Spectrum Alert: AI-Powered RF Monitoring and Anomaly Detection for Ham Radio

As the RF spectrum grows increasingly congested, amateur radio operators and regulators need smarter tools to monitor, detect, and respond to suspicious activity. Spectrum Alert is an open-source software suite designed to meet that challenge head-on. It brings machine learning, RF fingerprinting, and multi-device triangulation to the fingertips of ham operators and spectrum regulators alike.

📡 What is Spectrum Alert?

Spectrum Alert is a Python-based toolkit that leverages RTL-SDR receivers and advanced analytics to monitor ham bands, detect illegal transmissions, and even triangulate the source of RF anomalies. Whether you’re a radio enthusiast, an emergency communications volunteer, or part of a regulatory body, this tool can transform your spectrum surveillance operations.

🛠 Key Features

• 📊 Real-Time Spectrum Monitoring: Continuously scans pre-configured ham bands and detects abnormal signal behavior.
• 🔬 RF Fingerprinting: Trains models to uniquely identify and differentiate between transmitters based on their signal features.
• 🤖 AI-Powered Anomaly Detection: Uses the Isolation Forest algorithm to catch unauthorized or suspicious transmissions.
• 🧠 Model Training & Automation: Automatically gathers IQ data, trains ML models, and monitors the spectrum—hands-free.
• 🌐 MQTT Integration: Publishes real-time alerts, signal strength, and anomalies for centralized or cloud-based monitoring.
• 📍 Direction Finding (DF): Deploy multiple Raspberry Pis or SDR devices in different locations to triangulate the origin of signals.
• 💡 Lightweight Versions: Optimized builds for low-resource environments like Raspberry Pi or headless servers.

⚙️ How It Works

You can run Spectrum Alert via a simple menu-based interface, with options to:

• Gather RF data
• Train AI models
• Start real-time spectrum monitoring
• Run a complete end-to-end process with a single command

If you already have IQ datasets or trained models, Spectrum Alert intelligently skips steps, saving you time.

📚 Real-World Use Cases

📍 Scenario 1: Neighborhood Spectrum Watch

Want to ensure no pirate stations are interfering with your net? Deploy a Raspberry Pi and RTL-SDR dongle at your shack, gather data, and begin scanning. Anomalies are logged and sent to an MQTT dashboard for real-time review.

🧠 Scenario 2: Fingerprint Rogue Devices

Track the same illegal transmitter appearing on different bands or days. RF fingerprinting lets you identify and flag persistent offenders.

📡 Scenario 3: Multi-Device Triangulation

Set up multiple Spectrum Alert instances across your city. When each node detects an anomaly, MQTT aggregates the data—letting you estimate the source via cross-correlation. This transforms Spectrum Alert into a lightweight direction-finding system.

🔥 Heatmaps and Insight

The software supports geospatial heatmaps of anomalies and suspected devices. Using MQTT reports from multiple nodes, you can visualize where suspicious transmissions occur most frequently—great for regulatory reporting, club initiatives, or contest integrity.

🧪 Installation Overview

✅ Requirements:

• Python 3.x
• RTL-SDR dongle
• Packages: numpy, scikit-learn, pyrtlsdr, paho-mqtt, joblib, etc.

🚀 Quick Install:

git clone https://github.com/Slayingripper/SpectrumAlert.git
cd SpectrumAlert
pip install numpy scikit-learn pyrtlsdr configparser paho-mqtt joblib

Then, plug in your RTL-SDR, edit Trainer/config.ini, and run the menu.

📈 What’s Next?

Spectrum Alert is still growing. Here’s what’s coming soon:

• Easy menu interface
• Support for non-RTL SDRs (e.g., HackRF, Airspy)
• GPS integration for better triangulation
• Web UI for real-time anomaly dashboards

🪪 License

Spectrum Alert is free software, licensed under GNU GPL v3. You’re encouraged to fork, improve, and collaborate. Contributions are welcome!

👉 GitHub: Slayingripper/SpectrumAlert

💬 Final Thoughts

Whether you’re running a ham club net or managing national RF compliance, Spectrum Alert brings modern, AI-powered monitoring to the amateur radio world. It’s smart, modular, and community-friendly—exactly what 21st-century hams need to protect our bands.