Abstract: The integration of Artificial Intelligence (AI) in agriculture is revolutionizing farming practices by enhancing productivity, optimizing resources, and enabling precision farming. This project explores the use of AI technologies to improve agricultural processes, focusing on key tools, models, and steps involved. This project includes precision farming, crop health monitoring, yield prediction, market insights. The project utilizes machine learning algorithms such as decision trees, support vector machines (SVM), and deep learning models, data collection. Data inputs include environmental variables, soil conditions, crop health, weather patterns. Through the application of these AI models, the system can predict crop yields, detect diseases, optimize irrigation schedules, and recommend fertilizers and pesticides. The output includes actionable insights for farmers, providing them with precise recommendations to enhance crop management, reduce costs, and increase sustainability. The project demonstrates how AI can drive innovation in agriculture, ultimately improving food security and farming efficiency.
Keywords: Artificial Intelligence (AI), Precision Farming, Crop Health Monitoring, Yield Prediction, Market Insights, Environmental Variables, Soil Conditions, Weather Patterns, Disease Detection, Sustainability, Farming Efficiency.
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DOI:
10.17148/IJARCCE.2025.14349
