Jul 29, 2026 · 45 min · 11 segments
Indoor location technology has traditionally been viewed as little more than asset tracking. But what happens when precise location data becomes contextual intelligence? In this episode, Nick Earle…
Samuel van der VeldeGuest
Nick EarleHost
And before we get onto your first use case, which is a great one and a spoiler alert, we're going to be talking about cows.
But back to the point about the dot on the graph is not enough, if you can get more context and more rich information, what does become possible when you get that accuracy down to the, you know, you talked about 10 to 30 centimetres of accuracy.
So if you can do that using whatever technology is the right one, as you say, for the use case, what then becomes possible other than just pure location?
A room might be five meters by five meters, or even an industrial hall might be big, but still the level of detail is so much more bigger.
So with other technologies like wifi, you might simply know that you're on one side of the building, which doesn't really bring a whole lot of value.
Ultra-wideband is, on the other hand, there it's extremely accurate, but that allows you to also do automations.
Because now, because it's very accurate, you can detect if an asset has moved inside a certain area, even maybe inside a bin area where you're putting your material.
We can also better detect movements and that can allow you to see, okay, am I actually using this asset, this material? Imagine it's tools or forklifts.
What we often see is they're just standing still or they're not moving all that much.
And that is something that you can only do if you have that level of accuracy.
If you just know it's somewhere in that corner, then you can also not know if it's moving or not, or how long it's been there, if somebody just picked it up and things like that.
So let's talk about that first case study, because you talked there about assets that move into different parts of, let's say, an indoor building.
And before we get onto your first use case, which is a great one and a spoiler alert, we're going to be talking about cows.
But back to the point about the dot on the graph is not enough, if you can get more context and more rich information, what does become possible when you get that accuracy down to the, you know, you talked about 10 to 30 centimetres of accuracy.
So if you can do that using whatever technology is the right one, as you say, for the use case, what then becomes possible other than just pure location?
A room might be five meters by five meters, or even an industrial hall might be big, but still the level of detail is so much more bigger.
So with other technologies like wifi, you might simply know that you're on one side of the building, which doesn't really bring a whole lot of value.
Ultra-wideband is, on the other hand, there it's extremely accurate, but that allows you to also do automations.
Because now, because it's very accurate, you can detect if an asset has moved inside a certain area, even maybe inside a bin area where you're putting your material.
We can also better detect movements and that can allow you to see, okay, am I actually using this asset, this material? Imagine it's tools or forklifts.
What we often see is they're just standing still or they're not moving all that much.
And that is something that you can only do if you have that level of accuracy.
If you just know it's somewhere in that corner, then you can also not know if it's moving or not, or how long it's been there, if somebody just picked it up and things like that.
So let's talk about that first case study, because you talked there about assets that move into different parts of, let's say, an indoor building.
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