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.
This commit is contained in:
@@ -0,0 +1,87 @@
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#!/usr/bin/env python3
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"""
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Re-match existing captures with device matcher
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Runs the device matcher on all existing captures in the database
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"""
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import sys
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import json
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from pathlib import Path
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# Add project root to path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from src.matcher.simple_matcher import get_matcher
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def rematch_captures(storage_file):
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"""Re-run device matching on existing captures"""
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if not Path(storage_file).exists():
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print(f"❌ Storage file not found: {storage_file}")
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return 1
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# Load existing captures
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with open(storage_file, 'r') as f:
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data = json.load(f)
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captures = data.get('captures', [])
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if not captures:
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print("ℹ️ No captures to process")
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return 0
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print(f"🔄 Re-matching {len(captures)} captures...")
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matcher = get_matcher()
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updated_count = 0
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for i, capture in enumerate(captures, 1):
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frequency = capture.get('frequency', 0)
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protocol = capture.get('protocol', 'RAW')
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preset = capture.get('preset', 'Unknown')
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# Skip if already has device data
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if capture.get('device_name'):
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continue
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# Perform matching
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matches = matcher.match(frequency, protocol, preset)
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best_match = matches[0] if matches else None
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if best_match:
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# Update capture with device data
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capture['device_name'] = best_match.device_name
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capture['device_category'] = best_match.device_category
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capture['match_confidence'] = best_match.confidence
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capture['match_method'] = best_match.match_method
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capture['device_description'] = best_match.description
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capture['matched_devices'] = [
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{
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"device_name": m.device_name,
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"category": m.device_category,
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"confidence": m.confidence,
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"method": m.match_method,
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"description": m.description
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}
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for m in matches[:5]
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]
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updated_count += 1
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print(f" [{i}/{len(captures)}] {capture['filename']}: {best_match.device_name} ({best_match.confidence:.0%})")
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else:
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print(f" [{i}/{len(captures)}] {capture['filename']}: No match found")
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# Save updated data
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with open(storage_file, 'w') as f:
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json.dump(data, f, indent=2)
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print(f"\n✅ Updated {updated_count}/{len(captures)} captures with device information")
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return 0
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if __name__ == '__main__':
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STORAGE_FILE = Path(__file__).parent.parent / "data" / "captures_simple.json"
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sys.exit(rematch_captures(STORAGE_FILE))
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+50
-3
@@ -21,6 +21,7 @@ sys.path.insert(0, str(Path(__file__).parent.parent.parent))
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from src.parser.sub_parser import SubFileParser
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from src.parser.gps_extractor import GPSFilenameExtractor
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from src.matcher.simple_matcher import get_matcher
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# =============================================================================
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# APPLICATION INSTANCE
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@@ -151,6 +152,24 @@ async def get_captures():
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}
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@app.get("/api/v1/captures/{capture_id}")
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async def get_capture_detail(capture_id: int):
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"""Get detailed information for a specific capture"""
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# Find capture by ID
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capture = next((c for c in captures_storage if c.get("id") == capture_id), None)
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if not capture:
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return {
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"success": False,
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"message": f"Capture with ID {capture_id} not found"
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}
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return {
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"success": True,
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"capture": capture
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}
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@app.get("/api/v1/stats/summary")
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async def get_stats():
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"""Return stats from in-memory storage"""
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@@ -300,6 +319,18 @@ async def upload_captures(
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# Try to extract GPS from filename
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gps_coords = gps_extractor.extract(file.filename)
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# Extract signal parameters
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frequency = metadata.frequency if hasattr(metadata, 'frequency') else 0
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protocol = metadata.protocol if hasattr(metadata, 'protocol') else "RAW"
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preset = metadata.preset if hasattr(metadata, 'preset') else "Unknown"
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# Perform device matching
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matcher = get_matcher()
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matches = matcher.match(frequency, protocol, preset)
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# Get best match
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best_match = matches[0] if matches else None
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# Use GPS from manifest or filename
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global upload_counter
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upload_counter += 1
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@@ -307,15 +338,31 @@ async def upload_captures(
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capture_info = {
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"id": upload_counter,
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"filename": file.filename,
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"frequency": metadata.frequency if hasattr(metadata, 'frequency') else 0,
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"protocol": metadata.protocol if hasattr(metadata, 'protocol') else "RAW",
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"preset": metadata.preset if hasattr(metadata, 'preset') else "Unknown",
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"frequency": frequency,
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"protocol": protocol,
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"preset": preset,
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"latitude": gps_coords.latitude if gps_coords else manifest_data.get("captures", [{}])[0].get("latitude"),
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"longitude": gps_coords.longitude if gps_coords else manifest_data.get("captures", [{}])[0].get("longitude"),
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"gps_source": gps_coords.source if gps_coords else "manual",
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"timestamp": manifest_data.get("captures", [{}])[0].get("timestamp", ""),
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"data_source": manifest_data.get("data_source", "production"), # production, test, or mock
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"session_id": manifest_data.get("session_uuid", ""),
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# Device identification fields
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"device_name": best_match.device_name if best_match else None,
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"device_category": best_match.device_category if best_match else None,
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"match_confidence": best_match.confidence if best_match else None,
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"match_method": best_match.match_method if best_match else None,
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"device_description": best_match.description if best_match else None,
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"matched_devices": [
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{
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"device_name": m.device_name,
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"category": m.device_category,
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"confidence": m.confidence,
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"method": m.match_method,
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"description": m.description
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}
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for m in matches[:5] # Top 5 matches
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] if matches else []
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}
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# Store in memory
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@@ -0,0 +1,285 @@
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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 = {}
|
||||
|
||||
for match in matches:
|
||||
if match.device_name not in seen or match.confidence > seen[match.device_name].confidence:
|
||||
seen[match.device_name] = match
|
||||
|
||||
return list(seen.values())
|
||||
|
||||
def get_best_match(self, frequency: int, protocol: str = None, preset: str = None) -> Optional[DeviceMatch]:
|
||||
"""Get single best match"""
|
||||
matches = self.match(frequency, protocol, preset)
|
||||
return matches[0] if matches else None
|
||||
|
||||
def format_device_string(self, match: DeviceMatch) -> str:
|
||||
"""Format device match as human-readable string"""
|
||||
return f"{match.device_name} ({match.device_category})"
|
||||
|
||||
|
||||
# Singleton instance
|
||||
_matcher = None
|
||||
|
||||
def get_matcher() -> SimpleDeviceMatcher:
|
||||
"""Get singleton matcher instance"""
|
||||
global _matcher
|
||||
if _matcher is None:
|
||||
_matcher = SimpleDeviceMatcher()
|
||||
return _matcher
|
||||
@@ -543,6 +543,209 @@ footer p {
|
||||
margin-bottom: 0.5rem;
|
||||
}
|
||||
|
||||
/* Modal Styles */
|
||||
.modal {
|
||||
display: none;
|
||||
position: fixed;
|
||||
z-index: 2000;
|
||||
left: 0;
|
||||
top: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
background-color: rgba(0, 0, 0, 0.6);
|
||||
backdrop-filter: blur(4px);
|
||||
}
|
||||
|
||||
.modal.active {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
}
|
||||
|
||||
.modal-content {
|
||||
background: white;
|
||||
border-radius: 0.5rem;
|
||||
box-shadow: var(--shadow-lg);
|
||||
max-width: 800px;
|
||||
width: 90%;
|
||||
max-height: 90vh;
|
||||
overflow-y: auto;
|
||||
position: relative;
|
||||
animation: modalSlideIn 0.3s ease-out;
|
||||
}
|
||||
|
||||
@keyframes modalSlideIn {
|
||||
from {
|
||||
opacity: 0;
|
||||
transform: translateY(-50px);
|
||||
}
|
||||
to {
|
||||
opacity: 1;
|
||||
transform: translateY(0);
|
||||
}
|
||||
}
|
||||
|
||||
.modal-header {
|
||||
padding: 1.5rem;
|
||||
border-bottom: 1px solid var(--border-color);
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: start;
|
||||
}
|
||||
|
||||
.modal-header h2 {
|
||||
margin: 0;
|
||||
font-size: 1.5rem;
|
||||
}
|
||||
|
||||
.modal-close {
|
||||
background: none;
|
||||
border: none;
|
||||
font-size: 1.5rem;
|
||||
cursor: pointer;
|
||||
color: var(--text-secondary);
|
||||
padding: 0;
|
||||
width: 32px;
|
||||
height: 32px;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
border-radius: 0.25rem;
|
||||
transition: all 0.2s;
|
||||
}
|
||||
|
||||
.modal-close:hover {
|
||||
background: var(--light-bg);
|
||||
color: var(--text-primary);
|
||||
}
|
||||
|
||||
.modal-body {
|
||||
padding: 1.5rem;
|
||||
}
|
||||
|
||||
.detail-section {
|
||||
margin-bottom: 2rem;
|
||||
}
|
||||
|
||||
.detail-section:last-child {
|
||||
margin-bottom: 0;
|
||||
}
|
||||
|
||||
.detail-section h3 {
|
||||
font-size: 1.125rem;
|
||||
margin-bottom: 1rem;
|
||||
color: var(--text-primary);
|
||||
border-bottom: 2px solid var(--primary-color);
|
||||
padding-bottom: 0.5rem;
|
||||
}
|
||||
|
||||
.detail-grid {
|
||||
display: grid;
|
||||
grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
|
||||
gap: 1rem;
|
||||
}
|
||||
|
||||
.detail-item {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 0.25rem;
|
||||
}
|
||||
|
||||
.detail-label {
|
||||
font-size: 0.875rem;
|
||||
color: var(--text-secondary);
|
||||
font-weight: 500;
|
||||
}
|
||||
|
||||
.detail-value {
|
||||
font-size: 1rem;
|
||||
color: var(--text-primary);
|
||||
font-weight: 400;
|
||||
}
|
||||
|
||||
.detail-value.highlight {
|
||||
color: var(--primary-color);
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
.confidence-bar {
|
||||
height: 8px;
|
||||
background: var(--light-bg);
|
||||
border-radius: 4px;
|
||||
overflow: hidden;
|
||||
margin-top: 0.5rem;
|
||||
}
|
||||
|
||||
.confidence-fill {
|
||||
height: 100%;
|
||||
background: var(--success-color);
|
||||
transition: width 0.3s ease;
|
||||
}
|
||||
|
||||
.confidence-fill.medium {
|
||||
background: var(--warning-color);
|
||||
}
|
||||
|
||||
.confidence-fill.low {
|
||||
background: var(--danger-color);
|
||||
}
|
||||
|
||||
.matched-devices-list {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 0.75rem;
|
||||
}
|
||||
|
||||
.matched-device-item {
|
||||
padding: 1rem;
|
||||
background: var(--light-bg);
|
||||
border-radius: 0.375rem;
|
||||
border-left: 4px solid var(--primary-color);
|
||||
}
|
||||
|
||||
.matched-device-header {
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
margin-bottom: 0.5rem;
|
||||
}
|
||||
|
||||
.matched-device-name {
|
||||
font-weight: 600;
|
||||
color: var(--text-primary);
|
||||
}
|
||||
|
||||
.matched-device-confidence {
|
||||
background: var(--primary-color);
|
||||
color: white;
|
||||
padding: 0.25rem 0.5rem;
|
||||
border-radius: 0.25rem;
|
||||
font-size: 0.875rem;
|
||||
}
|
||||
|
||||
.matched-device-category {
|
||||
display: inline-block;
|
||||
background: white;
|
||||
padding: 0.25rem 0.5rem;
|
||||
border-radius: 0.25rem;
|
||||
font-size: 0.875rem;
|
||||
color: var(--text-secondary);
|
||||
margin-bottom: 0.5rem;
|
||||
}
|
||||
|
||||
.matched-device-description {
|
||||
font-size: 0.875rem;
|
||||
color: var(--text-secondary);
|
||||
margin-top: 0.5rem;
|
||||
}
|
||||
|
||||
.matched-device-method {
|
||||
font-size: 0.75rem;
|
||||
color: var(--text-secondary);
|
||||
margin-top: 0.5rem;
|
||||
font-style: italic;
|
||||
}
|
||||
|
||||
/* Responsive */
|
||||
@media (max-width: 768px) {
|
||||
header .container {
|
||||
|
||||
@@ -0,0 +1,230 @@
|
||||
// GigLez - Capture Detail Modal
|
||||
|
||||
async function viewCaptureDetails(captureId) {
|
||||
const modal = document.getElementById('detail-modal');
|
||||
const modalBody = document.getElementById('modal-body-content');
|
||||
|
||||
// Show loading state
|
||||
modal.classList.add('active');
|
||||
modalBody.innerHTML = '<div style="text-align: center; padding: 2rem;">Loading...</div>';
|
||||
|
||||
try {
|
||||
// Fetch capture details
|
||||
const response = await fetch(`/api/v1/captures/${captureId}`);
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to fetch capture details');
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
|
||||
if (!data.success) {
|
||||
throw new Error(data.message);
|
||||
}
|
||||
|
||||
// Render detail view
|
||||
modalBody.innerHTML = renderCaptureDetail(data.capture);
|
||||
|
||||
} catch (error) {
|
||||
modalBody.innerHTML = `
|
||||
<div style="text-align: center; padding: 2rem; color: var(--danger-color);">
|
||||
<p><strong>Error loading details:</strong></p>
|
||||
<p>${error.message}</p>
|
||||
</div>
|
||||
`;
|
||||
}
|
||||
}
|
||||
|
||||
function renderCaptureDetail(capture) {
|
||||
const freqMHz = (capture.frequency / 1e6).toFixed(2);
|
||||
const date = new Date(capture.timestamp || Date.now()).toLocaleString();
|
||||
|
||||
// Device identification section
|
||||
const deviceSection = capture.device_name ? renderDeviceSection(capture) : renderNoDeviceSection();
|
||||
|
||||
// Matched devices section
|
||||
const matchedSection = capture.matched_devices && capture.matched_devices.length > 0
|
||||
? renderMatchedDevices(capture.matched_devices)
|
||||
: '';
|
||||
|
||||
return `
|
||||
<!-- Device Identification -->
|
||||
${deviceSection}
|
||||
|
||||
<!-- Signal Information -->
|
||||
<div class="detail-section">
|
||||
<h3>Signal Information</h3>
|
||||
<div class="detail-grid">
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Frequency</span>
|
||||
<span class="detail-value highlight">${freqMHz} MHz</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Protocol</span>
|
||||
<span class="detail-value">${capture.protocol || 'RAW'}</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Modulation</span>
|
||||
<span class="detail-value">${capture.preset || 'Unknown'}</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Filename</span>
|
||||
<span class="detail-value">${capture.filename}</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Location Information -->
|
||||
<div class="detail-section">
|
||||
<h3>Location Information</h3>
|
||||
<div class="detail-grid">
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Latitude</span>
|
||||
<span class="detail-value">${capture.latitude.toFixed(6)}</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Longitude</span>
|
||||
<span class="detail-value">${capture.longitude.toFixed(6)}</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">GPS Source</span>
|
||||
<span class="detail-value">${capture.gps_source || 'unknown'}</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Timestamp</span>
|
||||
<span class="detail-value">${date}</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
${matchedSection}
|
||||
|
||||
<!-- Metadata -->
|
||||
<div class="detail-section">
|
||||
<h3>Metadata</h3>
|
||||
<div class="detail-grid">
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Capture ID</span>
|
||||
<span class="detail-value">${capture.id}</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Data Source</span>
|
||||
<span class="detail-value">${capture.data_source || 'production'}</span>
|
||||
</div>
|
||||
${capture.session_id ? `
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Session ID</span>
|
||||
<span class="detail-value">${capture.session_id}</span>
|
||||
</div>
|
||||
` : ''}
|
||||
</div>
|
||||
</div>
|
||||
`;
|
||||
}
|
||||
|
||||
function renderDeviceSection(capture) {
|
||||
const confidencePercent = (capture.match_confidence * 100).toFixed(0);
|
||||
const confidenceClass = capture.match_confidence >= 0.8 ? '' :
|
||||
capture.match_confidence >= 0.6 ? 'medium' : 'low';
|
||||
|
||||
return `
|
||||
<div class="detail-section">
|
||||
<h3>Device Identification</h3>
|
||||
<div class="detail-grid">
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Device Name</span>
|
||||
<span class="detail-value highlight">${capture.device_name}</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Category</span>
|
||||
<span class="detail-value">${capture.device_category}</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Match Method</span>
|
||||
<span class="detail-value">${capture.match_method || 'unknown'}</span>
|
||||
</div>
|
||||
<div class="detail-item">
|
||||
<span class="detail-label">Confidence</span>
|
||||
<span class="detail-value">${confidencePercent}%</span>
|
||||
<div class="confidence-bar">
|
||||
<div class="confidence-fill ${confidenceClass}" style="width: ${confidencePercent}%"></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
${capture.device_description ? `
|
||||
<div style="margin-top: 1rem; padding: 1rem; background: var(--light-bg); border-radius: 0.375rem;">
|
||||
<strong>Description:</strong> ${capture.device_description}
|
||||
</div>
|
||||
` : ''}
|
||||
</div>
|
||||
`;
|
||||
}
|
||||
|
||||
function renderNoDeviceSection() {
|
||||
return `
|
||||
<div class="detail-section">
|
||||
<h3>Device Identification</h3>
|
||||
<div style="padding: 2rem; text-align: center; background: var(--light-bg); border-radius: 0.375rem;">
|
||||
<p style="color: var(--text-secondary);">No device match found for this capture.</p>
|
||||
<p style="color: var(--text-secondary); font-size: 0.875rem; margin-top: 0.5rem;">
|
||||
This could be an unknown or custom protocol.
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
`;
|
||||
}
|
||||
|
||||
function renderMatchedDevices(matches) {
|
||||
if (!matches || matches.length === 0) return '';
|
||||
|
||||
const matchesHtml = matches.map(match => {
|
||||
const confidencePercent = (match.confidence * 100).toFixed(0);
|
||||
return `
|
||||
<div class="matched-device-item">
|
||||
<div class="matched-device-header">
|
||||
<span class="matched-device-name">${match.device_name}</span>
|
||||
<span class="matched-device-confidence">${confidencePercent}%</span>
|
||||
</div>
|
||||
<span class="matched-device-category">${match.category}</span>
|
||||
<p class="matched-device-description">${match.description}</p>
|
||||
<p class="matched-device-method">Matched via: ${match.method}</p>
|
||||
</div>
|
||||
`;
|
||||
}).join('');
|
||||
|
||||
return `
|
||||
<div class="detail-section">
|
||||
<h3>Alternative Matches</h3>
|
||||
<div class="matched-devices-list">
|
||||
${matchesHtml}
|
||||
</div>
|
||||
</div>
|
||||
`;
|
||||
}
|
||||
|
||||
function closeDetailModal() {
|
||||
const modal = document.getElementById('detail-modal');
|
||||
modal.classList.remove('active');
|
||||
}
|
||||
|
||||
// Close modal when clicking outside
|
||||
document.addEventListener('DOMContentLoaded', () => {
|
||||
const modal = document.getElementById('detail-modal');
|
||||
|
||||
modal.addEventListener('click', (e) => {
|
||||
if (e.target === modal) {
|
||||
closeDetailModal();
|
||||
}
|
||||
});
|
||||
|
||||
// Close on escape key
|
||||
document.addEventListener('keydown', (e) => {
|
||||
if (e.key === 'Escape' && modal.classList.contains('active')) {
|
||||
closeDetailModal();
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
// Export for use in other modules
|
||||
window.viewCaptureDetails = viewCaptureDetails;
|
||||
window.closeDetailModal = closeDetailModal;
|
||||
+1
-6
@@ -179,7 +179,7 @@ function createPopupContent(capture) {
|
||||
<p><strong>Captured:</strong> ${date}</p>
|
||||
<p><strong>Location:</strong> ${capture.latitude.toFixed(6)}, ${capture.longitude.toFixed(6)}</p>
|
||||
${capture.accuracy ? `<p><strong>Accuracy:</strong> ±${capture.accuracy.toFixed(1)}m</p>` : ''}
|
||||
<button onclick="viewCaptureDetails('${capture.file_hash}')" class="btn btn-primary" style="margin-top: 0.5rem;">
|
||||
<button onclick="viewCaptureDetails(${capture.id})" class="btn btn-primary" style="margin-top: 0.5rem;">
|
||||
View Details
|
||||
</button>
|
||||
</div>
|
||||
@@ -199,10 +199,5 @@ function updateStats() {
|
||||
document.getElementById('unique-devices').textContent = uniqueDevices;
|
||||
}
|
||||
|
||||
function viewCaptureDetails(fileHash) {
|
||||
// Navigate to detail page (to be implemented)
|
||||
alert(`Viewing details for capture: ${fileHash}`);
|
||||
}
|
||||
|
||||
// Export for external use
|
||||
window.reloadMapData = loadCaptures;
|
||||
|
||||
+2
-7
@@ -58,7 +58,7 @@ function displaySearchResults(captures) {
|
||||
|
||||
function createResultCard(capture) {
|
||||
const freqMHz = (capture.frequency / 1e6).toFixed(2);
|
||||
const date = new Date(capture.captured_at).toLocaleString();
|
||||
const date = new Date(capture.timestamp || Date.now()).toLocaleString();
|
||||
|
||||
const deviceName = capture.device_name || 'Unknown Device';
|
||||
const protocol = capture.protocol || 'RAW';
|
||||
@@ -67,7 +67,7 @@ function createResultCard(capture) {
|
||||
: 'N/A';
|
||||
|
||||
return `
|
||||
<div class="result-card" onclick="viewCaptureDetails('${capture.file_hash}')">
|
||||
<div class="result-card" onclick="viewCaptureDetails(${capture.id})">
|
||||
<div class="result-header">
|
||||
<div class="result-title">${deviceName}</div>
|
||||
<div class="result-frequency">${freqMHz} MHz</div>
|
||||
@@ -89,8 +89,3 @@ function createResultCard(capture) {
|
||||
</div>
|
||||
`;
|
||||
}
|
||||
|
||||
function viewCaptureDetails(fileHash) {
|
||||
// Show detail modal or navigate to detail page
|
||||
alert(`Viewing details for: ${fileHash}\n\nDetail view coming soon!`);
|
||||
}
|
||||
|
||||
@@ -256,6 +256,19 @@
|
||||
</section>
|
||||
</main>
|
||||
|
||||
<!-- Capture Detail Modal -->
|
||||
<div id="detail-modal" class="modal">
|
||||
<div class="modal-content">
|
||||
<div class="modal-header">
|
||||
<h2>Capture Details</h2>
|
||||
<button class="modal-close" onclick="closeDetailModal()">×</button>
|
||||
</div>
|
||||
<div class="modal-body" id="modal-body-content">
|
||||
<!-- Content loaded dynamically -->
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Footer -->
|
||||
<footer>
|
||||
<div class="container">
|
||||
@@ -272,6 +285,7 @@
|
||||
<script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.1/dist/chart.umd.min.js"></script>
|
||||
|
||||
<!-- Custom JS -->
|
||||
<script src="/static/js/detail-modal.js"></script>
|
||||
<script src="/static/js/map.js"></script>
|
||||
<script src="/static/js/upload.js"></script>
|
||||
<script src="/static/js/search.js"></script>
|
||||
|
||||
Reference in New Issue
Block a user