The positional accuracy on the BeSpoon didn’t seem so hot.

For our proposed app, where we are looking for patterns, exact location isn’t so critical as repeat-ability. In other words, even if the data is wrong, if it is wrong the *same way *each time then we might be able to notice patterns.

I need to find some easy, and obvious representation of the accuracy and repeatably. It’s a conundrum because really I want to show the range accuracy between ever pair of points in the apartment. Even if I just constrained it to 10×10 points that still requires (10×10) * (10×10) measurements. And for each pair of points I need to gather a bunch of samples, and calculate the mean and SD so I can get some feel for the measured location, and the spread. <μ, σ>. That’s well beyond my patience

Can I get a feel for the behavior of BeSpoon with just a few samples?

## What I did

I picked a point for an anchor. In the first case I put it atop a picture in my office. Then I went to six different “settling places” and took a sample. I worried that in real life I’d settle in a slightly different way each time, and that could be critical to the measurements. So in fact I did six laps of all of the settling places, sitting down in a slightly different way each time.

- My office chair
- The chair by Brenda’s desk
- The dining table where I stand and stare out the bay window
- My favorite location on the settee
- A spot just by the cupboard in the kitchen
- The hallway lavatory – I actually sat on it each time.

Plotting the results was a real pain, and the diagramming isn’t that great.

### Notation

The yellow triangle marks the location of the anchor.

The crosshatched areas are where I couldn’t get enough signal to range.

The samples sets are represent by a row of red lines, all of which are assumed to cross the invisible line radiating out from the anchor.

In each data set the blue cross represents the actual location where the samples were taken

The red lines represent each of the six samples.

### Conclusion

Not many yet. I need to gather a little more data I think.

- There is a clear tendency to over-estimate when the signal goes through a wall.
- The estimates do tend to cluster within about a 1 meter area

————–**David wrote**

**Mik responds**

## Continued…

**jittered over about 4 feet**. I chose a point that was in range of both anchors and drew donuts to illustrate the limits of the range jitter.

### Revised conclusions

- If we used this kind of data to trilaterate a position then it looks like we could have errors of about +/- 5 feet, and when standing on the cross in the kitchen you would appear to standing about 5 feet away — actually on the kitchen counter.
- But the donut intersection area is actually quite small: about 2 sq ft. The apartment is about 1500 sq ft, so we ought to be able to recognize a few hundred different settling points.
- One anchor covers about 2/3 of the area of the apartment.
- Battery life flagged after a couple of hours.