
How AI Can Help Moroccan Farmers Save Water
Demo content — Predictive irrigation turns scarce water into a managed resource rather than a daily guess.

AI-powered agriculture · Morocco
AgriVitro combines IoT sensors, artificial intelligence and precision irrigation so Moroccan farmers grow more while using dramatically less water and energy.
Less water used
Less energy consumed
Higher crop yield
Greenhouse GH-02
Souss-Massa · tomato cycle
Air temperature
24.6 °C
Soil moisture
41 %
Light (PAR)
680 µmol
CO₂
540 ppm
Irrigation plan · next 24 h
AI model schedules watering around forecast heat peaks to cut waste.
The challenge
Drought years, unpredictable heat waves and expensive energy make traditional greenhouse management increasingly difficult. Decisions are still often based on routine and intuition rather than live field data.

The AgriVitro system
Temperature, humidity, soil moisture, light and CO₂ sensors stream greenhouse conditions continuously.
Models learn each greenhouse and crop cycle, then recommend the right action at the right moment.
Water is delivered only where and when the crop needs it, protecting scarce Moroccan water resources.
Ventilation, heating and lighting follow the sun and forecast to keep energy consumption low.
One screen for every greenhouse, with alerts that reach growers on mobile before problems escalate.
Season-over-season analysis turns each harvest into measurable, repeatable agronomic knowledge.
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Less water used
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Less energy consumed
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Higher crop yield
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Greenhouses in field study
Figures observed across AgriVitro deployments and the ongoing 60-greenhouse field study in Fez and Souss-Massa.
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