Industrial-grade control systems adapted for agricultural production. Designed before the first seed goes in the ground.
The same framework that runs billion-dollar factories, scaled for a self-sustaining farm.
Farm-wide planning, financials, and market decisions.
Day-to-day farm management and execution.
Automated decision-making and system monitoring.
Physical sensors and actuators in the field.
Each system designed as a modular unit. Build one, prove it, add the next.
Closed-loop irrigation based on soil moisture, weather forecast, and crop requirements. No water wasted. Every zone independently controlled.
Control logic: IF soil_moisture < setpoint AND rain_forecast < 2mm/24hr AND time_in_window THEN irrigate_zone(n) FOR calculated_duration. Log everything. Trend everything.
Off-grid solar array with battery storage. The farm's nervous system runs on sunlight. Monitor production, consumption, and battery state in real time.
On-site weather station feeding data into every other system. Historical trends build the knowledge base for better decisions each season.
Continuous soil data across zones. pH, moisture, temperature, and eventually nutrient levels. The foundation for precision agriculture.
Well pump control, storage tank levels, filtration system monitoring, and distribution pressure. Water is life — treat the system accordingly.
ISA-101 compliant visualization. Not a pretty dashboard — an effective one. Situational awareness first, aesthetics second. Gray backgrounds, meaningful colors, progressive detail.
Design principle: Follow ISA-101 layering. L1 overview shows whole farm status at a glance. Drill into areas, then units, then diagnostics. Color means something — gray is normal, green is running, red needs action.
How data flows from the soil to the screen.
Sensors and actuators communicate via Modbus RTU/TCP or direct GPIO to local controllers. Simple, proven, cheap. RS-485 runs long distances across the farm without issues.
Edge controllers (Raspberry Pi, ESP32 clusters) publish data via MQTT with Sparkplug B payload format. Birth/death certificates, metric definitions, store-and-forward on disconnect.
All data lands in a time-series database. Grafana or custom dashboards for visualization. REST API for integration. Everything queryable, everything trended.
What gets measured gets managed. Industrial metrics adapted for agriculture.
OEE for farming? Adapted from manufacturing: Availability (growing days vs downtime) x Performance (actual yield vs theoretical max) x Quality (sellable produce vs total harvest). Track it per crop, per zone, per season. Improve relentlessly.
Every alarm is actionable. No nuisance alarms. No alarm floods.
| Priority | Response | Example |
|---|---|---|
| P1 — Emergency | Immediate | Water tank empty, pump cavitation |
| P2 — High | <1 hour | Irrigation zone failure, battery low |
| P3 — Medium | Same day | Soil moisture deviation, sensor drift |
| P4 — Low | Next check | Filter change due, data gap detected |
Target metrics: <6 alarms per hour average. Zero alarm floods. Every alarm documented with consequence and required response. Annual rationalization review.
Affordable, repairable, available in Brazil. No vendor lock-in.
The automation gets designed now. When the land is bought and the first post goes in the ground, the sensor network goes in with it.
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