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With the rapid development of the Internet of Things technology, more and more applications are brought to people's lives. Therefore, wireless sensor network nodes are deployed indoors, real-time collection of indoor environmental data, and corresponding fusion and processing of the data to analyze the dynamic changes of the indoor environment, and can predict and analyze the environmental conditions in each time period. The results are fed back to the user in real time, reminding the current indoor environmental issues to be studied. First, collect indoor temperature, humidity, PM2.5 and VOCs, utilize ZigBee wireless communication technology as the communication basis of the sensor network. At the same time, each sensor is used to obtain physical data of the indoor environment in real time. For effective monitoring and evaluation, the data is analyzed through experiments and the root mean square error RMSE is finally fitted in the multiple linear regression algorithm to be 0.0495, which can predict the changes of various indoor factors.