Files
giglez/static/js/map.js
T
Trilltechnician b083890e96 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.
2026-01-14 10:51:46 -08:00

204 lines
5.8 KiB
JavaScript

// GigLez - Map Visualization
let map;
let markerLayer;
let markerClusterGroup;
let capturesData = [];
// Frequency color mapping
const FREQUENCY_COLORS = {
315: '#10b981', // Green
433: '#3b82f6', // Blue
868: '#f59e0b', // Orange
915: '#ef4444', // Red
default: '#6b7280' // Gray
};
// Initialize map
document.addEventListener('DOMContentLoaded', () => {
initMap();
loadCaptures();
setupMapControls();
});
function initMap() {
// Create map centered on US
map = L.map('map').setView([39.8283, -98.5795], 4);
// Add OpenStreetMap tiles
L.tileLayer('https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png', {
attribution: '&copy; <a href="https://www.openstreetmap.org/copyright">OpenStreetMap</a> contributors',
maxZoom: 19
}).addTo(map);
// Create marker cluster group
markerClusterGroup = L.markerClusterGroup({
maxClusterRadius: 50,
spiderfyOnMaxZoom: true,
showCoverageOnHover: false,
zoomToBoundsOnClick: true
});
// Create regular marker layer
markerLayer = L.layerGroup();
// Add cluster group by default
map.addLayer(markerClusterGroup);
// Export map to window for access from other modules
window.map = map;
}
function setupMapControls() {
// Cluster toggle
document.getElementById('cluster-toggle').addEventListener('change', (e) => {
if (e.target.checked) {
map.removeLayer(markerLayer);
map.addLayer(markerClusterGroup);
} else {
map.removeLayer(markerClusterGroup);
map.addLayer(markerLayer);
}
renderMarkers();
});
// Frequency filter
document.getElementById('frequency-filter').addEventListener('change', () => {
renderMarkers();
});
// Heatmap toggle (placeholder)
document.getElementById('heatmap-toggle').addEventListener('change', (e) => {
if (e.target.checked) {
alert('Heatmap view coming soon!');
e.target.checked = false;
}
});
}
async function loadCaptures() {
try {
const response = await fetch('/api/v1/query/captures?limit=1000');
if (!response.ok) {
console.error('Failed to load captures');
return;
}
const data = await response.json();
capturesData = data.captures || [];
renderMarkers();
updateStats();
} catch (error) {
console.error('Error loading captures:', error);
}
}
function renderMarkers() {
// Clear existing markers
markerClusterGroup.clearLayers();
markerLayer.clearLayers();
// Get frequency filter
const frequencyFilter = document.getElementById('frequency-filter').value;
// Filter captures
let filtered = capturesData;
if (frequencyFilter) {
const targetFreq = parseInt(frequencyFilter) * 1e6;
filtered = capturesData.filter(c => {
const freq = c.frequency / 1e6;
return Math.abs(freq - parseInt(frequencyFilter)) < 50;
});
}
// Create markers
filtered.forEach(capture => {
const marker = createMarker(capture);
// Add to both layers (only one will be visible)
markerClusterGroup.addLayer(marker);
markerLayer.addLayer(marker);
});
// Update count
document.getElementById('total-captures').textContent = filtered.length;
}
function createMarker(capture) {
// Determine color based on frequency
const freqMHz = Math.round(capture.frequency / 1e6);
let color = FREQUENCY_COLORS.default;
for (const [freq, col] of Object.entries(FREQUENCY_COLORS)) {
if (freq === 'default') continue;
if (Math.abs(freqMHz - parseInt(freq)) < 50) {
color = col;
break;
}
}
// Create custom icon
const icon = L.divIcon({
className: 'custom-marker',
html: `<div style="background-color: ${color}; width: 12px; height: 12px; border-radius: 50%; border: 2px solid white; box-shadow: 0 0 4px rgba(0,0,0,0.3);"></div>`,
iconSize: [12, 12],
iconAnchor: [6, 6]
});
// Create marker
const marker = L.marker([capture.latitude, capture.longitude], { icon });
// Create popup
const popupContent = createPopupContent(capture);
marker.bindPopup(popupContent);
return marker;
}
function createPopupContent(capture) {
const freqMHz = (capture.frequency / 1e6).toFixed(2);
const date = new Date(capture.captured_at).toLocaleDateString();
let deviceInfo = 'Unknown Device';
if (capture.device_name) {
deviceInfo = `<strong>${capture.device_name}</strong>`;
if (capture.match_confidence) {
deviceInfo += ` (${(capture.match_confidence * 100).toFixed(0)}% confidence)`;
}
}
return `
<div class="marker-popup">
<h4>${deviceInfo}</h4>
<p><strong>Frequency:</strong> ${freqMHz} MHz</p>
<p><strong>Protocol:</strong> ${capture.protocol || 'RAW'}</p>
<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.id})" class="btn btn-primary" style="margin-top: 0.5rem;">
View Details
</button>
</div>
`;
}
function updateStats() {
// Total captures
document.getElementById('total-captures').textContent = capturesData.length;
// Unique devices
const uniqueDevices = new Set(
capturesData
.filter(c => c.device_name)
.map(c => c.device_name)
).size;
document.getElementById('unique-devices').textContent = uniqueDevices;
}
// Export for external use
window.reloadMapData = loadCaptures;