---

🌾 G5Farm

🚀 Demo Video:
Watch on YouTube

📊 Presentation (PPT):
View the PPT

This project allows users to manage and analyze agricultural data from their farmland using GIS technology. It provides detailed insights on soil health, land characteristics, crop recommendations, weather forecasts, and AI-based analysis for optimal farming decisions.

Flowchart

🚀 Features

🌍 Farmland Management

• Multiple Farmlands: Users can add multiple farmlands to their dashboard.

• Location Integration: Add farmlands by searching, using the current device location, or pinpointing on the map.

  

  

📊 Dashboard Overview (KisanMitra)

Each farmland dashboard presents key GIS data, including:

• Organic Carbon: Enhances soil structure and fertility.
• Inorganic Carbon: Affects soil pH and indicates degradation.
• Soil Depth: Determines root zone depth for water and nutrient uptake.
• NDVI & FNDVI: Monitor vegetation health and crop growth.
• Soil Texture: Influences water retention and crop suitability.
• Rabi-Kharif-Fallow Patterns: Indicate crop rotation and land usage.
• Land Degradation Factors: Salt-affected soil, water erosion, wind erosion.
• Soil Moisture & Water Logging: Affect irrigation needs and crop yields.
• Vegetation Fraction: Insights into land cover and conservation.
• Forest Cover & Fire Risk: Critical for long-term productivity.

⛅ Weather Forecast

• 7-day forecast for the farmland's location.
• Warnings for anomalies like drought, heavy rain, or fire risks to mitigate threats.

💡 AI Insights

• Current Conditions Analysis: Summarized analysis of soil and land conditions with suggestions for improvement.
• SWOT Board: A strategic analysis for Strengths, Weaknesses, Opportunities, and Threats.
• Crop Recommendations: Suggests crops like soybean and millet based on the land data.
• Yield & Profit Estimations: Provides an estimation of crop yields and profitability based on current data.

🤖 AI-Powered Chatbot

A chatbot is implemented to assist with:

• Querying specific data from the dashboard.

• Explaining GIS terms and soil health indicators.

• Answering questions about crop growth, irrigation, and more.

  

🌱 Soil Type Prediction (CNN)

• Predict the soil type using a Convolutional Neural Network (CNN) model based on input parameters.
• Crop Recommendations: Get recommendations for crops based on predicted soil type.

📸 Crop Disease Diagnosis

• Upload a photo of the crop to identify diseases.

• AI model detects and diagnoses the issue with suggestions for treatment and prevention.

  

🔍 Key Insights Provided

• Soil fertility, water erosion, crop health, and fire risk assessments.
• Crop management recommendations based on land characteristics.
• Soil moisture levels, evapotranspiration, and weather conditions forecasted for irrigation and water conservation strategies.

🔮 Future Enhancements

• Satellite Integration: Adding live satellite data for real-time land monitoring.
• Machine Learning Enhancements: Improving crop disease detection and soil prediction models.
• Mobile App Version: A mobile version for users on the go to enhance accessibility.
• Water Use Efficiency (WUE) Irrigation: Implementing irrigation strategies to optimize water usage based on soil moisture and evapotranspiration data.
• PEST / Disease Surveillance: Integrating real-time monitoring for pests and disease outbreaks, enabling early detection and mitigation.
• Plantation Analysis: Adding tools for plantation performance analysis, focusing on growth patterns and yield.
• Wasteland / Pollution Analysis: Monitoring and analyzing wasteland areas and pollution levels, aiming at land rehabilitation and conservation strategies.
• Yield & Profit Estimation: Enhancing crop yield predictions and profitability analysis using improved AI and machine learning models.

---