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linvs

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linvs
·il y a 10 mois·discuss
Awesome job!

A couple questions:

- How was the training/testing data split? Was it split window-wise or participant-wise?

- How does the system perform at elevated heart rates? Seems like it was mostly tested at resting/normal heart rates
linvs
·il y a 10 mois·discuss
As someone that works closely with WiFi data and given their very low error (< 0.5 BMP MAE) I'd love to see them address a few key points:

- Whether train/test splits were participant-wise to avoid data leakage.

- How the system performs at elevated or highly variable heart rates.

- Results from "placebo" or empty-room baselines to rule out false positives, typically done with bags of rice/water (used to simulate mass).
linvs
·il y a 3 ans·discuss
It does but we don't have a battery powered option (yet) so power availability is the bigger issue. Our sensors can only be outlet powered. Each sensor can cover cover roughly 5,000 sq.ft. or about two tennis courts.
linvs
·il y a 3 ans·discuss
Outstanding write-up! We actually built a business based on this technology (occuspace.io) and have had to address almost all the questions that you brought up. To answer some of them here:

Q: How accurate is BLE beacon count, as a proxy for occupancy?

A: It's very highly correlated but different dining locations, classrooms and library floors have very different correlation factors. Consider using other, perhaps more complex features, as well.

Q: How accurate is BLE beacon availability time, as a proxy for dwell time?

A: We don't believe it is very accurate given that BT MAC's randomize every 8-20 mins depending on manufacturer.

Q: Can we improve the accuracy by setting an RSSI minimum, for which devices weaker than it do not count, to ensure only those who are really nearby get counted?

A: That's a great idea. It's worth noting that different types of spaces and depending on where you installed your sensor, will have different threshold levels.