This project presents an AI-based Wi-Fi signal mapping system that analyzes Wi-Fi signal strength using RSSI (Received Signal Strength Indicator) values.
The system collects Wi-Fi signal information and displays it through a web-based dashboard. It helps identify weak-signal areas and provides intelligent recommendations for improving router placement.
- Measure Wi-Fi signal strength using RSSI values.
- Visualize Wi-Fi signal conditions through a web dashboard.
- Identify weak-signal and dead-zone areas.
- Monitor Wi-Fi signal variations.
- Provide router placement recommendations.
- Store and analyze Wi-Fi measurement data.
- 📶 Wi-Fi RSSI monitoring
- 📊 Signal strength visualization
- 🗺️ Wi-Fi signal mapping
- 🔴 Weak-signal area identification
- 🤖 Intelligent router placement recommendation
- 🌐 Flask-based web dashboard
- 📡 Automatic Wi-Fi measurement
- 💾 Local data storage using SQLite
The dashboard provides real-time visualization of Wi-Fi signal information, RSSI values, graphs, heatmap information, and recommendations.
The system architecture shows the flow from Wi-Fi signal collection through processing, storage, analysis, and dashboard visualization.
The flowchart represents the complete sequence of operations performed by the Wi-Fi signal mapping system.
The working methodology illustrates the three major stages: data collection, data processing, and visualization/output.
- ESP8266 / NodeMCU
- Wi-Fi-enabled computer/device
- Wi-Fi router
- Python
- Flask
- HTML
- CSS
- JavaScript
- SQLite
- Chart.js
Wi-Fi Signal
↓
RSSI Data Collection
↓
ESP8266 / Computer
↓
Python Processing
↓
Flask Backend
↓
Data Analysis
↓
Web Dashboard
↓
Signal Mapping
↓
Router Placement Recommendation