Intelligent Drone Design for Precision Cashew Farming

The integration of unmanned aerial vehicles (UAVs), particularly drones equipped with artificial intelligence, is transforming precision agriculture, significantly impacting economic development within the cashew industry—a critical sector pre-dominantly sustained by small and marginal farmers. This study focuses on the deployment of UAVs outfitted with advanced imaging and edge computing capabilities to enhance early disease detection and precise pesticide application in cashew farming. By employing mobileNetV2 within an end-to-end training architecture, our system classifies anthracnose disease in cashew leaves with a remarkable accuracy of 95%. Simultaneously, it identifies healthy leaves with 99% accuracy, utilizing a dataset prepared for cashew farming and identification of cashew leaf diseases. The application of AI-driven UAV technology not only optimizes pesticide use but also contributes significantly to sustainable farming practices by enabling rapid, accurate responses to disease outbreaks. These capabilities are vital for maintaining crop health and yield, particularly under the constraints of climate variability and limited resources prevalent in developing regions. Our findings underscore the potential of integrating edge computing with UAV technology to revolutionize disease management in agriculture, making a substantial impact on productivity and resource efficiency.