YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation

YOLOv10-Enabled IoT Robot Car for Accurate Disease Detection in Strawberry Cultivation

Blog Article

This study addresses the growing need for effective disease management in strawberry cultivation, a crop vital for global nutrition.We present an innovative approach that combines the YOLOv10 model with a Remote-Controlled Robot Car to revolutionize strawberry disease detection.Our system merges deep learning, IoT, and precision agriculture techniques to enable Apparel real-time monitoring of strawberry fields.This technology-driven solution offers a proactive and data-based method for identifying diseases early.Our findings show the potential of this advanced Playing Cards system to significantly improve agricultural practices and support sustainable food production.

The YOLOv10n model achieved a 96.78% mAP-50 ratio for accurately locating diseased leaves.By integrating IoT capabilities, the system allows for remote control and continuous monitoring, eliminating the need for daily on-site expert inspections.This approach not only enhances disease management efficiency but also has the potential to increase crop yields and reduce pesticide use, contributing to more sustainable farming practices.