Evaluate the quality of a sensor
Evaluate the quality of a smartphone sensor
Author:
Title 4
Learning objectives :
This activity helps students understand the concepts of measurement precision and uncertainty. It develops critical thinking regarding measuring instruments and introduces the statistical analysis of data.
Concepts covered
Normal distribution; Measurement uncertainty; Standard deviation; Sensor accuracy; Statistical analysis
What students will do :
The student measures the absolute acceleration of a stationary smartphone for 20 seconds then studies the dispersion of the values obtained using FizziQ statistical tools. By analyzing the histogram of the data and calculating the standard deviation, the student evaluates the accuracy of the accelerometer and compares its results with those obtained on other smartphone models.
What is required :
Smartphone with the FizziQ application; Stable surface to place the smartphone; Possibly several smartphones of different models for comparison; FizziQ experience notebook; Optional: spreadsheet software for additional analysis
Scientific background :
The accelerometer of a smartphone at rest should theoretically measure a constant value (around 9.81 m/s² for absolute acceleration, due to gravity). In reality, measurements fluctuate slightly around this value due to several factors: electronic noise from the sensor, minute vibrations from the environment, and intrinsic resolution limits of the MEMS sensor. These fluctuations generally follow a normal (Gaussian) distribution, characterized by its mean μ and its standard deviation σ. The standard deviation quantifies the dispersion of measurements and is an excellent indicator of sensor accuracy: the lower σ, the more precise the sensor. FizziQ allows direct visualization of this distribution via the histogram of the measurements. For an ideal sensor, the curve should be narrow and centered on the actual value. In modern smartphones, accelerometers typically have an accuracy of ±0.01 to ±0.05 m/s², but this value varies between models and manufacturers. The quality of a sensor does not necessarily correlate with the price of the smartphone; some entry-level models may have excellent accelerometers. Other statistical indicators such as skewness and kurtosis can provide additional information on the nature of sensor errors. This experiment illustrates the fundamental concepts of metrology, the science of measurement, and shows the importance of critical evaluation of measuring instruments in experimental science.