Why Durability Over Accuracy
Most sensor guides and community projects focus on accuracy — how close a reading is to a reference instrument at the moment of calibration. WeSense takes a different approach: we prioritise long-term stability and low maintenance over initial accuracy.
This is a deliberate design choice, and it's one that many people will instinctively push back on. This page explains why, with evidence.
The Problem with Accuracy-First
Calibration Degrades
A sensor calibrated to laboratory accuracy today will drift. The question is not if but how fast and how much. For a permanent, unattended sensor network:
- Most people will never recalibrate their sensors
- Any design that requires periodic calibration will fail at scale
- An "accurate" sensor that drifts unchecked gives worse data than a stable sensor that was never calibrated
The Painful Calibration Cycle
Many community sensor projects recommend regular recalibration against reference instruments. In practice:
- Reference instruments are expensive and not widely available
- The process is time-consuming and requires technical knowledge
- Compliance drops rapidly after the first few months
- The network degrades as uncalibrated sensors contribute drifting data
Why Stability Wins
Emergent Accuracy
A network of thousands of slightly imprecise but stable sensors achieves emergent accuracy — the statistical aggregate is more accurate than any individual sensor. This only works when sensors are consistent over time.
Government Stations Provide the Baseline
Government reference-grade monitoring stations (which WeSense also ingests) provide the accuracy baseline. Community sensors provide the density. You don't need every sensor to be reference-grade when you have reference stations for cross-validation.
What We Look for in a Sensor
| Property | Priority | Why |
|---|---|---|
| Long-term stability (low drift) | Critical | Data quality over years, not moments |
| Lifespan | High | Sensors should last 3-5+ years without replacement |
| Maintenance requirements | High | Must be zero or near-zero |
| Power efficiency | Medium | Enables solar/battery deployments |
| Initial accuracy | Lower | Correctable via cross-calibration with reference stations |
| Cost | Medium | Lower cost enables denser networks |