Algorithm Design Based on Multi-sensor Information Fusion and Greenhouse Internet of Things

Abstract

From the last century, many countries had costed a large amount of energy and material fund to study application of multi-source information fusion technology. At present, whether it is military or civilian, this new technology is widely used, indicating the importance of new technologies. This paper designs and implements a multi-sensor data fusion algorithm combining Kalman filter, Euclidean distance formula and multi-cluster statistical technique. The algorithm can better achieve data fusion and reduce data uncertainty and error caused by various errors such as temperature, humidity and light. We conducted experiments in the cucumber greenhouse in March. The results show that the algorithm is used to process the greenhouse data, which effectively optimizes the decision-making and adjustment basis of the system environmental parameters, which is beneficial to the economic benefits of high greenhouse production.