Preventing Agricultural Practice of Stubble Burning Through Applications of Artificial Intelligence

Abstract

Stubble burning, a common agricultural practice, is widespread across most of Asia and contributes significantly to severe air pollution. Our analysis aims to inform policy decision-makers about the relevance of artificial intelligence in controlling stubble burning by providing a comprehensive and structured review of the related streams of literature. From our balanced review of the related empirical literature, we infer that AI can help manage the effects of climate change by utilizing limited resources with less human intervention. In this study, Structural Topic Modelling (STM) and Sentiment Analysis tools have been employed to demonstrate how artificial intelligence can help reduce stubble burning and contribute to environmental conservation.