Data Processing Methods and Algorithms Based on Sensor Fusion

Due to the dynamic variability of environmental parameters, it is difficult to monitor them in real time. In particular, the wind changes its direction very quickly. To solve this problem, a real-time monitoring system based on multi-channel sensors was developed. The measurement time of the sensors used to measure the atmospheric parameters is different, and the measurement period of the sensors used for the system does not end at the same time. In this paper, methods and algorithms are developed for obtaining sensor data for the period after the end of the measurement time, processing the sensor data and synchronizing them to improve accuracy. A real-time monitoring device consisting of sensors measuring 5 atmospheric parameters is developed. A method for synchronizing sensor measurement data is proposed as a data integration method. The proposed method has been evaluated at different stages. After passing experimental tests, it Ismoilov demonstrates a high level of accuracy and reliability.