The Application of Data-Level Fusion Algorithm Based on Adaptive-Weighted and Support Degree in Intelligent Household Greenhouse

摘要

The paper first details the general structure and functions realization of intelligent home greenhouse control system. In order to make the data obtained from the intelligent home greenhouse system in this paper more accurate, the paper mainly explores how to accurately perceive the environment. Aiming at the error of same type sensors' data in household greenhouse environment, data-level fusion is used to reduce the error and obtain more accurate value of same type sensors' data. In order to improve the precision and reliability of data-level fusion, a weighting-coefficient construction method based on support degree and adaptive-weighted is proposed, which not only ensures the reliability of data fusion but also makes the fusion result more stable. The accuracy of data fusion directly determines the precision and quality of greenhouse intelligent control. The experimental results show that the fusion result adopting the proposed method of this paper is superior to the result of traditional average-estimation fusion and data fusion based on support degree.