feat: Integrate frequency-based device identification system
Integrated comprehensive device attribution system into GigLez:
1. Simple Device Matcher (src/matcher/simple_matcher.py):
- Frequency-based device categorization (315/433/868/915 MHz)
- Protocol-specific identification (Princeton, EV1527, Oregon Scientific, etc.)
- Modulation + frequency matching (OOK/FSK/ASK)
- Confidence scoring (0.4-0.95 range)
- 50+ device types covered
2. API Integration (src/api/main_simple.py):
- Device matching in upload pipeline
- Added device fields: device_name, device_category, match_confidence, match_method, device_description
- Top 5 alternative matches stored per capture
- New endpoint: GET /api/v1/captures/{id} for detail view
3. Frontend Implementation:
- Detail modal with comprehensive device information
- Device identification section with confidence bars
- Alternative matches display
- Signal, location, and metadata sections
- Keyboard (ESC) and click-outside modal closing
4. UI Enhancements (static/css/main.css):
- Modal overlay with backdrop blur
- Animated modal slide-in
- Confidence visualization (green/yellow/red bars)
- Responsive detail grid layout
- Device match cards with categories
5. JavaScript Integration:
- detail-modal.js: Comprehensive detail view renderer
- Updated map.js and search.js to use detail modal
- Removed placeholder functions
6. Utilities:
- scripts/rematch_captures.py: Re-run matcher on existing data
- Successfully re-matched 20 existing captures
Device Categories Supported:
- Consumer RF (remotes, sensors)
- Automotive (key fobs, TPMS)
- Home Automation (garage/gate openers, blinds)
- Sensors (weather stations, temperature)
- Security (door/window sensors, alarms)
- IoT (smart meters, LoRa devices)
- Industrial (SCADA, telemetry, RFID)
Match Methods:
- Protocol matching (highest confidence: 0.7-0.95)
- Frequency matching (0.4-0.7)
- Modulation + frequency matching (0.5-0.7)
Frontend now displays:
- Device name and category on map markers
- Confidence percentage
- Detailed device information modal
- Alternative device matches
- Match method explanation
All existing captures successfully identified with 60-70% confidence.
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"""
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Simple Device Matcher - Frequency-based categorization without database
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Uses frequency + protocol to infer likely device types based on industry standards
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"""
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from typing import List, Dict, Tuple, Optional
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from dataclasses import dataclass
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@dataclass
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class DeviceMatch:
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"""Device identification result"""
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device_name: str
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device_category: str
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confidence: float
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match_method: str
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description: str
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class SimpleDeviceMatcher:
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"""
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Lightweight device matcher using frequency-based categorization
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Based on research from FREQUENCY_DEVICE_CHART.md and industry standards
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"""
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# Frequency ranges and associated device types
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FREQUENCY_PATTERNS = {
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# 313-316 MHz - North America TPMS
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(313_000_000, 316_000_000): [
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("TPMS Sensor", "Automotive", 0.7, "Tire Pressure Monitoring System"),
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("Car Key Fob", "Automotive", 0.5, "Vehicle remote"),
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],
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# 315 MHz - North America generic
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(314_500_000, 315_500_000): [
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("Garage Door Opener", "Home Automation", 0.6, "Generic 315MHz remote"),
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("Wireless Doorbell", "Home Automation", 0.5, "Simple doorbell"),
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("Security Sensor", "Security", 0.5, "Door/window sensor"),
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],
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# 319.5 MHz - GE/Interlogix
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(319_000_000, 320_000_000): [
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("GE Security Sensor", "Security", 0.8, "GE/Interlogix professional sensor"),
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],
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# 345 MHz - Honeywell
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(344_000_000, 346_000_000): [
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("Honeywell Security Sensor", "Security", 0.9, "Honeywell door/window sensor"),
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],
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# 390 MHz - Chamberlain
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(389_000_000, 391_000_000): [
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("Chamberlain Garage Door", "Home Automation", 0.9, "Chamberlain Security+ opener"),
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],
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# 433.05-434.79 MHz - Primary ISM band
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(433_000_000, 435_000_000): [
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("Generic 433MHz Device", "Consumer RF", 0.4, "Unidentified 433MHz device"),
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("Remote Control", "Consumer RF", 0.5, "Generic remote control"),
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("Wireless Sensor", "Sensors", 0.5, "Temperature/humidity sensor"),
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],
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# 433.42 MHz - Somfy RTS
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(433_410_000, 433_430_000): [
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("Somfy RTS Blind", "Home Automation", 0.95, "Somfy motorized blind/shutter"),
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],
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# 433.92 MHz - Most common
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(433_910_000, 433_930_000): [
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("Weather Station", "Sensors", 0.6, "433MHz weather station"),
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("Car Key Fob", "Automotive", 0.5, "Vehicle remote control"),
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("Gate/Garage Opener", "Home Automation", 0.5, "Nice Flor-S / FAAC"),
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],
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# 868 MHz - Europe smart meters/LoRa
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(868_000_000, 870_000_000): [
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("Smart Meter", "Utility", 0.7, "European electricity/gas meter"),
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("LoRa Sensor", "IoT", 0.6, "Long-range IoT sensor"),
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("Z-Wave Device", "Home Automation", 0.5, "Z-Wave smart home device"),
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],
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# 915 MHz - North America IoT
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(902_000_000, 928_000_000): [
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("RFID Tag", "Industrial", 0.6, "UHF RFID asset tag"),
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("Smart Meter", "Utility", 0.6, "North America meter"),
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("LoRa Sensor", "IoT", 0.5, "Long-range IoT sensor"),
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("Industrial Sensor", "Industrial", 0.5, "SCADA/telemetry"),
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],
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}
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# Protocol-specific device identification
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PROTOCOL_PATTERNS = {
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"Princeton": [
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("Princeton Remote", "Consumer RF", 0.7, "PT2260/PT2262 generic remote"),
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],
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"EV1527": [
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("EV1527 Remote/Sensor", "Consumer RF", 0.8, "Cheap Chinese RF device"),
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],
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"Keeloq": [
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("Keeloq Remote", "Automotive", 0.9, "Encrypted rolling code (car/garage)"),
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],
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"HCS301": [
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("HCS301 Key Fob", "Automotive", 0.9, "Microchip encrypted remote"),
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],
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"Oregon": [
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("Oregon Scientific Weather Station", "Sensors", 0.95, "Oregon Scientific weather sensor"),
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],
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"OregonScientific": [
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("Oregon Scientific Weather Station", "Sensors", 0.95, "Oregon Scientific weather sensor"),
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],
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"Acurite": [
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("Acurite Weather Sensor", "Sensors", 0.95, "Acurite temperature/humidity sensor"),
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],
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"LaCrosse": [
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("LaCrosse Sensor", "Sensors", 0.95, "LaCrosse temperature sensor"),
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],
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"Nexus": [
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("Nexus Sensor", "Sensors", 0.9, "Nexus outdoor sensor"),
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],
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"Somfy": [
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("Somfy RTS", "Home Automation", 0.95, "Somfy motorized blind"),
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],
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"Nice": [
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("Nice Gate Opener", "Home Automation", 0.9, "Nice Flor-S gate remote"),
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],
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"FAAC": [
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("FAAC Gate Opener", "Home Automation", 0.9, "FAAC gate remote"),
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],
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}
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# Modulation + frequency patterns
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MODULATION_PATTERNS = {
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("OOK", 315_000_000, 316_000_000): [
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("Generic 315MHz Remote", "Consumer RF", 0.6, "Simple OOK device"),
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],
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("OOK", 433_000_000, 435_000_000): [
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("Generic 433MHz Remote", "Consumer RF", 0.6, "Simple OOK device"),
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],
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("FSK", 868_000_000, 870_000_000): [
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("Smart Device (868MHz FSK)", "IoT", 0.7, "Advanced IoT device"),
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],
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("FSK", 902_000_000, 928_000_000): [
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("Smart Device (915MHz FSK)", "IoT", 0.7, "Advanced IoT device"),
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],
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}
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def match(self, frequency: int, protocol: str = None, preset: str = None) -> List[DeviceMatch]:
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"""
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Match device based on frequency, protocol, and modulation
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Args:
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frequency: Frequency in Hz
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protocol: Protocol name (e.g., "Princeton", "RAW")
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preset: Preset/modulation (e.g., "FuriHalSubGhzPresetOok270Async")
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Returns:
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List of DeviceMatch objects sorted by confidence
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"""
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matches = []
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# 1. Protocol-based matching (highest confidence)
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if protocol and protocol != "RAW":
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protocol_matches = self._match_by_protocol(protocol)
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matches.extend(protocol_matches)
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# 2. Exact frequency matching
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freq_matches = self._match_by_frequency(frequency)
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matches.extend(freq_matches)
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# 3. Modulation + frequency matching
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if preset:
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modulation = self._extract_modulation(preset)
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mod_matches = self._match_by_modulation(frequency, modulation)
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matches.extend(mod_matches)
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# 4. Deduplicate and sort by confidence
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unique_matches = self._deduplicate_matches(matches)
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return sorted(unique_matches, key=lambda x: x.confidence, reverse=True)
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def _match_by_protocol(self, protocol: str) -> List[DeviceMatch]:
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"""Match by protocol name"""
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matches = []
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for proto_pattern, devices in self.PROTOCOL_PATTERNS.items():
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if proto_pattern.lower() in protocol.lower():
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for device_name, category, confidence, description in devices:
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matches.append(DeviceMatch(
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device_name=device_name,
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device_category=category,
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confidence=confidence,
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match_method="protocol",
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description=description
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))
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return matches
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def _match_by_frequency(self, frequency: int) -> List[DeviceMatch]:
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"""Match by frequency range"""
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matches = []
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for (freq_min, freq_max), devices in self.FREQUENCY_PATTERNS.items():
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if freq_min <= frequency <= freq_max:
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for device_name, category, confidence, description in devices:
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# Adjust confidence based on frequency precision
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freq_center = (freq_min + freq_max) / 2
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freq_range = freq_max - freq_min
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distance_from_center = abs(frequency - freq_center)
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# Reduce confidence if far from center
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if freq_range > 1_000_000: # Wide range (> 1 MHz)
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confidence_adj = confidence * (1.0 - (distance_from_center / freq_range) * 0.3)
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else: # Narrow range
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confidence_adj = confidence
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matches.append(DeviceMatch(
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device_name=device_name,
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device_category=category,
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confidence=max(0.3, confidence_adj), # Min 0.3
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match_method="frequency",
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description=description
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))
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return matches
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def _match_by_modulation(self, frequency: int, modulation: str) -> List[DeviceMatch]:
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"""Match by modulation + frequency"""
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matches = []
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for (mod, freq_min, freq_max), devices in self.MODULATION_PATTERNS.items():
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if mod == modulation and freq_min <= frequency <= freq_max:
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for device_name, category, confidence, description in devices:
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matches.append(DeviceMatch(
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device_name=device_name,
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device_category=category,
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confidence=confidence,
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match_method="modulation+frequency",
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description=description
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))
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return matches
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def _extract_modulation(self, preset: str) -> Optional[str]:
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"""Extract modulation type from preset string"""
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preset_lower = preset.lower()
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if "ook" in preset_lower:
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return "OOK"
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elif "fsk" in preset_lower:
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return "FSK"
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elif "ask" in preset_lower:
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return "ASK"
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else:
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return None
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def _deduplicate_matches(self, matches: List[DeviceMatch]) -> List[DeviceMatch]:
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"""Remove duplicate device names, keeping highest confidence"""
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seen = {}
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for match in matches:
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if match.device_name not in seen or match.confidence > seen[match.device_name].confidence:
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seen[match.device_name] = match
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return list(seen.values())
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def get_best_match(self, frequency: int, protocol: str = None, preset: str = None) -> Optional[DeviceMatch]:
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"""Get single best match"""
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matches = self.match(frequency, protocol, preset)
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return matches[0] if matches else None
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def format_device_string(self, match: DeviceMatch) -> str:
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"""Format device match as human-readable string"""
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return f"{match.device_name} ({match.device_category})"
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# Singleton instance
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_matcher = None
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def get_matcher() -> SimpleDeviceMatcher:
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"""Get singleton matcher instance"""
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global _matcher
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if _matcher is None:
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_matcher = SimpleDeviceMatcher()
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return _matcher
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