AI-Driven Solutions for Precision Agriculture in Food Production

Min Dugki, S. Vinoth Kumar, Hoeun Lee, C. S. Madhumathi, Sufyan Yakubu

Abstract


Artificial intelligence (AI) is playing a pivotal role in revolutionizing precision agriculture, enhancing food production through data-driven insights. This paper examines the applications of AI in agriculture, including crop monitoring, soil analysis, and yield prediction. By utilizing machine learning algorithms and sensor data, farmers can make informed decisions that optimize resource use and increase productivity. The paper also discusses challenges in implementing AI technologies and the future prospects for AI-driven precision agriculture in ensuring food security.

Keywords


AI, precision agriculture, food production, machine learning.

References


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Sharma, Abhinav, et al. ‘Machine Learning Applications for Precision Agriculture: A Comprehensive Review’. IEEE Access, vol. 9, IEEE, 2020, pp. 4843–4873.

Fraser, Alistair. ‘Land Grab/Data Grab: Precision Agriculture and Its New Horizons’. The Journal of Peasant Studies, vol. 46, no. 5, Taylor & Francis, 2019, pp. 893–912.

Talaviya, Tanha, et al. ‘Implementation of Artificial Intelligence in Agriculture for Optimisation of Irrigation and Application of Pesticides and Herbicides’. Artificial Intelligence in Agriculture, vol. 4, Elsevier, 2020, pp. 58–73.


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