Research on smart agricultural waste discharge supervision and prevention based on big data technology

Abstract

In order to improve the effect of agricultural waste supervision and prevention and control of agricultural environmental pollution, under the concept of smart agriculture and circular economy, this paper builds a smart agricultural waste discharge supervision and prevention system based on big data technology. Moreover, this paper uses mathematical models such as the Environmental Kuznets (EKC) model and the decoupling model to study the overall scale of agricultural waste carbon emissions and its growth trend, and uses the logarithmic average Dixie Index method (LMDI) to construct a decomposition model of carbon emission driving factors to interpret the influence of each driving factor on the scale of overall agricultural waste discharge. In addition, this paper constructs the functional modules of the smart agricultural waste discharge supervision and prevention system according to actual needs, and conducts a test analysis of the system performance. The research results show that the system constructed in this paper has certain practical effects and can lay a foundation for the subsequent sustainable development of agriculture.