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Home knowledges What is a sensor?

What is a sensor?

A sensor is a device that produces an output signal for the purpose of sensing a physical phenomenon.

In the broadest definition, a sensor is a device, module, machine, or subsystem that detects events or changes in its environment and sends the information to other electronics, frequently a computer processor. Sensors are always used with other electronics.

Sensors are used in everyday objects such as touch-sensitive elevator buttons (tactile sensor) and lamps which dim or brighten by touching the base, and in innumerable applications of which most people are never aware. With advances in micromachinery and easy-to-use microcontroller platforms, the uses of sensors have expanded beyond the traditional fields of temperature, pressure and flow measurement,for example into MARG sensors.

Analog sensors such as potentiometers and force-sensing resistors are still widely used. Their applications include manufacturing and machinery, airplanes and aerospace, cars, medicine, robotics and many other aspects of our day-to-day life. There is a wide range of other sensors that measure chemical and physical properties of materials, including optical sensors for refractive index measurement, vibrational sensors for fluid viscosity measurement, and electro-chemical sensors for monitoring pH of fluids.

A sensor's sensitivity indicates how much its output changes when the input quantity it measures changes. For instance, if the mercury in a thermometer moves 1  cm when the temperature changes by 1 °C, its sensitivity is 1 cm/°C (it is basically the slope dy/dx assuming a linear characteristic). Some sensors can also affect what they measure; for instance, a room temperature thermometer inserted into a hot cup of liquid cools the liquid while the liquid heats the thermometer. Sensors are usually designed to have a small effect on what is measured; making the sensor smaller often improves this and may introduce other advantages.

Technological progress allows more and more sensors to be manufactured on a microscopic scale as microsensors using MEMS technology. In most cases, a microsensor reaches a significantly faster measurement time and higher sensitivity compared with macroscopic approaches.Due to the increasing demand for rapid, affordable and reliable information in today's world, disposable sensors—low-cost and easy‐to‐use devices for short‐term monitoring or single‐shot measurements—have recently gained growing importance. Using this class of sensors, critical analytical information can be obtained by anyone, anywhere and at any time, without the need for recalibration and worrying about contamination.

Classification of measurement errors

An infrared sensor

A good sensor obeys the following rules:

  • it is sensitive to the measured property
  • it is insensitive to any other property likely to be encountered in its application, and
  • it does not influence the measured property.

Most sensors have a linear transfer function. The sensitivity is then defined as the ratio between the output signal and measured property. For example, if a sensor measures temperature and has a voltage output, the sensitivity is constant with the units [V/K]. The sensitivity is the slope of the transfer function. Converting the sensor's electrical output (for example V) to the measured units (for example K) requires dividing the electrical output by the slope (or multiplying by its reciprocal). In addition, an offset is frequently added or subtracted. For example, −40 must be added to the output if 0 V output corresponds to −40 C input.

For an analog sensor signal to be processed or used in digital equipment, it needs to be converted to a digital signal, using an analog-to-digital converter.

Sensor deviations

Since sensors cannot replicate an ideal transfer function, several types of deviations can occur which limit sensor accuracy:

Since the range of the output signal is always limited, the output signal will eventually reach a minimum or maximum when the measured property exceeds the limits. The full scale range defines the maximum and minimum values of the measured property.[citation needed]

The sensitivity may in practice differ from the value specified. This is called a sensitivity error. This is an error in the slope of a linear transfer function.

If the output signal differs from the correct value by a constant, the sensor has an offset error or bias. This is an error in the y-intercept of a linear transfer function.

Nonlinearity is deviation of a sensor's transfer function from a straight line transfer function. Usually, this is defined by the amount the output differs from ideal behavior over the full range of the sensor, often noted as a percentage of the full range.

Deviation caused by rapid changes of the measured property over time is a dynamic error. Often, this behavior is described with a bode plot showing sensitivity error and phase shift as a function of the frequency of a periodic input signal.

If the output signal slowly changes independent of the measured property, this is defined as drift. Long term drift over months or years is caused by physical changes in the sensor.

Noise is a random deviation of the signal that varies in time.

A hysteresis error causes the output value to vary depending on the previous input values. If a sensor's output is different depending on whether a specific input value was reached by increasing vs. decreasing the input, then the sensor has a hysteresis error.

If the sensor has a digital output, the output is essentially an approximation of the measured property. This error is also called quantization error.

If the signal is monitored digitally, the sampling frequency can cause a dynamic error, or if the input variable or added noise changes periodically at a frequency near a multiple of the sampling rate, aliasing errors may occur.

The sensor may to some extent be sensitive to properties other than the property being measured. For example, most sensors are influenced by the temperature of their environment.

All these deviations can be classified as systematic errors or random errors. Systematic errors can sometimes be compensated for by means of some kind of calibration strategy. Noise is a random error that can be reduced by signal processing, such as filtering, usually at the expense of the dynamic behavior of the sensor.


The sensor resolution or measurement resolution is the smallest change that can be detected in the quantity that it is being measured. The resolution of a sensor with a digital output is usually the numerical resolution of the digital output. The resolution is related to the precision with which the measurement is made, but they are not the same thing. A sensor's accuracy may be considerably worse than its resolution.

For example, the distance resolution is the minimum distance that can be accurately measured by any distance measuring devices. In a time-of-flight camera, the distance resolution is usually equal to the standard deviation (total noise) of the signal expressed in unit of length.

The sensor may to some extent be sensitive to properties other than the property being measured. For example, most sensors are influenced by the temperature of their environment.