- E-LEARNING PROJECTS
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Digital Signal Processing Interactive Lab
Objective
To develop an interactive platform that allows engineering students to perform digital signal processing experiments online, including signal generation, filtering, and transformation, with real-time visualization of signals and frequency-domain analysis.
Key Features
Student Panel:
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Generate and visualize discrete-time signals (sine, square, triangular, sawtooth)
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Apply DSP techniques such as convolution, correlation, FFT, IFFT, and filtering
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Visualize time-domain and frequency-domain representations in real-time
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Adjust signal parameters (amplitude, frequency, phase) dynamically
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Save experiments and export plots for reports
Teacher Panel:
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Create or upload DSP experiments for students
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Assign tasks and monitor student activity and results
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Provide feedback and guidance on signal analysis
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Upload reference signals and expected outputs for comparison
Admin Panel:
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Manage users (students & teachers)
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Monitor system performance and active sessions
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Add new DSP modules, signal types, or filters
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View analytics on usage patterns and student engagement
Tech Stack
| Layer | Technologies |
|---|---|
| Frontend | React.js / Angular / Vue.js, D3.js / Plotly.js (for graphs) |
| Backend | Node.js + Express / Django / Python Flask |
| DSP Engine | Python (NumPy, SciPy, Matplotlib) / MATLAB Engine API / JavaScript DSP libraries |
| Database | MongoDB / PostgreSQL / Firebase |
| Authentication | JWT / OAuth 2.0 |
| Hosting | AWS / Heroku / Vercel / Firebase |
Workflow (Step-by-Step)
1. User Registration & Login
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Students and teachers register/login securely
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Access DSP lab dashboard with available experiments
2. Experiment Selection
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Select experiment type: signal generation, filtering, convolution, FFT, etc.
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Adjust input parameters: amplitude, frequency, phase, sampling rate
3. Real-Time Signal Processing
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Generate signals and apply DSP techniques
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Observe real-time visualizations in time-domain and frequency-domain
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Apply filters and transformations dynamically
4. Data Collection & Reporting
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Save simulation results and visualizations
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Export plots and data for reports or submission
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Teachers review student experiments and provide feedback
5. Analytics & Progress Tracking
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Track student engagement and completed experiments
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Generate reports for instructors on accuracy and parameter variations
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Identify common mistakes or learning gaps