Dr. Shruti Awasthi*
Professor, Department of Life Sciences, School of Sciences, Garden City University, Bangalore, Karnataka; shruti.awasthi@gcu.edu.in; ORCID: 0000-0002-7648-1387
ABSTRACT
The incorporation of Artificial Intelligence (AI) in agriculture is catalyzing a significant transformation toward more efficient, sustainable, and adaptive farming practices. This chapter examines the application of AI across various agricultural domains, including crop monitoring and disease detection through AI-powered sensors, drones, and imaging technologies for early identification of plant stress and disease. It also explores the use of predictive analytics and machine learning models to optimize crop yield forecasting and inform planting decisions. Furthermore, AI-driven systems for soil health analysis and irrigation management are enhancing resource efficiency and promoting sustainable agricultural practices. The deployment of autonomous machinery, such as tractors, harvesters, and drones, is streamlining farm operations, while AI applications in climate modeling are facilitating adaptive strategies for climate-smart agriculture. Additionally, AI-driven decision support systems are fostering data-driven sustainability by reducing waste and minimizing environmental impact. Despite the promising benefits, challenges related to digital infrastructure, data security, and ethical concerns must be addressed to fully realize the potential of AI in agriculture. The chapter concludes with a forward-looking perspective on the role of AI in the future of global food production systems.
Keywords: Smart Crop Monitoring, robotics, Artificial intelligence, Irrigation Management
Citation of this paper: Awasthi, S. (2025). AI IN PRECISION AGRICULTURE & SUSTAINABLE FARMING. VLEARNY Journal of Biological Sciences, 2(1), 4–25. https://doi.org/10.5281/zenodo.19136594
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