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For the problems of complex internal space structure of traditional buildings, high wiring cost and low data acquisition accuracy, LoRa wireless communication technology is used to build a sensor network, which is mainly used to monitor the changes of indoor temperature parameters; for the phenomenon of small fluctuations in the traditional Kalman data fusion results, the isolated forest algorithm is introduced, and the indoor temperature data fusion algorithm based on the improved Kalman filter algorithm is proposed The error range of the improved Kalman data fusion algorithm is controlled between -0.12 and 0.1 with perturbed samples and -0.03 to 0.14 with distorted data, which are much smaller than the traditional Kalman data fusion algorithm and the mean The results of experimental simulation show that the improved algorithm improves the robustness and accuracy of indoor temperature data acquisition.