SmartCropGuard: An IoT-Based Real-Time Paddy Plant Disease Detection System for Precision Agriculture in Cauvery Delta Regions

The rising need for effective crop health monitoring systems higligts the importance of innovation solutions to protect crops and maximize output potential.This paper introduces SmartCropGuard (SCG), a cutting-edge Internet of Things (IoT) based plant disease monitoring system designed specifically for precision farming.Sensor node, which includes temperature, humidity, leaf moisture, and image sensors, is deployed across crop fields to collect real time informaation on environmental conditions and plant health.The proposed SCG consisits of three major functional units, (i)sensor nodes, (ii)a gateway, and (iii)a cloud-based analytics platform.Environmental and plant health data collected by the sensors is transmitted via the gateway to the cloud.The gateway then compiles and sends the data to the cloudbased analytics platform.The data is analyzed using Convolutional Neural Networks (CNNs), which are widely accepted for their ability to automatically extract meaningful features from images, tolerate noise, and achieve high classification accuracy.Predictive models for plant disease detection are developed to ensure timely interventions and reduce manual inspection efforts.SCG facilitates timely interventions by providing real-time, continuous monitoring, which lessens the need for manual inspections and the labor expenditures that go along with them.Furthermore, machine learning improves the accuracy of illness diagnosis and detection, enabling more focused treatments and reducing the need for pesticides.This approach enhances disease management efficiency while promoting sustainable farming practices.By combining sensor-driven data collection, cloud analytics, and intelligent algorithms, SCG offers a scalable and effective solution for real-time crop health monitoring and productivity enhancement.