AgroNet 🌱🚀

AgroNet is a web application created by our team for the hackathon NASA Space Apps Challenge Athens. The project focuses on providing farmers in Evoia, Greece with vital information about the risk level of green bollworm infestations in their cotton fields.

By leveraging satellite data and local sensor inputs, AgroNet helps farmers make informed decisions on when to check their fields and optimize pesticide use, reducing the environmental impact while protecting crops from pests.

🚜 Project Overview

Cotton farmers need to monitor the presence of green bollworms in their fields regularly. While pesticides can be used to manage these pests, excessive use can harm the plants and ecosystem. Farmers must balance between early detection and limited pesticide application.

AgroNet addresses this challenge by creating a bollworm danger level indicator based on:

By using machine learning, AgroNet can dynamically adjust the weights of these factors (temperature, flora, sensor data) based on real-world field data.

Farmers can also contribute by pressing a Worm Alert Button, which will increase the danger level in their area, refining the indicator for nearby farms.

🌟 Features

🛠️ Future Improvements

📷 Screenshots

Screenshot NDVI

NDVI Data Visualization - Green areas represent high vegetation density. The marked squares display areas with temperature that benefits bollworm population increase.

Screenshot Web

Web Interface - Real-time bollworm danger level indicator and user alerts.