Analyze (Smart Decision-Making)
Once the data is collected from sensors, drones, and other sources, it needs to be processed, interpreted, and converted into useful insights for farmers.
🔹 What it Involves
Data Integration & Cleaning
Combine inputs from soil sensors, weather stations, satellite images, and farmer records. Remove noise/errors to ensure accuracy.
Data Processing
Use cloud computing, AI, and machine learning models to process large volumes of farm data. Example: predicting irrigation needs from soil moisture trends.
Pattern Recognition & Prediction
Detect crop stress, pest infestation, disease spread, or yield potential. Forecast rainfall, temperature, and irrigation requirements.
Decision Support Systems (DSS)
Generate actionable recommendations like:
– “Irrigate Field A in 2 hours”
– “Apply 20 kg nitrogen fertilizer to Field B”
– “Spray pesticide in Zone 3 to prevent outbreak.”
🔹 Benefits of Analyzing
- Converts raw sensor data into meaningful insights.
- Helps in precision farming by suggesting where, when, and how much to apply resources.
- Reduces resource wastage (water, fertilizer, pesticides).
- Supports predictive farming → farmers know what will happen before it happens.