An Integrated Web Based IoT and Generative AI Platform for RealTime Plant Disease and Pest Management in Smart Agriculture

Abstract

Plant diseases and pest infestations remain major challenges in modern agriculture, often leading to reduced crop productivity and excessive pesticide use. Although artificial intelligence (AI) and the Internet of Things (IoT) have been widely adopted in smart farming, many existing systems provide only disease detection and lack integrated support for real-time monitoring and farm management. This study developed a web-based platform that combines IoT, Edge AI, and Generative Artificial Intelligence (Generative AI) to enable real-time detection and management of plant diseases and pests. Environmental data collected from IoT sensors were integrated with images captured by IP cameras, while synthetic images generated using Generative AI were incorporated to improve dataset diversity and model performance. The platform was developed following a research and development approach and evaluated through laboratory testing and field implementation. The proposed AI model achieved an accuracy of 96.8%, while field experiments demonstrated a 41.5% reduction in pesticide use and an 18.2% increase in crop yield. The integrated platform also provided real-time notifications, historical data management, and automated decision support for farmers. These findings demonstrate that the proposed platform offers an effective and scalable solution for smart agriculture by improving disease detection, supporting sustainable farm management, and reducing reliance on chemical pesticides.