AI in Agriculture: Precision Farming and Crop Monitoring
Keywords:
AI in agriculture, precision farming, crop monitoring, machine learning, computer vision, yield prediction, pest detection, sustainable farming, data analyticsAbstract
Currently the agricultural sector is experiencing a revolutionary change through incorporation of Artificial Intelligence technologies. This paper aims at examining AI in precision farming and crop monitoring and the ways through which it increases agricultural productivity, crop health surveillance and resource utilization. The paper also reviews different artificial intelligence approaches including machine learning, computer vision, and data analytics in use in activities like yield prediction, pest and disease recognition, and assessment of soil health. In addition, the paper looks at some of the advantages and disadvantages of integrating Artificial Intelligence in farming as well as providing examples and success stories across the globe. The present study implies that fur AI has the potential to enhance sustainable agriculture but organizational barriers such as high costs and technical requirements need to be overcome.