Phase 3 Complete: Web Interface MVP
Major Achievements: - ✅ Full web interface (1,520+ lines of frontend code) - ✅ Interactive Leaflet.js map with marker clustering - ✅ Drag-and-drop upload system with GPS input - ✅ Search & filter UI with multi-criteria - ✅ Statistics dashboard with Chart.js - ✅ Responsive mobile-friendly design Backend: - ✅ FastAPI static file serving - ✅ Simplified server mode (main_simple.py) - ✅ Improved startup script with port auto-selection - ✅ PostgreSQL schema ready (requires setup) Database: - ✅ SQLite populated with 85 Flipper Zero signatures - ✅ Device matching system operational - ✅ Frequency-based search working Documentation: - ✅ PHASE_3_COMPLETE.md - Technical summary - ✅ WEB_INTERFACE_README.md - User guide - ✅ WEBAPP_STARTUP_GUIDE.md - Troubleshooting - ✅ POSTGRESQL_SETUP_EXPLANATION.md - DB setup guide - ✅ DATABASE_POPULATION_SUCCESS.md - Import report - ✅ DEVICE_IDENTIFICATION_REPORT.md - Matching analysis Files Created: - templates/index.html (260 lines) - static/css/main.css (500 lines) - static/js/*.js (760 lines total) - src/api/main_simple.py (simplified server) - start_web.sh (auto port selection) Status: Production MVP Ready Next: Phase 4 - API & Integration 🛰️ Generated with Claude Code https://claude.com/claude-code Co-Authored-By: Claude <noreply@anthropic.com>
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#!/usr/bin/env python3
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"""
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Match T-Embed captures against Flipper Zero signature database
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Demonstrates device identification using expanded signature knowledge base
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"""
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import sys
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from pathlib import Path
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from typing import List, Dict
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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.parser.sub_parser import SubFileParser
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def load_flipper_signatures(flipper_dir: Path) -> List[Dict]:
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"""Load all Flipper Zero signatures"""
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parser = SubFileParser()
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signatures = []
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for sub_file in flipper_dir.glob('**/*.sub'):
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try:
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metadata = parser.parse(str(sub_file))
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signatures.append({
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'device_name': sub_file.stem,
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'filename': sub_file.name,
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'frequency': metadata.frequency,
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'protocol': metadata.protocol or 'RAW',
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'file_format': metadata.file_format,
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'bit_length': metadata.bit_length,
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'has_raw': bool(metadata.raw_data),
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'raw_samples': len(metadata.raw_data) if metadata.raw_data else 0
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})
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except:
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pass
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return signatures
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def match_by_frequency(target_freq: int, signatures: List[Dict], tolerance_hz: int = 10000) -> List[Dict]:
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"""Match by frequency with tolerance"""
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matches = []
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for sig in signatures:
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freq_diff = abs(sig['frequency'] - target_freq)
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if freq_diff <= tolerance_hz:
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confidence = 1.0 - (freq_diff / tolerance_hz)
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confidence = max(0.5, confidence)
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matches.append({
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'signature': sig,
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'confidence': confidence,
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'freq_diff_hz': freq_diff,
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'match_method': 'frequency'
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})
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return sorted(matches, key=lambda x: x['confidence'], reverse=True)
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def main():
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"""Main entry point"""
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print("="*80)
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print("DEVICE MATCHING: T-Embed vs Flipper Zero Database")
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print("="*80)
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print()
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# Load Flipper signatures
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flipper_dir = Path(__file__).parent.parent / 'signatures' / 'flipperzero-firmware'
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if not flipper_dir.exists():
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print("❌ Flipper Zero database not found")
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return 1
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print("Loading Flipper Zero signature database...")
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signatures = load_flipper_signatures(flipper_dir)
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print(f"✅ Loaded {len(signatures)} signatures\n")
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# Load T-Embed capture
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tembed_dir = Path(__file__).parent.parent / 'signatures' / 't-embed-rf'
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parser = SubFileParser()
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tembed_file = tembed_dir / 'raw_7.sub'
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print(f"Analyzing T-Embed capture: {tembed_file.name}")
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print("-"*80)
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metadata = parser.parse(str(tembed_file))
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print(f"Frequency: {metadata.frequency/1e6:.2f} MHz")
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print(f"Protocol: {metadata.protocol or 'RAW (undecoded)'}")
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print(f"Format: {metadata.file_format}")
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if metadata.raw_data:
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print(f"RAW Samples: {len(metadata.raw_data)}")
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print(f"\n{'='*80}")
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print("MATCHING AGAINST FLIPPER ZERO DATABASE")
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print(f"{'='*80}\n")
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# Match by frequency (±10 kHz tolerance)
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matches = match_by_frequency(metadata.frequency, signatures, tolerance_hz=10000)
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if matches:
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print(f"Found {len(matches)} potential matches:\n")
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for i, match in enumerate(matches[:10], 1):
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sig = match['signature']
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print(f"{i}. {sig['device_name']}")
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print(f" Frequency: {sig['frequency']/1e6:.3f} MHz (diff: {match['freq_diff_hz']/1000:.1f} kHz)")
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print(f" Protocol: {sig['protocol']}")
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print(f" Format: {sig['file_format']}")
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print(f" Confidence: {match['confidence']:.1%}")
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print()
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# Best match
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best = matches[0]
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print(f"{'='*80}")
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print(f"BEST MATCH: {best['signature']['device_name']}")
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print(f"Confidence: {best['confidence']:.1%}")
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print(f"Method: Frequency matching ({best['freq_diff_hz']/1000:.1f} kHz difference)")
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print(f"{'='*80}")
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else:
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print("❌ No matches found in Flipper Zero database")
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print("\nThis device is at 915 MHz (ISM band)")
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print("Flipper Zero database contains mostly 433 MHz devices")
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print("\nTo improve matching:")
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print("- Import RTL_433 database (has 915 MHz devices)")
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print("- Add more T-Embed captures from wardriving")
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print("- Import community-contributed 915 MHz signatures")
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print(f"\n{'='*80}")
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print("DATABASE COVERAGE ANALYSIS")
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print(f"{'='*80}\n")
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# Analyze frequency coverage
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freq_groups = {}
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for sig in signatures:
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freq_mhz = sig['frequency'] / 1e6
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freq_band = f"{int(freq_mhz/100)*100}-{int(freq_mhz/100)*100+100}"
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if freq_band not in freq_groups:
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freq_groups[freq_band] = 0
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freq_groups[freq_band] += 1
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print("Frequency Band Coverage:")
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for band in sorted(freq_groups.keys()):
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print(f" {band} MHz: {freq_groups[band]} devices")
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# Check if 915 MHz covered
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target_freq = metadata.frequency / 1e6
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target_band = f"{int(target_freq/100)*100}-{int(target_freq/100)*100+100}"
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print(f"\nTarget device: {target_freq:.2f} MHz ({target_band} MHz band)")
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if target_band in freq_groups:
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print(f"✅ Coverage: {freq_groups[target_band]} devices in target band")
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else:
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print(f"❌ No coverage: Target band not in Flipper database")
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print("\n" + "="*80)
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return 0
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if __name__ == '__main__':
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sys.exit(main())
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