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Crop health monitoring using YOLO algorithm

 Department: Computer Science  
 By: usericon MIke_Tech_World  

 Project ID: 9713
   Rating:  (5.0) votes: 1
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   Price:₦5000
Abstract
Crop health monitoring is a critical aspect of modern agriculture, ensuring optimal yield and sustainable farming practices. This project leverages the YOLO (You Only Look Once) algorithm, a state-of-the-art deep learning model, for real-time detection and classification of crop diseases. High-resolution images captured by drones and ground-based cameras, along with environmental data from IoT sensors, are used to train and validate the model. The system integrates edge computing to process data locally, enhancing responsiveness and reducing latency. A user-friendly web interface, developed using Flask, allows farmers to upload images, view detection results, and access actionable insights. By combining advanced imaging technologies, IoT, and deep learning, this system aims to provide a comprehensive solution for early disease detection, improving crop management and boosting agricultural productivity....
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