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26h 31m 22s logged

Hi, long time no see.

Over the past few weeks, I have been developing two new approaches for presence detection. The main issue was that the system could not reliably distinguish between an empty room and a room with me standing inside :( .
To solve this, I first developed D5 and then D6. D5 is already available on GitHub. D6 is not available yet because it is still under development and has not been fully validated with real measurements and blind tests.
D5 Presence Detection:
D5 was designed to determine whether a room is empty or occupied. It compares the current CSI measurements with a previously recorded empty-room reference. However, D5 mainly evaluated changes in one direction. In practice, a person’s presence can cause CSI values to either increase or decrease, depending on the receiver and the propagation path. As a result, D5 behaved more like a motion detector and could miss a person who remained still. While it significantly improved presence detection, it was not yet robust enough for reliable real-world use.
D6 – Presence Detection and Position Classification:
D6 builds on D5 by evaluating deviations from the empty-room reference in both directions, making it much more effective at detecting people who remain stationary. Once a person has been detected, D6 attempts to classify their position. Instead of calculating arbitrary coordinates, it identifies one of nine predefined locations (P01–P09) that were previously trained using CSI recordings.
A position is only reported if:

  • the hardware setup is valid and sealed,
  • all receivers provide fresh and valid CSI data,
  • the correct transmitter has been verified,
  • a person has been detected,
  • a valid position index is available, and the classification result is sufficiently confident.

If any of these conditions are not met, D6 deliberately reports no position instead of inventing one.
The software pipeline is largely complete, but the system still needs to be validated using a new sealed setup, fresh training recordings, and independent blind tests before D6 can be released on GitHub.

I also redesigned the UI from the standard RuView interface to a clean white Samaritan-inspired design, based on the AI system from the TV series Person of Interest.

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@Gerafftes

The complete hardware setup, room layout, calibration process, and all technical details are already documented in the GitHub repository.
Since D6 is still under development and has not yet been fully validated, I wanted to keep this update focused on the overall progress.
In the next development log, I’ll take a much deeper look at D6, explain how it works internally, and show the complete validation process with the final hardware setup and real-world test results.