Final-Year Research Project
UAV-Based Remote Sensing for Early Crop Disease Detection
An end-to-end autonomous UAV quadcopter integrated with low-cost multi-spectral and RGB camera sensors for automated early-stage paddy leaf disease identification. Utilised custom deep learning classification models and deployed an interactive Flask / REST API web dashboard for agricultural field monitoring. Awarded 1st Runner-Up at the University of Colombo Research Symposium 2024.