• Nabhan Abdul Qadir
• Muhammed Rhasil
• Athmi Shetty
• Sanjana V
• Nagaraja Hebbar N

This work introduces an AI-powered system for real-time crop disease detection and precision pesticide spraying. Leveraging deep learning models (CNN) and computer vision, the system accurately identifies diseases from leaf images captured by onboard cameras. The robotic platform then performs targeted pesticide application using a smart spraying mechanism, optimizing chemical usage and minimizing environmental impact. This work supports sustainable agriculture by integrating AI, robotics, and precision farming techniques to enhance crop productivity while minimizing expenses and environmental impact.

Deep learning, multi-class classification, CNN, smart agriculture.

"AI-BASED PLANT DISEASE DETECTION AND PESTICIDE SPRAYING SYSTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.849-854, July-2025, Available :http://www.jetir.org/papers/JETIRGX06161.pdf

"AI-BASED PLANT DISEASE DETECTION AND PESTICIDE SPRAYING SYSTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp849-854, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06161.pdf