TRANSFORMING AGRICULTURE WITH AI-POWERED SMART DRONES

This paper introduces an AI-driven smart drone framework for precision agriculture, integrating computer vision, machine learning, and sensor technology to enable real-time crop monitoring and disease detection. By transitioning from manual methods to automated, site-specific interventions for water and chemical application, the system significantly optimizes resource use. Comparative analysis demonstrates that this framework enhances productivity and cost-efficiency while promoting environmental sustainability through reduced wastage. Key Points Technology Integration: Combines UAVs (drones) with computer vision and machine learning for automated field analysis. Precision Management: Enables targeted application of pesticides, fertilizers, and water, reducing chemical usage by an estimated 30–35%. Health Diagnostics: Provides early and accurate identification of crop diseases and nutritional deficiencies compared to traditional visual inspection. Operational Efficiency: Significantly reduces labor dependency and manual error through real-time aerial data processing. Economic & Green Impact: Improves Return on Investment (ROI) over time and fosters sustainable farming by minimizing the environmental footprint of agricultural chemicals.