How Storage Sentry Was Built: A Monitoring Platform Designed for Agriculture From the Ground Up
Most farm monitoring tools are adapted from industrial or commercial applications. Storage Sentry was built differently — because it had to be.
If you have ever tried to find a ready-made sensor monitoring solution for an agricultural operation, you already know the problem. The options tend to fall into two camps: tools that are too simple, measuring a single condition with no ability to integrate with anything else, and tools that are over-engineered, expensive, and built for a factory floor rather than a cold storage facility or grain barn.
Neither works well for a farm. Storage Sentry exists because a working farm put that problem in front of the right person and asked him to solve it.
The Gap in the Market
Schuyler Farms, a multi-site agricultural operation in Norfolk County, Ontario, had been running manual monitoring rounds across their storage facilities. Staff walked the buildings with clipboards, logging temperature, humidity, and air quality readings at each station. The data never made it into a system. The knowledge lived with individuals. When someone was sick or away, the process fell apart.
The farm tested several off-the-shelf solutions. None of them solved the actual problem. Alerts went to everyone on the team regardless of who was responsible for a given area. Data was fragmented. There was no way to assign accountability or give someone the context they needed to act quickly.
What Schuyler Farms needed was a system purpose-built for agricultural operations: multi-condition monitoring across multiple facilities, with alerts routed to the right people, carrying enough information to act without interpretation. That product did not exist. So they asked Adam Wills to build it.
The Build: Starting With the Hardware
Wills had already worked with Schuyler Farms on a weather station network and pest monitoring system. He understood both the technical requirements and the realities of working in agricultural environments, where equipment faces dust, moisture, temperature swings, and physical wear that would sideline hardware built for cleaner settings.
The first challenge was finding sensors that could actually hold up. With hundreds of models on the market at varying price points and reliability levels, Wills tested dozens of options across different applications before selecting the hardware for the initial installation. Durability, waterproofing, data accuracy, and signal consistency were all evaluated in real conditions, not spec sheets.
He installed the sensors incrementally, location by location. This mattered. Rather than deploying everything at once and troubleshooting blind, the incremental approach let him validate each device's data output in context and adjust the configuration before moving to the next area. By the time the platform went live, the hardware had already been stress-tested.
The Build: The Software Layer
With the sensors generating reliable data, Wills built Storage Sentry, a custom web application that analyses incoming readings and distributes alerts based on who needs to act, not who happens to be on a group notification list.
The alerting logic was designed around two distinct categories:
Environmental alerts. Triggered when conditions like temperature or humidity fall outside the defined acceptable range for a given storage area. These give the team advance warning, before product quality is compromised, with clear information about what the issue is and exactly where it is occurring.
Sensor performance alerts. Triggered by low battery, lost signal, or extended inactivity. A monitoring system is only useful if it is actually monitoring. These alerts keep the infrastructure itself accountable.
As the system matured, it expanded to include multi-node sensor units in cooling areas, capturing readings at multiple points within a single space to verify consistent airflow and ambient conditions throughout.
The platform was also built to be managed in-house. Wills trained the Schuyler team on installation, troubleshooting, and adding new sensors, so the system could grow with the operation without requiring outside support for every change.
What Makes It Different
Most monitoring tools are built for a generic use case and adapted, sometimes awkwardly, for agriculture. Storage Sentry was built from the opposite direction: starting with a specific agricultural operation, its specific failure modes, and the specific information its team needed to act effectively.
That starting point produced a few design decisions that distinguish it from off-the-shelf alternatives.
Targeted alerting. Notifications go to the person responsible for a given area, with context. Not to a group inbox. Not to a manager who then has to relay the information. The right person gets the alert, understands what it means, and knows what to do.
Field-tested hardware. The sensors in Storage Sentry were selected through hands-on evaluation in agricultural environments, not chosen from a catalogue. That distinction matters when equipment needs to perform reliably in a cold storage room through a busy harvest season.
Traceability. Historical sensor data gives the team the ability to trace quality issues back to specific times and conditions. If a batch of product shows spoilage, the team can determine whether conditions fell outside acceptable ranges on-site or after it left the facility.
Designed to scale. The platform was built so the farm could add sensors, update locations, and expand coverage independently. It grows with the operation rather than requiring a new implementation project every time something changes.
Where It Goes From Here
Storage Sentry was built to solve one farm's problem. It turned out to be a problem shared across the industry.
Agricultural operations that still rely on manual monitoring face the same compounding risks: knowledge trapped in individuals, no historical data to learn from, and no early warning when conditions drift. The platform built for Schuyler Farms is directly applicable to any operation dealing with those same gaps.