Research on Intelligent Agriculture Based on Artificial Intelligence and Embedded Perception Algorithms

Abstract

In order to solve the problems of weak collection link, limited data coverage and poor real-time for big data in agriculture, smart agriculture by implementing artificial intelligence and embedded sensing is proposed. The front-end perceptron and wireless gateway were designed. A steady-state data collection system was constructed according to the characteristics of intelligent agricultural information data. Combining various algorithms such as data unification and data recognition, intelligent perception calculation parameters were extracted. The adaptive steady-state sensing model was designed relying on deep learning technology in the field of artificial intelligence. The experimental results show that the RMSE value of the designed system in the study is 0.028, which meets the requirements of intelligent agricultural information data perception accuracy. It is concluded that agricultural big data is a collection of data involved in the process of agricultural production, transportation and marketing, and data collection is the most important part of it.