This project is centered on the detection of diverse diseases affecting paddy crops, as well as signaling nutrient deficiencies in the plant. Through multimodalities (image and sound), the system is able to capture and identify various classes of paddy diseases (e.g., Bacterial Leaf Blight, Brown Spot, Leaf Smut, and Bacterial Panicle Blight), paddy pests (e.g., Rice Gall Midge, Rice Leaf Caterpillar, Rice Leaf Roller, Rice Leaf Hopper, Rice Shell Pest, and Rice Water Weevil), as well as through the sounds of pests (e.g., Cicadas, Mice, Frogs, Birds, and Snakes). Additionally, the project leverages IoT technology to incorporate sound detection of pests, providing real-time information through a mobile application synchronized with the IoT’s GPS.

RiceRescue has the potential to significantly transform paddy cultivation by enabling early, precise, and accessible monitoring of crop health and pest threats. By combining AI-driven multimodal detection (image and sound) with IoT integration, the system empowers farmers with real-time, location-based insights that reduce crop losses, improve yields, and minimize dependency on manual inspections or chemical overuse. This innovation directly contributes to food security and sustainability, ensuring healthier crops, more efficient use of resources, and reduced environmental impact