61 Signal Processing Essentials
61.1 Overview
Signal processing is fundamental to IoT systems—it bridges the gap between continuous physical phenomena and discrete digital data that computers can process. This series covers the complete signal processing pipeline from analog sensor output to digital transmission.
Total Reading Time: ~60 minutes | Lab Time: 60-90 minutes
61.2 Chapter Series
61.2.1 1. Signal Processing Overview
⏱️ ~20 min | ⭐ Foundational
What You’ll Learn: - Why analog-to-digital conversion is necessary - The Nyquist sampling theorem - How to choose appropriate sampling rates - Common pitfalls: oversampling waste vs undersampling aliasing
Key Topics: Analog vs digital signals, ADC pipeline, Nyquist theorem, sampling strategy
61.2.2 2. Aliasing and ADC Resolution
⏱️ ~15 min | ⭐⭐ Intermediate
What You’ll Learn: - How undersampling causes aliasing distortion - Calculating required ADC resolution - Selecting ADC parameters (8-bit, 10-bit, 12-bit, 16-bit) - Implementing digital filters (median, moving average, low-pass)
Key Topics: Aliasing prevention, quantization levels, filter selection, ADC trade-offs
61.2.3 3. Voice and Audio Compression
⏱️ ~14 min | ⭐⭐⭐ Advanced
What You’ll Learn: - Toll quality baseline (64 kbps) - Companding (μ-law and A-law) for better SNR - Linear Predictive Coding (LPC) for 8-27× compression - Practical codec selection for IoT applications
Key Topics: Voice compression, companding, source-filter model, codec comparison
61.2.4 4. Sensor Dynamics and Linearization
⏱️ ~15 min | ⭐⭐⭐ Advanced
What You’ll Learn: - Why sensors don’t respond instantly (mass-spring-damper model) - Understanding step response and bandwidth - Matching sampling rate to sensor bandwidth - Linearizing non-linear sensors (thermistors, LDRs)
Key Topics: Sensor dynamics, step response, bandwidth matching, linearization methods
61.2.5 5. Signal Processing Labs
⏱️ 60-90 min | ⭐⭐ Practical
What You’ll Do: - Configure ESP32 ADC with different resolutions - Compare median vs moving average filters - Perform FFT frequency analysis - Design multi-stage filter pipelines
Key Topics: Hands-on ESP32 simulation, practical filtering, FFT analysis, pipeline design
61.3 Learning Path Recommendations
61.3.1 Beginner Path
- Start with Overview - understand the basics
- Read Aliasing and ADC - grasp quantization
- Do Labs Exercise 1-2 - hands-on ADC and filtering
- Skip voice compression and sensor dynamics until needed
61.3.2 Standard Path
- Read all chapters in order (1-4)
- Complete all labs (chapter 5)
- Total time: ~3 hours including hands-on
61.3.3 Advanced Path
- Skim chapters 1-2 (review basics)
- Deep dive into chapters 3-4 (voice, sensor dynamics)
- Complete all labs
- Extend labs with custom projects
61.4 Prerequisites
Before starting this series, you should understand:
- Sensor Fundamentals: Types of sensors and their outputs
- Data Representation: Binary numbers and bit depth
- Basic electronics: Voltage, current, resistance (Ohm’s law)
61.6 Quick Reference: Key Formulas
Nyquist Theorem: \[f_s > 2 \times f_{max}\]
ADC Resolution: \[\text{Step Size} = \frac{V_{ref}}{2^{bits} - 1}\]
Voltage from ADC: \[V = \text{ADC Value} \times \frac{V_{ref}}{2^{bits} - 1}\]
Companding (μ-law): \[F(x) = \text{sgn}(x) \cdot \frac{\ln(1 + \mu |x|)}{\ln(1 + \mu)}\]
Sensor Bandwidth: \[BW = \frac{1}{2\pi\tau}\]
61.7 Chapter Statistics
| Chapter | Words | Reading Time | Difficulty | Lab Time |
|---|---|---|---|---|
| Overview | ~3,500 | 20 min | Foundational | - |
| Aliasing & ADC | ~2,800 | 15 min | Intermediate | - |
| Voice Compression | ~2,500 | 14 min | Advanced | - |
| Sensor Dynamics | ~2,000 | 15 min | Advanced | - |
| Labs | ~2,700 | 10 min | Practical | 60-90 min |
| Total | ~13,500 | 74 min | Mixed | 60-90 min |
61.8 Start Learning
Ready to begin? Start with Signal Processing Overview →