Solution blueprintAgriculture

Farm digital twin for yield forecasting and irrigation planning

A field-level digital twin built from satellite imagery, weather and soil data that forecasts yield and recommends when and how much to irrigate.

Solution blueprint. This describes how BigAI delivers this type of project, using our products and methods. It is not a specific client engagement.

The challenge

Procurement and input planning depend on yield estimates that arrive late and vary widely. Water is scarce, and irrigation is often scheduled by habit rather than need.

Our approach

  1. Map fields and bring in satellite vegetation indices, weather and soil data.
  2. Calibrate crop-growth and machine-learning yield models on past seasons.
  3. Run what-if scenarios for irrigation and sowing dates.
  4. Deliver forecasts and recommendations through dashboards and the farmer app.

The solution

  • Field-level digital twin
  • Yield forecasts updated through the season
  • Irrigation recommendations

What we measure

  • Forecast error against actual harvest
  • Water used per hectare
  • Lead time of procurement planning

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