If you’ve ever built a dashboard, you know the feeling: the seductive clarity of green bars, time series graphs, and neat little boxes telling you what’s happening—right now, in real time.
It’s clean. It’s structured. It feels like control.
So of course, at some point, I started thinking about building a dashboard for the garden. A way to track temperature swings, soil moisture, rainfall, UV exposure. Maybe even humidity at root level, if I got ambitious.
Not because I need it. But because I wanted to see it. I wanted a map of what the system was doing, a visual language for something that’s mostly silent. Something to confirm that my intuition hadn’t gone dull.
But here’s the thing: a dashboard doesn’t just show you what’s happening. It changes how you see it. It filters. It abstracts. It decides what matters.
And once you start relying on a dashboard, you don’t just risk seeing less, you risk believing too much.
What a Garden Dashboard Might Track
Let’s start with the obvious:
- Soil moisture (shallow + deep)
- Ambient temperature
- Rainfall totals
- Sunlight exposure over time
- pH levels
- Air humidity
- Time since last manual watering or compost turning
All of these can be measured. Most of them can be logged and visualised with off-the-shelf components: an ESP32, a few sensors, a local MQTT broker, a Grafana instance on the home server.
From a design perspective, it’s doable. From a systems perspective, it’s beautiful.
But from a philosophical one? It raises a different question entirely:
Do you want to know everything—or just enough to act?
The Danger of Knowing Too Much
The first lie a dashboard tells is that it’s complete.
It’s not. It’s a snapshot, sliced, compressed, and modelled. It shows you what’s wired, not what’s alive. It will tell you the soil is moist, but not whether the plants are thriving. It will tell you how much light hit a sensor, not how much of that light was useful.
That’s not a flaw. It’s the nature of abstraction. But forget that, and you’ll start trusting the readout over your own eyes.
And if the system lies, if a sensor drifts, or a graph flatlines, or the server goes down in the middle of a heatwave, you won’t see the garden. You’ll see the ghost of it on your screen.
That’s the second lie: that the system’s still real just because the dashboard is running.
Why Build One Anyway?
So why do it?
Because data can teach. Because trends matter. Because noticing that rainfall is down 30% this month should change how you water. Because being able to zoom out and spot seasonal patterns might help you plan better next year.
Because it feels good to understand the machine you’re living inside, even if it’s made of roots and not code.
But a dashboard isn’t a replacement for the garden. It’s a tool for seeing what you’re missing, so long as you remember that it, too, is missing things.
The key is to let the data inform, not dictate. To treat the dashboard like a first opinion, not a final diagnosis.
Keep the Loop Open
A good dashboard encourages feedback. Not just from sensors, but from you. It shows data, but also lets you add data back. Notes. Exceptions. Observations.
If you’re building a garden dashboard in theory or in practice, include space for:
- Manual notes on plant health
- Unexpected events (a hard frost, a late pest wave)
- Interventions made (amending the soil, pruning, repotting)
- Your own uncertainty
Because the loop isn’t closed until it includes the human. You. The one who notices the scent of decay before a sensor reads a spike in ammonia. The one who hears the dry crack of soil before the moisture value starts to drop.
No dashboard can replace that.
But the right one might remind you to keep listening.
Build It—But Keep Watching
I still think about building that dashboard. And maybe someday, I will. Not because I think it’ll save the garden, but because I want to understand it better.
But here’s my theory:
Build your dashboards. Log what you can. Automate with care. But never stop walking the perimeter.
Because when the system fails, and it will eventually, it won’t be the graph that saves you. It’ll be the moment you noticed the leaves were wrong. The moment you felt the air change. The moment you trusted the system just enough, but not more than the earth beneath your feet.
Part of my Garden Data & Automation series.