Sensors in Internet of Things(IoT)
Generally, sensors are used in the architecture of IOT devices.
Sensors are used for sensing things and devices etc.
A device that provides a usable output in response to a specified measurement.
The sensor attains a physical parameter and converts it into a signal suitable for processing (e.g. electrical, mechanical, optical) the characteristics of any device or material to detect the presence of a particular physical quantity.
The output of the sensor is a signal which is converted to a human-readable form like changes in characteristics, changes in resistance, capacitance, impedance etc.
- A transducer converts a signal from one physical structure to another.
- It converts one type of energy into another type.
- It might be used as actuators in various systems.
Sensors characteristics :
1. Static characteristics :
It is about how the output of a sensor changes in response to an input change after steady state condition.
- Accuracy –
Accuracy is the capability of measuring instruments to give a result close to the true value of the measured quantity. It measures errors. It is measured by absolute and relative errors. Express the correctness of the output compared to a higher prior system. Absolute error = Measured value – True value
Relative error = Measured value/True value
- Range –
Gives the highest and the lowest value of the physical quantity within which the sensor can actually sense. Beyond these values, there is no sense or no kind of response.
e.g. RTD for measurement of temperature has a range of -200`c to 800`c.
- Resolution –
Resolution is an important specification towards selection of sensors. The higher the resolution, better the precision. When the accretion is zero to, it is called threshold.
Provide the smallest changes in the input that a sensor is able to sense.
- Precision –
It is the capacity of a measuring instrument to give the same reading when repetitively measuring the same quantity under the same prescribed conditions.
It implies agreement between successive readings, NOT closeness to the true value.
It is related to the variance of a set of measurements.
It is a necessary but not sufficient condition for accuracy.
- Sensitivity –
Sensitivity indicates the ratio of incremental change in the response of the system with respect to incremental change in input parameters. It can be found from the slope of the output characteristics curve of a sensor. It is the smallest amount of difference in quantity that will change the instrument’s reading.
- Linearity –
The deviation of the sensor value curve from a particular straight line. Linearity is determined by the calibration curve. The static calibration curve plots the output amplitude versus the input amplitude under static conditions.
A curve’s slope resemblance to a straight line describes the linearity.
- Drift –
The difference in the measurement of the sensor from a specific reading when kept at that value for a long period of time.
- Repeatability –
The deviation between measurements in a sequence under the same conditions. The measurements have to be made under a short enough time duration so as not to allow significant long-term drift.
Dynamic Characteristics :
Properties of the systems
- Zero-order system –
The output shows a response to the input signal with no delay. It does not include energy-storing elements.
Ex. potentiometer measure, linear and rotary displacements.
- First-order system –
When the output approaches its final value gradually.
Consists of an energy storage and dissipation element.
- Second-order system –
Complex output response. The output response of the sensor oscillates before steady state.
Sensor Classification :
- Passive & Active
- Analog & digital
- Scalar & vector
- Passive Sensor –
Can not independently sense the input. Ex- Accelerometer, soil moisture, water level and temperature sensors.
- Active Sensor –
Independently sense the input. Example- Radar, sounder and laser altimeter sensors.
- Analog Sensor –
The response or output of the sensor is some continuous function of its input parameter. Ex- Temperature sensor, LDR, analog pressure sensor and analog hall effect.
- Digital sensor –
Response in binary nature. Design to overcome the disadvantages of analog sensors. Along with the analog sensor, it also comprises extra electronics for bit conversion. Example – Passive infrared (PIR) sensor and digital temperature sensor(DS1620).
- Scalar sensor –
Detects the input parameter only based on its magnitude. The answer for the sensor is a function of magnitude of some input parameter. Not affected by the direction of input parameters.
Example – temperature, gas, strain, color and smoke sensor.
- Vector sensor –
The response of the sensor depends on the magnitude of the direction and orientation of input parameter. Example – Accelerometer, gyroscope, magnetic field and motion detector sensors.