Integrated multi-dimensional technology of data sensing method in smart agriculture
Xiaomin Li, Rihong Zhang · 2020
Data sensing is a key step for precision farming and smart agriculture, directly affects the efficiency of the post-processing of data and the information value mining. Therefore, highly efficient agricultural data sensing becomes very important. However, traditional methods usually use one or two techniques to complete data sensing. There are a lot of shortcomings, especially the validity, flexibility, and efficiency of data. In the paper, we firstly discuss the related data sensing technologies from different aspects. Then, according to these technologies, a new agricultural data sensing framework is designed. Moreover, to increase the validity of data a rapid identification of inaccurate agricultural conditions based on machine learning is proposed. Finally, a real platform of data sensing is given by integrated multi-dimensional technology.