Grow Pro: A Smart Assistant for Rice Disease Detection and Decision Support Using Deep Learning

Grow Pro is an innovative agricultural assistant designed to support rice farmers by combining the power of deep learning and IoT in a user-friendly application. Through the use Convolutional Neural Network (CNN), Grow Pro enables farmers to detect common rice illnesses, including brown spot, bacterial leaf blight, andleaf smut, by analyzing leaf images uploaded via a simple interface. This paper presents an overview of recent advances in AI-driven agriculture, highlighting CNNs' effectiveness in real-time disease classification across mobile and IoT platforms, which has been shown to improve detection accuracy and accessibility. Studies emphasize the critical role of CNNs in precision agriculture, especially when integrated with real-time data to support decision-making. Additionally, Grow Pro incorporates location-specific environmental data, enhancing precision agriculture by considering factors variables such soil moisture content, humidity, temperature, and rainfall data. Research has shown that environmental data integration significantly improves disease prediction accuracy and resource efficiency. By combining AI and pooling layer, Grow Pro provides tailored recommendations, optimizing water and fertilizer use for increased productivity and sustainability. Studies also underscore the importance of scalable and cost-effective IoT frameworks to make these solutions accessible to small-scale farmers, minimizing costs and maximizing output. Finally, research on region-specific disease prediction highlights the benefit of local data, allowing Grow Pro to deliver targeted recommendations for disease management based on geographic conditions.