Study of intelligent home environment system based on big data and improved k-means algorithm

Abstract

The Embedded operating system based on STC12C5A MCU is designed to facilitate real-time monitoring and control of the home environment, in order to solve some problems such as low acquisition frequency, poor real-time performance, lack of feedback and adaptation. The Kalman filter and improved k-means algorithm are used to analyze the big data which is processed by BP neural network, and then the most comfortable living environment parameters can be obtained. The independent monitoring mechanism and feedback adjustment are designed to achieve efficient collaboration and stable operation of system hardware and software. The test results show that the system has high acquisition accuracy, fast response speed, good reliability performance, as well as good real-time and adaptive capabilities.