Hospitality · Strong theory

TableState — restaurant table lifecycle tracking

Every table tells you its state: seated, eating, lingering, needs bussing.

Strong theory Strong theory live in runtime

The physics is solid; our own validation is scheduled.

Seated diners quietly block a little signal, and eating adds a gentle hand-to-mouth rhythm on top. When people leave, the moved chairs and dishes keep the table's signal fingerprint different from clean-and-empty. So the floor map knows which tables are done but not yet cleared — without a camera or a button.

In the physics: Seated bodies create static attenuation plus characteristic eating micro-Doppler (hand-to-mouth cycles ~0.2-0.5Hz arm motion, cutlery micro-motions); an abandoned but uncleared table shows the residual static multipath change of chairs/objects moved from baseline with no Doppler.
Preparing the recorded fieldLoading real LatentField pipeline output…

This is real pipeline output for Hospitality, replayed. The exact reading depends on your room.

Bring this into the real roomFloor & Bar Pulse3 sensing nodes · ~$130 parts · about 90 min
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How the field becomes an answer

RTI differential imaging for per-table occupancy zones micro-Doppler gesture band (0.1-5Hz) classified into eating vs idle vs vacant compartment Kalman per table to smooth state transitions and emit 'turn the table' events.

How we prove it

OPERAnet activity classes as proxy for seated-activity discrimination; own 6-node ESP32 deployment over 8 tables in a partner restaurant with POS timestamps as ground truth.

Who it is for

Table-turn accelerator: tells the floor manager which tables are done but not bussed — sold on covers-per-night uplift to the restaurant GM.

runtime Runs today in LatentField 2.0 as machine_vibration

Complete first-room estimateFloor & Bar Pulse3 nodes · ~$130 parts · 90 min Request kit, subscribe, or set up →
Compatible DIY hardware options
Operator Single-Venue$280–380

120 min · advanced

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