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SDR-Shark

Hardware-free RF sensing demo with real software depth.

SDR-Shark is a browser-based software-defined radio console packaged as a public-safe Docker demo with synthetic IQ replay, Bluetooth-like frequency-hopping signal behavior, FFT, waterfall, and decoded signal activity workflows.

Portfolio proof

A repeatable SDR workflow reviewers can run without radio hardware.

The public demo generates deterministic synthetic IQ data locally, starts the SDR-Shark backend and frontend, activates replay, and exposes the same browser workflow used for spectrum visualization and signal review. It is designed for public portfolio review without committing real RF captures.

Run the public Docker demo in one command:

docker compose -f docker-compose.demo.yml up --build

What It Demonstrates

  • Stationary receiver view of a Bluetooth-like frequency-hopping emitter with replay-backed FFT, max-hold, persistence, and waterfall views
  • Scanner-oriented spectrum workflows and signal activity panels
  • Python backend APIs for IQ sessions, replay control, and live data
  • Docker packaging for one-command public demonstration
  • Integration points for RF classification and gateway-backed SDR deployments

Live interface

Browser-based spectrum, waterfall, and signal activity views.

SDR-Shark presents RF software as an operator-facing web application: spectrum traces, waterfall history, decoded activity cards, scanner configuration, settings dialogs, and analysis workflows are visible from the browser rather than hidden inside scripts or notebooks.

SDR-Shark public demo showing a Bluetooth-like frequency-hopping synthetic emitter in the spectrum and waterfall interface

Engineering scope

Where this applies.

SDR Prototyping

Prototype receive pipelines, scanner dwell plans, replay tools, dashboards, and integration glue for software-defined radio systems.

RF Data Products

Turn IQ streams, FFT products, detected activity, and metadata into reviewable interfaces and evidence artifacts.

RF/ML Integration

Prepare hooks for classifier workflows, feature extraction, model-backed labeling, and signal-family exploration.

Demo Packaging

Create deterministic, public-safe demonstrations that let stakeholders evaluate a working system without lab hardware.