Analysis of the Critical Role of a Smart Agricultural Internet of Things System in Industrial Benefit Evaluation

Abstract

Agriculture is transforming from traditional agriculture to smart agriculture. To realize the intelligent, precise, and scientific management of agricultural production, it is necessary to conduct real-time, accurate, and effective monitoring of various agricultural production elements. Therefore, the agricultural internet of things monitoring system has important research and application value. In the intelligent irrigation decision-making subsystem, first, the authors use the HHT data processing method to process the real data samples of the area (EEMD decomposition) and then apply the machine learning method to establish the economic benefit evaluation model. This article examines multiple models, including artificial neural networks, support vector regression models, and multiple linear regression models.