There’s a lot of talk about using soil moisture sensors and other digital tools in the garden. In theory, installing a sensor should make things easier—providing objective data to guide watering and care. But the reality is often more complicated.
Imagine a scenario: one day, a sensor reads 320, bone dry. Two days later, after heavy rain, it reads 315, still dry? Yet, a quick check with your finger finds the soil is actually waterlogged. This illustrates a common issue: sensors can drift over time, subtly and unpredictably.
The Myth of Precision
Digital sensors promise objectivity, numbers instead of guesswork. But most affordable environmental sensors operate in messy, ever-changing conditions. Soil is alive and variable. Minerals build up, water pools unevenly, roots grow around probes. The readings aren’t necessarily wrong, but they can be misleading.
Biology doesn’t care about decimal points. Plants respond to conditions, not numbers. Software abstracts; life reacts. damn, thats a good line
Calibration Is a Negotiation
In principle, sensors can be calibrated: dry the soil, wet the soil, compare readings, and set a range. But even then, you’re calibrating for one type of soil, not all soils. Compost, clay, sand, and organic matter all affect readings differently. Every measurement is context-dependent, and every calibration is temporary.
It raises the question: what should you trust—the sensor or the soil itself?
Trust Boundaries
In software, trust boundaries define where reliable code ends and the unpredictable world begins. The garden is firmly outside that boundary. It doesn’t follow your rules or care about your sampling rate.
A cautious approach might include:
- Not acting on a single data point
- Looking for trends, not spikes
- Checking the actual plant, not just the numbers
- Being wary of sensors that never need recalibration
Sensors, in this context, are like second-hand information: potentially useful, but always needing a reality check.
Organic Systems, Abstract Models
The more you abstract from the soil, the easier it is to mistake precision for truth. Dashboards and charts can look reassuring, but beneath them is a world of muck, roots, and unpredictable processes.
If you never check the soil directly, you risk managing a garden the way a spreadsheet manages a forest.
Final Note
This isn’t to say sensors shouldn’t be used, only that their data should be treated with healthy scepticism. They’re tools, not oracles. In theory, combining digital measurements with hands-on observation offers the best of both worlds.