Precision Agriculture for Village-Scale Farming
Built for rural Uganda — offline-first, solar-powered, field-hardened. Industrial-grade IoT, precision sensors, mechanization, and AI designed for the realities of East Africa.
Three-Tier Controller Architecture
Resilient, distributed control from field to cloud
Field Controllers
Solar-powered microcontrollers at each valve point. Operate autonomously with local schedules. Communicate via LoRa radio to zone hubs.
Zone Hubs
Aggregation points with cellular connectivity. Collect sensor data from field controllers, execute zone-level irrigation logic, relay to cloud.
Cloud Platform
Central management dashboard. ET₀ calculations, irrigation scheduling, alerts, reporting. Accessible via web and mobile.
Sensor Platform
Comprehensive environmental monitoring, affordable per farmer
Soil Sensors
Moisture at multiple depths, temperature, EC, pH. Guides irrigation timing and fertilizer application.
Weather Stations
Temperature, humidity, rainfall, wind, solar radiation. Calculates reference evapotranspiration (ET₀).
Plant Health
NDVI camera modules for crop vigor monitoring. Early detection of stress, nutrient deficiency, and disease.
Water Quality
pH, turbidity, dissolved oxygen monitoring at intake points. Ensures safe irrigation water for crops.
Mechanization-as-a-Service
Shared machinery for village-scale efficiency
Walking Tractor Fleet
VDM's communal land blocks enable mechanization that fragmented smallholder farms can't support. Walking tractors with interchangeable implements — ploughs, planters, harvesters — are shared across the village scheme, reducing labor costs and land preparation time from weeks to days.
MOI Strategy
- Maintenance schedules tracked via IoT telemetry
- Village-based operators trained and certified
- Spare parts inventory at zone hub level
- Usage-based billing — pay per hectare, not per machine
Smart Irrigation Scheduling
Science-based water management
ET₀-Based Scheduling
We calculate reference evapotranspiration (ET₀) using the Penman-Monteith equation from on-site weather data. Combined with crop coefficients (Kc) and soil moisture readings, the system determines exactly when and how much to irrigate.
Results
- 30–40% water savings vs. fixed-schedule irrigation
- Reduced pumping energy costs
- Optimal crop stress management
- Automated night-time irrigation for efficiency
AI & Data Products
Machine learning applied to real agricultural challenges
Pest & Disease Detection
Phone-based image recognition identifies crop diseases and pest damage. Recommendations pushed to farmers via SMS and app.
Yield Prediction
Combine satellite imagery, sensor data, and historical yields to forecast harvest volumes 4–6 weeks ahead.
Market Advisory
Real-time crop prices, optimal selling windows, and buyer matching. Connects farmers to the best available markets.
Open for Collaboration
We believe in open standards and collaborative development. If you're a research institution, technology company, or developer interested in agricultural IoT for rural Africa — let's talk.
Get in Touch