Automated Crop Health Monitoring and Drone-Based Image Processing for Crop Disease Detection in Smart Farming Using IoT

Abstract

The innovative approach to automated CHM and disease detection in smart farming through the integration of drone-based image processing and IoT technologies. Combining information from IoT sensors and drone images can be complex, making it difficult to analyze CH effectively. To Create a comprehensive system that combines IoT sensors and drone imagery to facilitate real-time monitoring of CH, enabling early detection of diseases. Implement advanced image processing algorithms to accurately analyze drone-captured images and identify ESOCDs, improving detection rates. Efficient Particle Filter Multi-Target (EPFMT) Technique facilitates real-time crop disease detection, multi-target tracking, data fusion, and resource optimization. It includes noise reduction, to eliminate artifacts and improve the clarity of the images. PLSR- SEDA, PLSR in smart farming by effectively modelling the relationship between spectral data from drone imagery and various CH indicators, enabling precise disease identification and management. SEDA is used in boundaries of plant structures and potential disease symptoms in aerial imagery, facilitating precise analysis of CH and identification of affected areas. Spanning Tree Optimization (STO) is used to enhance the efficiency of data transmission, minimize energy consumption, and ensure reliable communication among IoT devices, facilitating timely detection and management of crop diseases in smart farming.  The result shows that the frog eye leaf spot follows closely with an impressive accuracy of 92%, demonstrating strong detection capabilities, while bacterial leaf spot has a slightly lower accuracy at 90%, implemented using Python software. The future scope of automated CHM using drone-based image processing and IoT includes integrating ML for enhanced disease prediction, expanding sensor technologies for comprehensive soil and environmental analysis, and user-friendly platforms for planters to heighten reserve management and increase productivity while promoting sustainable agricultural practices.