Due to the uncertainty and inconsistency of measurement data from multiple sensors in the same space, a multi-sensor data fusion algorithm is used to fuse the measurement data of multiple nodes. We propose a multi-Bayesian estimation method for fusing multi-sensor data, and combine Bayesian estimation with ARIMA model to predict the ambient temperature of bamboo and wood building materials. It can utilize the redundancy of data to reduce this uncertainty and improve the reliability of subsequent predictions. © 2023 ACM.