• B. Shirisha

This project introduces an AI-powered crop health monitoring system that leverages computer vision and machine learning to detect diseases at an early stage. With the growing demands in agriculture and the adverse effects of climate change, timely and precise detection of plant health issues has become crucial. Our system analyzes leaf images and environmental parameters to classify crop diseases, assisting farmers in taking timely action. This approach reduces crop loss, promotes sustainable practices, and minimizes chemical pesticide usage. The system achieved promising accuracy in real-world testing, making it suitable for large-scale deployment.

AI in Agriculture, Crop Disease Detection, Machine Learning, Deep Learning, IoT Sensors, Sustainable Farming, Precision Agriculture

"AI-Based Crop Health Monitoring and Disease Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.692-696, May-2025, Available :http://www.jetir.org/papers/JETIRGV06098.pdf

"AI-Based Crop Health Monitoring and Disease Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. pp692-696, May-2025, Available at : http://www.jetir.org/papers/JETIRGV06098.pdf