Assessfy Pvt. Ltd Moderate 5 milestones 100 marks

Software-Defined Radio (SDR)-Based Spectrum Analyzer

Target year: TE Sem 5-6 (Mini-Project-IIA/IIB) AICTE: 3 credits · ~75 hrs Bloom: Analyze MU CBCS: ETC601/ETC701 Mini-Project 2A/2B

Real-world project · AICTE-aligned · AI-graded · Audit-ready certificate

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Milestones

Available mentors

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Core skills

About this project

Use a cheap RTL-SDR dongle + GNU Radio + Python to build a real-time spectrum analyzer that scans 24 MHz to 1.7 GHz, identifies known transmissions (FM broadcast, ADS-B, GSM control channels), and visualizes them in a Streamlit dashboard.

Course Learning Outcomes (CLOs):
CLO1: Apply DSP fundamentals to wideband sampled signals.
CLO2: Build GNU Radio flowgraphs for live RF capture + processing.
CLO3: Implement an FFT-based spectrum analyzer in Python.
CLO4: Identify and classify known RF signals visually + algorithmically.
CLO5: Build a usable real-time dashboard for end users.

Industry/societal relevance: SDR is the basis of 5G + IoT communication systems; direct preparation for jobs at Reliance Jio, Nokia India, Ericsson, Tata Elxsi.

Milestones

1. SDR Setup + GNU Radio Hello-World

15 marks 7d

Install RTL-SDR drivers + GNU Radio. Capture FM broadcast around 91.1 MHz, demodulate to audio. Submit screen recording.

2. Wideband FFT Capture

20 marks 12d

Python script using pyrtlsdr: capture I/Q samples across a band, FFT, plot waterfall. Save to .npy file.

3. Multi-Band Scan

20 marks 14d

Sweep 24-1700 MHz in 2MHz chunks, stitch into a panoramic spectrum image. Save high-res PNG.

4. Signal Classification

25 marks 18d

Detect peaks above noise floor, classify by frequency: FM radio (88-108), aviation (118-137), GSM-900 (935-960), etc.

5. Streamlit Dashboard

20 marks 14d

Live updating dashboard: current spectrum, waterfall, detected stations list. Deploy on local server, demo video.

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Upcoming sessions

Session	Window	Enrolled
Software-Defined Radio (SDR)-Based Spectrum Analyzer	11 Jun 2026 to 10 Jun 2028	0

Skills you'll learn

Software-Defined Radio fundamentalsGNU Radio flowgraphsPython (NumPy / SciPy)DSP (FFTfilteringwindowing)Real-time data visualizationSignal classification

Tools used

RTL-SDR v3 dongleGNU Radio CompanionPython 3.11NumPySciPyStreamlitmatplotlibGitHub

Prerequisites

Communication Engineering I; Signals & Systems; Python intermediate; comfort with Linux

Available mentors

Priyang Kumar

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