feat: RTL_433 protocol database integration (Phase 1)
Parse and import 286 device protocols from RTL_433:
- Created RTL_433 C source parser (scripts/parse_rtl433_devices.py)
- Extracted device names, modulation, timing parameters, categories
- Generated structured JSON database (data/rtl_433_protocols.json)
Protocol breakdown:
- 116 weather stations/sensors (Acurite, Oregon, LaCrosse, Fine Offset)
- 39 generic sensors (temperature, humidity, leak detectors)
- 25 TPMS tire pressure sensors (BMW, Ford, Toyota, etc.)
- 23 security devices (alarms, motion, smoke)
- 18 home automation (remotes, doorbells, garage doors)
- 52 other (energy meters, lighting, automotive)
Modulation analysis:
- 152 OOK (On-Off Keying) devices
- 105 FSK (Frequency Shift Keying) devices
- Timing parameters extracted (pulse widths, gaps, resets)
Next steps:
- Integrate RTL_433 DB into matching engine
- Add timing analysis for RAW captures
- Target: 75-80% accuracy (from current 60-70%)
Trilltechnician
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