Precision Agriculture Platform for Large-Scale Farming
A large-scale farm operator was over-irrigating by 35% and under-fertilising in variable soil zones, reducing yields and increasing costs.
Team
6 IoT engineers + 2 ML specialists
Timeline
18 weeks end-to-end
Client
Large-Scale Farm Operator (12,000 hectares)
Outcomes Delivered
28%
Water Usage Reduction
19%
Crop Yield Increase
$890K
Annual Input Cost Savings
How we delivered it
Deployed a network of 800 soil moisture, temperature, and nutrient sensors across 12,000 hectares with solar-powered LoRaWAN connectivity.
Integrated weekly drone multispectral imagery to generate NDVI vegetation health maps at 5cm resolution.
Trained a crop stress prediction model combining sensor data, satellite imagery, and weather forecasts to generate field-level intervention recommendations.
Built a variable-rate application map generator that exports prescription files directly to precision irrigation and fertiliser spreader equipment.
Developed a farm manager mobile app (Flutter) with daily field alerts, weather integration, and season-to-date input cost tracking.
What we built
Deployed a precision agriculture platform combining drone imagery, soil sensors, and ML crop models to generate variable-rate application maps.
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