A machine learning based website that recommends the best crop to grow, fertilizers to use, and the diseases caught by your crops.
A platform of machine learning based website that recommends the best crop to grow, fertilizers to use, and the diseases caught by your crops.
AI-powered satellite analysis for agriculture using Sentinel-2 data—vegetation indices and farmer insights.
A machine learning-based project aimed at detecting and identifying plant diseases from images of affected plants. Plant Disease Detection Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials
This repository contains code, analysis scripts, and findings from a research project conducted at TUM Precision Agriculture Lab, Duernast.
A wireless soil moisture monitoring system using XBee enables real-time data transmission for precise irrigation. It reduces water waste, avoids over-irrigation, and improves crop health. The low-power, scalable design supports continuous monitoring, aiding smart, efficient agriculture.
Deep Semantic Segmentation model training for row-based crops navigation.
A Python package for digital agriculture in vineyard-related activities
EchoAgri is an advanced agricultural platform designed to harness the power of technology to improve farming practices. This project integrates IoT devices and machine learning algorithms to monitor and manage various agricultural processes, providing farmers with actionable insights.
This repository contains the data used in the manuscript titled "Persistence patterns in sub-field crop water use to guide variable rate management."
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