Agriculture accounts for approximately 70% of global freshwater withdrawals. The crop on the line this season represents months of inputs, labor, and capital. A silo that develops a hot spot can lose a grain lot worth six figures. An irrigation schedule running on last week’s soil readings waters crops that don’t need it and under-waters crops that do.
The industry has been installing sensors for a decade. Soil probes, weather stations, silo temperature cables, moisture meters, GPS-enabled equipment — the data exists. The gap that persists is not data. It is execution.
The operator who checked the dashboard at 9:30 AM missed the optimal irrigation window that closed at 7:00 AM. The grain temperature alert that fired Saturday evening was not acknowledged until Monday. The soil sensor that showed field block 7 hit stress threshold ran for 14 hours unactioned because nobody was watching the screen.
LoRaWAN-based IoT changes the infrastructure economics. VX-Olympus changes what happens to the data.
Why LoRaWAN for Agricultural Applications
Agricultural deployments have constraints that disqualify most connectivity options:
Scale: A medium-sized grain operation covers 5,000–20,000 acres. A single farm may have 50–200 monitoring points distributed across that footprint. Getting data off each point reliably requires a connectivity technology that covers distance.
Power access: Most agricultural sensors are remote from power infrastructure. Battery-powered sensors need to run for years between service — not months. A sensor that needs an annual battery replacement at 150 field locations is a logistics operation, not a monitoring system.
Cost per endpoint: Cellular airtime at $2–$5 per device per month for 150 sensors is $3,600–$9,000 per year, every year, before any value is generated. At 500 sensors across a large multi-property operation, that is $12,000–$30,000 annually.
LoRaWAN addresses all three: a single gateway covers 5–15 kilometers in open agricultural terrain; Class A devices run 3–7 years on battery; per-device connectivity costs nothing after gateway hardware.
IoT SimpleLink manages the LoRaWAN network layer: gateway provisioning, device authentication, ADR optimization, and data forwarding to VX-Olympus. The operator does not manage a network server.
Soil Moisture and Field Condition Monitoring
What Gets Measured
Soil moisture sensors come in two primary types used in commercial agricultural IoT deployments:
- Capacitance sensors — measure the dielectric constant of the surrounding soil, which changes with moisture content. Installed at defined depths (typically 12", 24", and 36" for root zone profiling). Accurate, no moving parts, suitable for long-term installation.
- Tensiometer sensors — measure soil water tension (how hard plant roots have to work to extract water). More sensitive to plant-available water than raw moisture content.
In either case, the sensor transmits readings via LoRaWAN to IoT SimpleLink, which forwards the data to VX-Olympus, where each sensor is mapped to a named field block, depth, and crop type.
From Reading to Irrigation Decision
VX-Olympus rule chains evaluate incoming soil moisture readings against configured thresholds per field block:
- Optimal range: No action. Data logged.
- Below lower threshold (water stress): Irrigation task generated. Depending on integration, this can trigger an automated irrigation controller or generate a dispatch notification to the irrigation team.
- Above upper threshold (saturation): Over-watering alert. Suppress scheduled irrigation for this zone.
The rule chain is context-aware. A threshold breach at 2:00 AM in Zone 4 triggers differently than the same breach at 9:00 AM — the system can factor in time-of-day windows for irrigation scheduling, ensuring the action happens in the optimal early-morning window rather than mid-afternoon.
Multi-Block Farm View
A farm with 40 field blocks, each with 3 soil sensors, has 120 data streams flowing into VX-Olympus. The farm manager’s dashboard shows each block as a color-coded grid cell — green (optimal), amber (approaching threshold), red (threshold breached). They see the farm’s moisture status across all blocks at a glance.
Drill into any block and see the full depth profile: how moisture is distributed across the root zone, historical trend, and the last irrigation event.
Silo and Grain Storage Monitoring
Grain stored in a silo or bin risks quality degradation from two primary threats: moisture infiltration and heat buildup. Both are invisible from the outside. Both compound over time if not caught early.
Temperature Cable Monitoring
Grain temperature cables run vertically through a silo, with sensors at defined intervals (typically every 6–10 feet). Each sensor reads the temperature at that point in the grain mass. Hot spots — caused by microbial activity, insect activity, or moisture pockets — create localized temperature elevations that appear in the profile before they cause visible damage.
IoT SimpleLink connects temperature cable sensors via LoRaWAN interface units that aggregate the cable readings and transmit them to VX-Olympus. Each silo has a digital temperature profile in real time.
Alert thresholds:
- Warm spot detected: Temperature at any cable point exceeds baseline by 5°F or more. Alert to grain manager — investigate and consider aeration.
- Hot spot threshold: Temperature exceeds 90°F (or crop-specific threshold). Immediate alert — aeration required, grain may be at risk.
- Critical threshold: Temperature approaching 120°F. Emergency alert — grain quality at significant risk, immediate intervention required.
Moisture Monitoring
Grain entering storage above the safe moisture content threshold (approximately 14% for corn, 13% for soybeans, 13.5% for wheat) will develop problems in storage. IoT-connected moisture sensors at silo entry points or within the grain mass provide continuous monitoring.
Combined with temperature data, moisture readings provide the complete grain health picture: is this lot at risk, and how urgent is the intervention?
Silo Level Monitoring
Ultrasonic or pressure-based level sensors at the silo crown measure grain fill level in real time. For operations with multiple silos across multiple properties, the aggregate inventory view — how many bushels of which crop in which silo — is an operational and financial management tool, not just an operational one.
Reorder or transfer decisions for grain operations depend on knowing current inventory. Without real-time level monitoring, that requires a manual probe or a site visit.
Irrigation Control Integration
Monitoring without control creates half the value. VX-Olympus connects to irrigation controllers — pivot controllers, drip system controllers, zone valves — via MQTT, Modbus, or dedicated IoT interfaces to close the loop between soil moisture readings and water delivery.
Automated irrigation rules:
- Soil sensor below threshold → evaluate time window → if within allowed window, fire irrigation command → log run start and duration
- Post-run: re-evaluate soil moisture after configured soak interval → if still below threshold, generate manual review task
- Rain sensor detects precipitation → suspend scheduled irrigation for defined period → resume when soil returns to baseline
This is not autonomous irrigation without human oversight. It is condition-triggered execution with human review. The system handles the 80% of routine irrigation decisions automatically. Humans handle the exceptions.
Weather Station Integration
Local weather station data — temperature, humidity, wind speed, rainfall, solar radiation — feeds VX-Olympus alongside soil data for richer irrigation decision logic.
A simple example: a rule chain that evaluates both soil moisture AND forecasted rainfall (via weather station data or API integration) before triggering irrigation. If rain is forecast within 12 hours, suppress the irrigation trigger — the natural precipitation will handle the moisture deficit.
More sophisticated logic accounts for evapotranspiration (ET) calculations using temperature, humidity, and solar radiation to estimate how much water the crop is losing to atmosphere each day, allowing irrigation to replace actual consumption rather than respond to threshold breaches alone.
Network Design for Agricultural LoRaWAN Deployments
Agricultural terrain is typically favorable for LoRaWAN propagation: open, flat, with minimal obstruction. Gateway placement on a grain elevator, a water tower, or any elevated structure provides maximum coverage.
Coverage planning for agricultural operations:
- Open field terrain: 1 gateway covers 10–15 km radius. A 2,000-acre operation (roughly 3 miles across) typically needs 1–2 gateways.
- Rolling terrain with tree lines: Reduced coverage radius. Plan for 3–5 km effective coverage, 3–4 gateways per 2,000 acres.
- Multi-property operations: Each property may need at least 1 gateway, but properties within range of a centrally placed high-elevation gateway can share coverage.
IoT SimpleLink manages all gateways — regardless of how many properties or how many gateways — from a single management interface.
The Outcome
The data was always there. LoRaWAN connectivity makes it economically viable to collect it at scale. VX-Olympus rule chains make it operationally useful.
Talk to our team about a LoRaWAN agriculture deployment scoped to your operation size and crop types.