Application of Kalman filtering algorithm in greenhouse environment monitoring

The greenhouse environment monitoring requires high accuracy of data, and there are many redundancies and errors in the data collected through the wireless sensor network. In order to improve the accuracy of data, the paper proposes a method which is applying the kalman filtering algorithm to the data fusion and introducing the improved distribution map method to improve kalman filtering algorithm which will ameliorate the measurement precision further, and then, the paper analysed the setting of all parameters of the kalman filter. The simulation results show that the algorithm can effectively avoid the influence of some interference factors, produce the satisfied effect of data fusion, improve the accuracy of the measurement data effectively and provide accurately environmental parameters of greenhouse.