549  Sensor Interfacing and Processing

Complete Guide to IoT Sensor Integration

sensing
protocols
data-processing
power-management
Author

IoT Textbook

Published

January 19, 2026

Keywords

sensor interfacing, I2C, SPI, calibration, filtering, power management, IoT sensors

549.1 Overview

This section covers the complete sensor integration pipeline for IoT systems, from physical communication protocols to data processing and real-world applications. The content is organized into focused chapters that build progressively from fundamentals to advanced techniques.

TipFor Beginners: What is Sensor Interfacing?

Sensor interfacing is the art of connecting physical sensors to your microcontroller and making sense of the data they produce. Just like learning a new language, you need to understand how sensors β€œspeak” (protocols like I2C and SPI), how to clean up their β€œaccent” (filtering noise), and how to translate their words into useful information (calibration). This section teaches all these skills through practical examples.

549.2 Chapter Overview

This comprehensive topic has been organized into five focused chapters:

549.2.1 1. Sensor Communication Protocols

Focus: I2C, SPI, and UART interfaces for connecting sensors to microcontrollers.

Topics Covered:

  • I2C two-wire bus protocol with 7-bit addressing
  • SPI four-wire full-duplex high-speed interface
  • Protocol selection decision tree
  • Common pitfalls: pull-up resistors, SPI mode configuration
  • Interactive I2C bus scanner demonstration

Estimated Time: 30 minutes

549.2.2 2. Sensor Data Processing

Focus: Filtering techniques and calibration procedures for accurate measurements.

Topics Covered:

  • Moving average filters for noise reduction
  • Kalman filters for optimal state estimation
  • Median filters for spike/outlier removal
  • Two-point calibration for offset and gain correction
  • Multi-point calibration for non-linear sensors
  • Worked example: Calibrating a soil moisture sensor

Estimated Time: 45 minutes

549.2.3 3. Sensor Networks and Power Management

Focus: Multi-sensor aggregation and battery optimization strategies.

Topics Covered:

  • Multi-sensor data aggregation with JSON payloads
  • Deep sleep modes for microamp-level consumption
  • Power budget calculations for battery life estimation
  • Transmission buffering for 3x+ battery life extension
  • Sensor fusion tradeoffs: complementary vs Kalman filters
  • Wake source configuration pitfalls

Estimated Time: 40 minutes

549.2.4 4. Sensor Applications

Focus: Real-world IoT implementation examples with complete code.

Topics Covered:

  • Smart home environmental monitoring with MQTT
  • Servo-controlled automated blinds
  • Temperature-controlled relay switching with hysteresis
  • Sensor selection guide for common applications
  • Practice exercises for hands-on learning

Estimated Time: 45 minutes

549.2.5 5. Sensor Calibration Lab

Focus: Hands-on Wokwi workshop for calibration techniques.

Topics Covered:

  • Interactive browser-based calibration lab
  • Two-point calibration procedure step-by-step
  • Moving average filter implementation
  • EEPROM storage for calibration persistence
  • Challenge exercises: three-point calibration, drift compensation

Estimated Time: 60 minutes (hands-on)

549.3 Learning Path

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flowchart LR
    A[Communication<br/>Protocols] --> B[Data<br/>Processing]
    B --> C[Power<br/>Management]
    C --> D[Applications]
    D --> E[Calibration<br/>Lab]

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    style E fill:#16A085,stroke:#2C3E50,color:#fff

Figure 549.1: Recommended learning path through sensor interfacing topics

Recommended Order:

  1. Start with Communication Protocols to understand how sensors connect
  2. Move to Data Processing for filtering and calibration theory
  3. Study Power Management for battery-powered deployments
  4. Apply knowledge with Applications examples
  5. Solidify skills with the hands-on Calibration Lab

549.4 Key Concepts Summary

Concept Chapter Description
I2C Protocol Protocols Two-wire bus, 7-bit addressing, multi-device support
SPI Protocol Protocols Four-wire full-duplex, high-speed data transfer
Moving Average Processing Noise reduction through sample averaging
Kalman Filter Processing Optimal adaptive state estimation
Two-Point Calibration Processing Offset and gain correction
Deep Sleep Power Microamp-level power consumption
Transmission Buffering Power Batch transmissions for battery savings
Hysteresis Control Applications Prevent rapid switching in control systems

549.5 Prerequisites

Before starting this section, you should be familiar with:

  • Basic Arduino/C++ programming
  • Digital I/O and analog inputs
  • Serial communication concepts
  • Sensor Fundamentals chapter content

549.6 What You Will Build

By completing all chapters, you will have the skills to:

  • Interface any I2C or SPI sensor with an ESP32 or Arduino
  • Remove noise from sensor readings using appropriate filters
  • Calibrate sensors for production-quality accuracy
  • Design battery-powered sensor nodes lasting months to years
  • Build complete sensor-to-cloud IoT applications

549.7 Quick Reference

Common I2C Addresses:

Sensor Address Alternate
BMP280 0x76 0x77
BME280 0x76 0x77
MPU6050 0x68 0x69
BH1750 0x23 0x5C
SSD1306 0x3C 0x3D

Power Consumption Typical Values:

State ESP32 ESP8266
Active + Wi-Fi 150-200 mA 70-80 mA
Deep Sleep 10 uA 20 uA
Light Sleep 800 uA 1 mA

Filter Selection Guide:

Noise Type Recommended Filter
Gaussian (random) Moving Average
Spikes/Outliers Median
Tracking motion Kalman
Fast response needed EMA (alpha=0.1-0.3)

Sensing Deep Dives:

Data Processing:

Architecture:

Learning Hubs: