Artificial intelligence has embarked on significant changes in various fields
and agriculture is one of them. This chapter is focused on the transformative effects of
artificial intelligence (AI) on modern agriculture with an emphasis on how it has
improved sustainability and completely disrupted farming methods. Precision
agriculture is the second name given to modern farming that includes various tools and
technologies to monitor and optimize agricultural production processes. It helps
farmers to maximise crop yields, and environmental impact, and use resources more
efficiently. Soil analysis, crop monitoring, disease and pest detection, and autonomous
machinery are some of the major applications that are covered here. AI-powered
imaging systems are essential for early disease diagnosis and management in crop
management. These technologies enable prompt actions via early detection of disease
or pest infestation indicators. In order to ensure improved crop health and increased
yields, machine learning algorithms examine trends in plant health and suggest suitable
remedies. AI models also help farmers plan more efficiently for storage, marketing, and
distribution by predicting crop yields based on a variety of parameters, including
weather data, soil conditions, and plant health. Also, Artificial Intelligence (AI)
guarantees that crops are transported and sold efficiently, decreasing waste and
increasing farmer profitability by anticipating demand and optimising logistics and
distribution. Supply chain optimisation powered by AI improves agricultural
operations' overall sustainability and efficiency. The chapter explores computer vision,
predictive analytics, and machine learning algorithms, showing how these technologies
support real-time interventions and data-driven decision-making.
Keywords: Crop monitoring, Plant diseases, Predictive analysis, Robotic farming, Sowing seeds, Smart irrigation.
