Description:

The Precision Farming Analytics Platform is a data-driven web application that helps farmers optimize crop production by providing actionable insights from multiple agricultural data sources.
It leverages IoT sensor data, satellite imagery, soil health metrics, and climate forecasts to deliver field-specific recommendations for irrigation, fertilization, pest control, and harvesting schedules.

This project promotes smart agriculture, reduces waste of resources, and increases crop yield efficiency through advanced analytics and real-time monitoring.

Key Features:

1. Field Data Dashboard – Displays soil moisture, nutrient levels, temperature, and crop growth stages in real time.

2. Satellite & Drone Imagery Analysis – Integrates NDVI (Normalized Difference Vegetation Index) and crop health mapping.

3. Predictive Crop Yield Estimation – Uses historical and real-time data to forecast yield per acre.

4. Irrigation Optimization Tool – Suggests exact water requirements for each field based on soil and weather conditions.

5. Fertilizer & Pesticide Recommendation Engine – Calculates precise amounts to avoid overuse and environmental harm.

6. Pest & Disease Risk Alerts – AI-driven models detect early symptoms from sensor and image data.

7. Weather Impact Analysis – Predicts how upcoming weather conditions will affect crop health and yield.

8. Resource Usage Reports – Tracks water, fertilizer, and pesticide usage for cost and sustainability analysis.

Technology Stack:

• Backend: Node.js / PHP / Java (for API handling, analytics processing, and recommendations)

• Frontend: HTML, CSS, Bootstrap, JavaScript (for interactive visualizations and reports)

• Database: MySQL / PostgreSQL (for storing sensor, weather, and crop data)

• Data Science Layer: Python (Pandas, NumPy, TensorFlow, Scikit-learn for prediction models)

• Visualization: D3.js / Chart.js for graphs, Leaflet.js for geospatial farm maps

• IoT Integration: Arduino / Raspberry Pi with soil and weather sensors

• External APIs:

  • OpenWeather API for weather data

  • Sentinel-2 Satellite API for vegetation analysis

  • FAO & USDA crop datasets

Example Use Case:

• A wheat farmer uses the platform to track real-time soil moisture levels and receives an alert to irrigate only 3 acres instead of the entire field, saving 30% water.

• The system predicts a 15% yield increase based on optimal fertilizer distribution and adjusted irrigation schedules.

• Pest infestation risk alerts allow preventive action, reducing crop loss by 20%.