👉 Sensor mathematics involves the use of mathematical models to interpret and process data collected by sensors, which are devices that detect and respond to physical phenomena. These models convert raw sensor readings into meaningful information by accounting for various factors such as noise, calibration errors, and environmental conditions. For instance, in temperature sensing, the raw voltage output from a thermistor is often converted using a calibration equation to determine the actual temperature. Similarly, in motion sensors, mathematical algorithms might filter out noise and accurately detect changes in position or velocity. The core of sensor mathematics includes linear and nonlinear transformations, signal processing techniques like filtering and Fourier transforms, and statistical methods to ensure accuracy and reliability in data interpretation.
