Application of Artificial Intelligence in Agriculture

Abstract

Objective: This study aims to explore the integration of artificial intelligence (AI) technologies in agriculture and its potential to address global food production challenges, improve crop quality and yield, and enhance the efficiency of farming practices.

Method: A review of recent advancements in AI and its implementation in the agricultural sector was conducted. The study examines AI-driven tools, including machine learning, robotics, and computer vision, and their applications in precision agriculture, soil monitoring, crop management, and disease detection.

Results: AI technologies are revolutionizing agriculture by enabling more efficient use of resources and reducing human error. AI-driven sensors and machines have proven effective in predicting weather patterns, monitoring soil and crop health, identifying pests and diseases, and optimizing irrigation and fertilization schedules. AI applications also extend to autonomous machinery, such as drones and robots, which assist in planting, spraying, and harvesting crops with increased accuracy and reduced labor costs.

Conclusions: AI's role in agriculture is transformative, offering innovative solutions to meet the growing global food demand while promoting sustainability and reducing environmental impact. However, challenges such as the need for technological infrastructure, familiarity with AI tools, and security concerns must be addressed for wider adoption in the agricultural industry.