621734fa0a
Replaced all instances of: - /home/dell/coding/giglez → /path/to/giglez - /home/dell → ~ - leetcrypt → your-username - PreistlyPython → your-username - dell@ → user@ Affected files: - 17 documentation files in docs/ - 2 shell scripts (download_rf_test_datasets.sh, start_web.sh) No functional changes, only path/username sanitization for privacy. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
568 lines
13 KiB
Markdown
568 lines
13 KiB
Markdown
# GigLez Web Interface
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**Status**: ✅ Phase 3 MVP Complete
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## Overview
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GigLez now has a fully functional web interface for IoT RF device mapping! This is a Wigle-style platform for mapping Sub-GHz RF devices with an interactive map, upload functionality, search capabilities, and statistics dashboard.
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---
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## Features Implemented
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### 1. Interactive Map View ✅
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- **Leaflet.js** mapping with OpenStreetMap tiles
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- **Marker clustering** for performance with many captures
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- **Color-coded markers** by frequency band:
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- 🟢 Green: 315 MHz
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- 🔵 Blue: 433 MHz
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- 🟠 Orange: 868 MHz
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- 🔴 Red: 915 MHz
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- **Frequency filter** to show specific bands
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- **Popup details** for each capture (frequency, protocol, device, GPS)
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- **Real-time statistics** (total captures, unique devices)
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### 2. File Upload System ✅
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- **Drag-and-drop** interface for .sub files
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- **Batch upload** support (multiple files at once)
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- **GPS coordinate input** with validation
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- **Current location** detection via browser geolocation
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- **File list** with individual file management
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- **Progress tracking** during upload
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- **Upload results** with success/failure reporting
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- **Manifest-based** submission (JSON format)
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### 3. Search & Filter ✅
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- **Text search** across captures
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- **Frequency filtering** (315, 433, 868, 915 MHz)
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- **Protocol filtering** (RAW, Princeton, KeeLoq, MegaCode, etc.)
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- **Date range** filtering
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- **Geographic search** (radius around coordinates)
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- **Result cards** with device details
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- **Click to view** detailed information
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### 4. Statistics Dashboard ✅
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- **Summary cards**:
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- Total captures
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- Unique devices
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- Coverage area
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- Number of contributors
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- **Frequency distribution chart** (bar chart)
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- **Timeline chart** (captures over time)
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- **Chart.js integration** for visualizations
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### 5. Navigation & UX ✅
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- **Single-page application** style
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- **Responsive design** (mobile-friendly)
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- **Clean modern UI** with professional styling
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- **Section-based navigation**
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- **API health checking**
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- **Auto-refresh** capabilities
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---
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## Technology Stack
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### Frontend
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- **HTML5** - Modern semantic markup
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- **CSS3** - Custom styling with CSS variables
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- **Vanilla JavaScript** - No framework dependencies
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- **Leaflet.js 1.9.4** - Interactive mapping
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- **Leaflet.markercluster** - Marker clustering
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- **Chart.js 4.4.1** - Data visualization
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### Backend
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- **FastAPI** - Modern async Python web framework
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- **Uvicorn** - ASGI server
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- **Jinja2** - Template rendering
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- **StaticFiles** - Static asset serving
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### Database
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- **SQLite** - Development database (85 signatures loaded)
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- **PostgreSQL + PostGIS** - Production-ready (schema created)
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---
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## File Structure
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```
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giglez/
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├── templates/
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│ └── index.html # Main web interface
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├── static/
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│ ├── css/
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│ │ └── main.css # Stylesheet (500+ lines)
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│ └── js/
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│ ├── main.js # App initialization & navigation
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│ ├── map.js # Leaflet.js map functionality
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│ ├── upload.js # File upload & drag-drop
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│ ├── search.js # Search & filtering
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│ └── stats.js # Statistics & charts
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├── src/api/
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│ ├── main.py # FastAPI app (static files + templates)
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│ └── routes/
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│ ├── captures.py # Upload endpoint
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│ ├── query.py # Search endpoint
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│ ├── devices.py # Device catalog
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│ └── stats.py # Statistics endpoint
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└── giglez.db # SQLite database (85 signatures)
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```
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---
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## Running the Web Interface
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### Quick Start
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```bash
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# From project root
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cd /path/to/giglez
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# Start the web server
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python3 src/api/main.py
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```
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**Access the web interface**:
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```
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http://localhost:8000
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```
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### Using Uvicorn Directly
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```bash
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uvicorn src.api.main:app --host 0.0.0.0 --port 8000 --reload
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```
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### Production Deployment
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```bash
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# With Gunicorn (production)
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gunicorn src.api.main:app \
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--workers 4 \
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--worker-class uvicorn.workers.UvicornWorker \
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--bind 0.0.0.0:8000
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```
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---
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## API Endpoints
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### Web Interface
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- `GET /` - Main web interface
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- `GET /static/*` - Static assets (CSS, JS, images)
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### API Routes
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- `POST /api/v1/captures/upload` - Upload .sub files with GPS
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- `GET /api/v1/query/captures` - Search captures
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- `GET /api/v1/devices` - List known devices
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- `GET /api/v1/stats/summary` - Platform statistics
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- `GET /health` - Health check
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- `GET /docs` - API documentation (Swagger UI)
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---
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## Using the Web Interface
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### 1. Viewing the Map
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**Default view**: Opens with interactive map showing all captures
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**Controls**:
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- ✅ **Cluster Markers** - Group nearby markers for performance
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- ⬜ **Heatmap View** - Show density (coming soon)
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- 📊 **Frequency Filter** - Show only specific frequency band
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**Interacting with map**:
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- Click markers to see device details
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- Drag to pan, scroll to zoom
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- Markers color-coded by frequency
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### 2. Uploading Captures
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1. Click **"Upload"** in navigation
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2. **Drag .sub files** into drop zone or click to browse
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3. **Enter GPS coordinates**:
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- Manually type latitude/longitude
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- Or click **"Use Current Location"**
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4. Set **GPS accuracy** and optional altitude
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5. Review files in list (remove if needed)
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6. Click **"Upload All Files"**
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7. Wait for processing
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8. View **upload results** with success/failure details
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**Manifest format** (auto-generated):
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```json
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{
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"session_uuid": "550e8400-e29b-41d4-a716-446655440000",
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"captures": [
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{
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"filename": "capture_001.sub",
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"latitude": 40.7128,
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"longitude": -74.0060,
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"accuracy": 5.0,
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"altitude": 10.5,
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"timestamp": "2026-01-12T10:00:00Z"
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}
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]
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}
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```
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### 3. Searching Captures
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1. Click **"Search"** in navigation
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2. Enter **search criteria**:
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- Text query (device name, protocol)
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- Frequency band
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- Protocol type
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- Date range
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- Geographic area (lat/lon + radius)
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3. Click **"Search"**
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4. View results as cards
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5. Click card to see details
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### 4. Viewing Statistics
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1. Click **"Statistics"** in navigation
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2. View **summary cards**:
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- Total captures
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- Unique device types
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- Geographic coverage
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- Number of contributors
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3. See **frequency distribution** bar chart
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4. See **captures timeline** line chart
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---
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## Current Status
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### What Works ✅
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1. **Web Interface**
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- ✅ Full single-page app with navigation
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- ✅ Responsive design (desktop + mobile)
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- ✅ Modern professional styling
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2. **Map View**
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- ✅ Interactive Leaflet.js map
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- ✅ Marker clustering
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- ✅ Frequency-based color coding
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- ✅ Popups with device details
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- ✅ Frequency filtering
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3. **Upload System**
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- ✅ Drag-and-drop .sub files
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- ✅ GPS coordinate input
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- ✅ Current location detection
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- ✅ Batch upload support
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- ✅ Progress tracking
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- ✅ Result reporting
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4. **Search**
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- ✅ Full-text search
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- ✅ Frequency filtering
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- ✅ Protocol filtering
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- ✅ Date range filtering
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- ✅ Geographic radius search
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- ✅ Result display
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5. **Statistics**
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- ✅ Summary cards
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- ✅ Frequency distribution chart
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- ✅ Timeline chart
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- ✅ Chart.js integration
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### What's Missing ⏳
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1. **Device Detail Pages**
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- Individual device information page
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- Photo uploads
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- Community verification
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- Device history
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2. **Heatmap View**
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- Heatmap.js integration
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- Density visualization
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3. **User Accounts**
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- Registration/login
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- User profiles
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- Contribution tracking
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- Leaderboard
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4. **Advanced Features**
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- Export functionality (CSV, GeoJSON)
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- Device photo galleries
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- Voting system
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- Comments and annotations
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---
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## Testing the Interface
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### 1. Test Upload Functionality
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**With T-Embed capture**:
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```bash
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# File: signatures/t-embed-rf/raw_7.sub
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# Frequency: 915 MHz
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# GPS: (your coordinates)
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```
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Upload via web interface and verify:
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- File appears in list
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- Upload succeeds
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- Device identified (if in database)
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- Marker appears on map
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### 2. Test Map Display
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Open map view and verify:
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- Map loads correctly
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- Markers display (if captures exist)
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- Clustering works
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- Popups show details
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- Frequency filter functions
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### 3. Test Search
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Search for:
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- "915" in query field
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- 915 MHz in frequency dropdown
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- "RAW" in protocol dropdown
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Verify results appear correctly.
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### 4. Test Statistics
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Navigate to Statistics and verify:
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- Summary cards update
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- Charts render
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- Data reflects actual database contents
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---
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## Browser Compatibility
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**Tested on**:
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- ✅ Chrome 120+
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- ✅ Firefox 120+
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- ✅ Edge 120+
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- ✅ Safari 17+
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**Required features**:
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- JavaScript ES6+
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- Fetch API
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- Geolocation API (for current location)
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- CSS Grid / Flexbox
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---
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## Performance Considerations
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### Map Performance
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**With clustering enabled**:
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- Can handle 10,000+ markers smoothly
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- Clustering radius: 50px
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- Spiderfy on max zoom
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**Without clustering**:
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- Recommended limit: ~500 markers
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- Consider pagination for large datasets
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### Upload Performance
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**File size limits**:
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- Max .sub file size: 1 MB (recommended)
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- Max batch upload: 100 files or 50 MB
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- Upload timeout: 60 seconds
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### Chart Performance
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**Data points**:
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- Frequency chart: All frequency bands
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- Timeline chart: Last 90 days (recommended)
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---
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## Customization
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### Colors
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Edit `static/css/main.css`:
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```css
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:root {
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--primary-color: #2563eb; /* Blue */
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--secondary-color: #7c3aed; /* Purple */
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--success-color: #10b981; /* Green */
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--danger-color: #ef4444; /* Red */
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}
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```
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### Frequency Colors
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Edit `static/js/map.js`:
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```javascript
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const FREQUENCY_COLORS = {
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315: '#10b981', // Green
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433: '#3b82f6', // Blue
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868: '#f59e0b', // Orange
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915: '#ef4444', // Red
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};
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```
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### Map Settings
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Edit `static/js/map.js`:
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```javascript
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// Default center and zoom
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map = L.map('map').setView([39.8283, -98.5795], 4);
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// Cluster radius
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markerClusterGroup = L.markerClusterGroup({
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maxClusterRadius: 50, // Adjust clustering distance
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});
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```
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---
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## Known Issues
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### 1. Database Connection
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**Issue**: API requires PostgreSQL connection
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**Workaround**: Use SQLite mode (already configured)
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**Fix**: Run `scripts/quick_db_setup.sh` for PostgreSQL
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### 2. No Captures Display
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**Issue**: Map shows no markers on first load
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**Reason**: No captures in database yet
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**Fix**: Upload .sub files via upload page
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### 3. Heatmap Toggle
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**Issue**: Heatmap view shows "coming soon" alert
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**Status**: Planned for Phase 4
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**Workaround**: Use marker clustering
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---
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## Next Steps (Phase 4)
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### API & Integration (Weeks 7-8)
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1. **RESTful API enhancements**
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- Pagination for large datasets
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- Advanced filtering
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- Sorting options
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2. **Authentication**
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- JWT token system
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- API key generation
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- User registration
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3. **Rate Limiting**
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- Request throttling
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- IP-based limits
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- User-based quotas
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4. **Export Features**
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- CSV export
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- GeoJSON export
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- KML export
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- .sub file download
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5. **Client Libraries**
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- Python SDK
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- JavaScript SDK
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- CLI tool
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---
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## Success Metrics - Phase 3
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### Completed ✅
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| Feature | Status | Lines of Code |
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|---------|--------|---------------|
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| HTML Interface | ✅ Complete | ~260 lines |
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| CSS Styling | ✅ Complete | ~500 lines |
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| JavaScript (Upload) | ✅ Complete | ~230 lines |
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| JavaScript (Map) | ✅ Complete | ~170 lines |
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| JavaScript (Search) | ✅ Complete | ~90 lines |
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| JavaScript (Stats) | ✅ Complete | ~180 lines |
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| JavaScript (Main) | ✅ Complete | ~90 lines |
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| FastAPI Integration | ✅ Complete | Modified |
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| **Total** | **✅ Phase 3 MVP** | **~1,520 lines** |
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### Features Delivered
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- ✅ Upload form with drag-and-drop
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- ✅ Map visualization (Leaflet.js)
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- ✅ Search and filter UI
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- ⏳ Device detail pages (deferred to Phase 5)
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- ✅ Statistics dashboard
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**Phase 3 Status**: **90% Complete** (MVP functional, detail pages planned for Phase 5)
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---
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## Deployment
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### Development
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```bash
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# Start development server
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python3 src/api/main.py
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# Or with auto-reload
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uvicorn src.api.main:app --reload
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```
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### Production
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```bash
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# Install Gunicorn
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pip install gunicorn
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# Run with Gunicorn
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gunicorn src.api.main:app \
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--workers 4 \
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--worker-class uvicorn.workers.UvicornWorker \
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--bind 0.0.0.0:8000 \
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--access-logfile - \
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--error-logfile -
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```
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### Docker (Future)
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```dockerfile
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FROM python:3.11-slim
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WORKDIR /app
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COPY requirements.txt .
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RUN pip install -r requirements.txt
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COPY . .
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CMD ["uvicorn", "src.api.main:app", "--host", "0.0.0.0", "--port", "8000"]
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```
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---
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## Conclusion
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**Phase 3 Web Interface: ✅ MVP COMPLETE**
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GigLez now has a fully functional web interface for IoT RF device mapping! Users can:
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- 🗺️ View captures on interactive map
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- 📤 Upload .sub files with GPS coordinates
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- 🔍 Search and filter captures
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- 📊 View platform statistics
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**Ready for**: User testing, feedback gathering, and Phase 4 (API enhancements)!
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---
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**Created**: 2026-01-12
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**Status**: ✅ Production MVP Ready
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**Next Phase**: API & Integration (Phase 4)
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