Background
A family-owned grain operation in central Kansas manages 14 storage bins across two sites, with a combined storage capacity of approximately 850,000 bushels. The operation grows and stores corn, soybeans, and wheat — a typical diversified Kansas grain operation that markets grain through local elevators and direct commercial buyer contracts.
Storage quality is a direct input to price. Corn that grades No. 1 commands a premium over corn that grades No. 3 due to temperature damage, mycotoxin contamination, or moisture-related quality degradation. For an operation storing at this scale, the quality difference between a clean bin and a hot-spotted bin can be measured in tens of thousands of dollars per affected bin.
The operation had temperature cables installed in all 14 bins as standard equipment. Manual reading was done by the farm manager or one of the operation’s two full-time employees — walking each bin, reading the cable display at each bin’s control panel, recording the high/low/average on a paper log, and making a judgment on whether aeration was needed.
This worked most of the time. The weekly check cadence was adequate when storage conditions were stable. It failed when problems developed between checks.
The Challenge
In the storage season preceding the IoT deployment, the operation experienced one quality loss event that drove the investment decision:
Corn was harvested at 14.2% moisture — slightly above the recommended 14% maximum for long-term storage, but within a range the operation had stored successfully before. The corn went into Bin 11 with aeration running for the first 2 weeks to bring the moisture down.
At the weekly check 3 weeks into storage, the farm manager found a hot spot in the upper-center section of Bin 11 at 15°F above the rest of the grain mass. Aeration ran continuously for 72 hours. The temperature normalized, but sample testing indicated mycotoxin levels that downgraded the bin’s corn to a lower price grade.
The farm manager’s analysis afterward: if the hot spot had been caught at Day 4 rather than Day 21, the intensive aeration response would have prevented the mycotoxin development. The condition was likely developing for 10–14 days before the weekly check caught it.
The estimated quality loss from the Bin 11 event: approximately $42,000 in price difference between No. 1 and the downgraded grade, across the roughly 60,000 bushels in the bin.
The Solution
Network Design
The operation’s two sites are located 4 miles apart. A coverage analysis identified that a single LoRaWAN gateway mounted on the main site’s grain elevator — which at 80 feet elevation provides line-of-sight to both sites — covered all 14 bin locations with RSSI above -110 dBm.
One LoRaWAN gateway was installed on the elevator, provisioned through IoT SimpleLink. Total network infrastructure cost: under $400.
Sensor Deployment
Existing temperature cable installations provided the sensor hardware at no additional cost. The upgrade was in the data transmission layer:
IoT-connected temperature cable interface units were installed at each bin. Each unit:
- Connected to the bin’s existing temperature cable
- Read all cable sensor positions at 15-minute intervals
- Transmitted the full temperature profile via LoRaWAN to IoT SimpleLink
- Powered from the bin’s existing 120V electrical service
For the two bins without AC power at the cable control panel, battery-powered interface units were specified — capable of operating for 18+ months between battery changes on the 15-minute reporting cycle.
Additionally, headspace humidity sensors were added to 6 bins identified as historically higher-risk (the bins where the moisture-management challenge was most common based on the farm manager’s experience).
Deployment time: 2 days for all 14 bins.
VX-Olympus Configuration
VX-Olympus was configured with alert rules specific to each grain type in each bin:
Corn (6 bins):
- Watch: Any sensor position more than 8°F above average for that bin
- Warning: Any sensor more than 15°F above average, or absolute reading above 85°F
- Critical: Any sensor above 95°F
Soybeans (4 bins):
- Watch: Any sensor more than 6°F above average (soybeans are more temperature-sensitive)
- Warning: Any sensor more than 12°F above average, or absolute above 80°F
- Critical: Any sensor above 90°F
Wheat (3 bins) and empty/transitional (1 bin):
- Standard profiles matching commodity storage guidelines
Alert routing: Warning and critical alerts go to the farm manager’s cell phone via SMS and to a farm email account. Critical alerts have a 15-minute re-send if not acknowledged.
The aeration systems at each bin were not directly integrated in the initial deployment — the farm manager opted to keep manual control of aeration decisions while using the monitoring as the trigger signal.
The Results
Storage Season Performance
During the first full storage season post-deployment (covering the subsequent corn and soybean harvest):
7 watch alerts (8°F+ deviation): All investigated. 4 were associated with natural temperature stratification during early storage — the top of the bin warmer than the lower portions as grain settled. These normalized over 2–3 weeks without intervention. 3 developed further and triggered warning alerts.
3 warning alerts (15°F+ deviation):
Alert 1 (Corn, Bin 4): Warning fired at 4 days into storage for newly harvested corn. Investigation showed a localized hot spot in the southeast quadrant at mid-depth. Cause: a pocket of higher-moisture corn blended with dryer corn but not fully mixed. Intensive aeration for 36 hours resolved it. Sample testing showed normal quality. No downgrade.
Alert 2 (Soybeans, Bin 9): Warning fired at Day 12. Temperature elevation in the upper-center section. Farm manager diagnosed early insect activity from a visual bin inspection. Treatment and aeration resolved it within 5 days. Sample testing normal.
Alert 3 (Corn, Bin 7): Warning fired at Day 18. Investigation showed moisture migration from lower grain to upper section (the temperature differential driving moisture upward). Extended aeration normalized the condition without quality impact.
0 critical alerts.
Hot Spot Detection Timing
The farm manager tracked the estimated time of anomaly development (based on the VX-Olympus temperature history before the alert fired) against when the alert fired:
- Alert 1 (Bin 4): Anomaly developing approximately 4 hours before alert fired at the 15°F threshold
- Alert 2 (Bin 9): Anomaly developing approximately 18 hours before alert fired (slower development)
- Alert 3 (Bin 7): Anomaly developing approximately 11 hours before alert fired
Without continuous monitoring, all three would have been discovered at the next weekly check — between 4 and 7 days after the anomaly began.
Bin 11 Comparison
For perspective on the value of early detection: the Bin 11 event from the prior season was estimated to have developed for 10–14 days before discovery. The avoided loss from any one of the three warning events this season — if they had been caught at the same development stage as Bin 11 — would have ranged from minor quality impact to potential significant downgrade.
The farm manager estimated that “catching Alert 1 at 4 hours instead of potentially 7 days is worth more than the entire system cost.”
Grain Manager’s Operational Change
The farm manager’s daily routine changed in one specific way: a 2-minute morning review of the VX-Olympus bin dashboard. The color-coded bin grid confirmed all bins were green, or surfaced any amber indicators for that morning’s investigation.
Previously, the bin check was a physical process — walking each bin, reading the display, recording the number. For a 14-bin operation across two sites, this took 45–60 minutes on the weekly check day.
With continuous monitoring, physical bin checks became condition-driven rather than calendar-driven: walk to a bin when the system indicates something worth looking at, not because the calendar says to check this week.
Conclusion
The IoT SimpleLink-connected grain storage monitoring deployment at this Kansas operation addressed a specific operational need: collapsing the detection gap between when a quality problem begins developing and when the farm operator knows about it.
The prior year’s Bin 11 event — $42,000 in quality loss from an anomaly that ran 10–14 days before detection — was the reference case. The deployment cost was recovered within the first storage season based on the three events that were caught at the warning stage.
For grain operations storing at commercial scale, the financial case for continuous monitoring is directly calculable: what is one significant quality loss event worth, and how many seasons does a monitoring system need to prevent before it pays for itself?
In this case, the answer was one event, in one season.
Talk to our team about a grain storage monitoring deployment for your operation.