Wireless and Optical Sensing for IoT · Study deck

Wi-Fi Channel-State Information for Presence and Motion Sensing

Radio Remi is helping a library keep lights on while people are studying.

Radio Remi is your guide for this deck.

wifi-csi-sensingiot-sensing
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After studying this chapter

Learning objectives

You will be able to:

  • Explain how channel-state information describes amplitude and phase across Wi-Fi subcarriers.
  • Build calibrated window features and evaluate them on held-out synthetic room data.
  • Separate a detection result from evidence about people, rooms, radios, and privacy.
  • Explain: Radio Remi is helping a library keep lights on while people are studying.
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Major section

Start With the Story

Radio Remi is helping a library keep lights on while people are studying.

  • A camera would collect more detail than the team needs.
  • A motion sensor misses someone who sits still.
  • Remi asks whether changes in the room's Wi-Fi path can support a simple occupied or empty decision.
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Major section

Calibrate, window, and describe change

Calibration removes part of the static room and radio offset; it does not remove furniture changes, people outside the target zone, or radio drift.

  • A threshold should include an uncertain band so borderline windows can be reviewed instead of forced into occupied or empty.
  • Window duration controls how quickly the detector responds and how much short-term variation it averages.
  • The calibration record should retain device, channel, placement, room state, and collection time.
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Major section

Read the sensing pipeline

The final card compares held-out predictions with labels and keeps uncertainty visible.

  • The arrows show processing order, not proof that the final output is correct in every setting.
Wi-Fi CSI evidence pipeline from packet measurements through calibrated features to bounded decisions.
Wi-Fi CSI evidence pipeline from packet measurements through calibrated features to bounded decisions.
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Major section

Summary

The useful result is a consented, calibrated decision that can abstain when the room no longer matches its evidence.

  • That record lets a reviewer distinguish a repeatable motion cue from a lucky result or an unreported change in the room.
  • CSI records per-subcarrier channel change, not a direct image of a person.
  • Calibration, windowing, held-out rooms, and abstention keep the claim bounded.
  • A simulated classifier teaches the pipeline but cannot validate an installed Wi-Fi sensing system.
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Deck summary

Key takeaways

Radio Remi is helping a library keep lights on while people are studying.

  • Calibration removes part of the static room and radio offset; it does not remove furniture changes, people outside the target zone, or radio drift.
  • The final card compares held-out predictions with labels and keeps uncertainty visible.
  • The useful result is a consented, calibrated decision that can abstain when the room no longer matches its evidence.
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Retrieval practice

Recall check

Radio Remi says: answer from memory, then check your reasoning.

Q1Why should CSI data be split by room or time before evaluation?

ATo test whether the method survives conditions not copied into training
BTo make every subcarrier have the same phase
CTo remove the need for consent
DTo guarantee that motion caused every channel change
Show answer

Answer: A To test whether the method survives conditions not copied into training.

Q2What is the safest action for a CSI window inside the uncertain threshold band?

AReport no decision and gather more evidence
BAlways label the room occupied
CDiscard the calibration record
DTreat the strongest subcarrier as a person's identity
Show answer

Answer: A Report no decision and gather more evidence.

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Print reference

Answers

Answer key.

  1. A · To test whether the method survives conditions not copied into training.
  2. A · Report no decision and gather more evidence.
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