Even high-quality sensors can produce inaccurate readings if they are not calibrated properly. Calibration aligns sensor output with real-world values and is essential for reliable measurements.
This article explains practical calibration techniques for common sensor types used in Arduino and ESP32 projects.
What Is Calibration?
Calibration is the process of adjusting a sensor’s output to match a known reference.
- Corrects offset errors
- Improves measurement accuracy
- Compensates for sensor variation
Many sensors are factory calibrated, but real-world conditions often require additional adjustments.
Offset Calibration (Simple Correction)
The simplest method is offset correction:
- Measure a known reference value
- Calculate the difference
- Add or subtract this offset in software
Example:
- Sensor reads 26°C while actual temperature is 25°C
- Apply -1°C correction
This method is easy and effective for many applications.
Two-Point Calibration
Two-point calibration improves accuracy over a range:
- Measure at two known reference points
- Calculate slope and offset
Example:
- 0°C and 50°C reference points
- Adjust scaling accordingly
This corrects both offset and scaling errors.
Sensor-Specific Calibration Methods
Temperature Sensors
- Use a reliable thermometer as reference
- Apply offset or two-point correction
Humidity Sensors
- Use controlled environments (e.g. sealed containers)
- Compare against reference sensors
Soil Moisture Sensors
- Calibrate using dry and wet soil
- Map readings to moisture percentage
Gas Sensors (MQ Series)
- Require baseline calibration
- Measure in clean air for reference
- Use relative changes rather than absolute values
Light Sensors
- Use known light sources
- Adjust scaling based on expected range
Environmental Compensation
Some sensors are affected by environmental factors:
- Temperature affects humidity sensors
- Pressure sensors depend on altitude
Modern sensors often include compensation internally, but external calibration can still improve results.
Averaging and Filtering
Noise can affect calibration accuracy:
- Average multiple readings
- Use filtering to stabilize values
This improves repeatability but does not replace calibration.
Storing Calibration Data
Calibration values should be stored for reuse:
- In microcontroller memory (EEPROM / flash)
- In configuration files
This avoids recalibration after every restart.
Comparison Overview
| Method | Complexity | Accuracy Improvement | Use Case |
|---|---|---|---|
| Offset | Low | Moderate | Simple correction |
| Two-point | Medium | High | Improved accuracy |
| Multi-point | High | Very high | Precision systems |
Common Mistakes
- Skipping calibration entirely
- Using unreliable reference values
- Ignoring environmental effects
Practical Recommendations
- Use offset calibration for simple projects
- Use two-point calibration for better accuracy
- Focus on repeatability rather than perfect accuracy
Conclusion
Calibration is essential for obtaining meaningful sensor data. Even simple calibration techniques can significantly improve accuracy and reliability.
Understanding your sensor and applying appropriate calibration methods ensures consistent and trustworthy results.