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Revolutionizing Agriculture: AI-Powered Crop Yield Forecasting and Precision Farming for Optimal Harvests.

EasyChair Preprint no. 11942

12 pagesDate: February 4, 2024


In recent years, the agricultural landscape has undergone a transformative shift with the integration of artificial intelligence (AI) technologies. This paper explores the revolutionary impact of AI in agriculture, specifically focusing on its application in crop yield prediction and precision farming practices. By harnessing advanced machine learning algorithms, AI offers unprecedented capabilities to analyze vast datasets, enabling farmers to make data-driven decisions for optimized crop production. This study delves into the key methodologies, challenges, and promising outcomes associated with AI-powered agriculture, shedding light on its potential to reshape the future of food production. The paper concludes by outlining recommendations for policymakers, emphasizing international collaboration, and underscoring the need for ethical frameworks to guide the equitable and sustainable integration of AI in agriculture. Ultimately, AI offers immense potential to revolutionize agriculture, ensuring food security, environmental sustainability, and efficient resource management for a burgeoning global population.

Keyphrases: Agricultural Transformation, AI in Agriculture, Crop yield prediction, data-driven decision making, machine learning, Precision Farming

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {William Jack and Solman Bagh},
  title = {Revolutionizing Agriculture: AI-Powered Crop Yield Forecasting and Precision Farming for Optimal Harvests.},
  howpublished = {EasyChair Preprint no. 11942},

  year = {EasyChair, 2024}}
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