform running Hadoop and machine learning algorithms to learn and identify user behaviours to achieve autonom ous decision-making capabilities. Through the analysis of examples, it can be seen that the solution greatly improves the humanization of the smart home system.
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