Category Archives: Sensors

What are Radar Sensors?

Autonomous driving requires the car to have radar sensors as its ears. Originally, the military and avionics developed radar for their applications. Automobiles typically use millimeter wave radar, with a working frequency range of 30-300 GHz, and wavelengths nearer to centimeter waves. These millimeter wave radar offer advantages of photoelectric and microwave guidance to automobiles, because of their significant penetration power.

Automobile collision avoidance mainly uses 24 GHz and 77 GHz radar sensors. In comparison with centimeter wave radar, millimeter-wave radar offers a smaller size, higher spatial resolution, and easier integration. Compared to optical sensors, infrared, and lasers, millimeter wave radar has a significantly stronger ability to penetrate smoke, fog, and dust, along with a good anti-interference ability. Although the millimeter band radar is essential for autonomous driving, heavy rain can significantly reduce the performance of radar sensors, as it produces a large interference. 

Automobiles first used radar sensors in a research project about 40 years ago. Commercial vehicle projects started using radar sensors only in 1998. Initially, they were useful only for adaptive cruise control. Later, radar sensors have developed to provide collision warnings also.

Radar sensors are available in diverse types, and they have a wide range of applications. Automobile applications typically use them as FMCW or frequency-modulated continuous wave radars. FMCW radars measure the air travel time and frequency difference between the transmitted and received signals to provide indirect ranging.

The FMCW radar transmits a frequency-modulated continuous wave. The frequency of this wave changes with time, depending on another triangular wave. After reflection from the object, the echo received by the radar has the same nature of frequency as the emitted wave. However, there is a time difference, and this tiny time difference represents the target distance.

Another radar in common use is the CW Doppler radar sensor. These sensors use the principle of the Doppler effect for measuring the speed of targets at various distances. The radar transmits a microwave signal towards the target, analyzing the frequency change of the reflected signal. The difference between the two frequencies accurately represents the target’s speed relative to the vehicle.

Autonomous vehicles use radar sensors as their basic but critical technical accessories. The radar sensor helps the vehicle to sense objects surrounding it, such as other vehicles, trees, or pedestrians, and determine their relative positions. Then the car can use other sensors to take corresponding measures. Radar sensors provide warnings like front vehicle collisions and the initial adaptive cruise. Vehicles with autopilot radars require more advanced radar sensors such as LIDARs that offer significantly faster response speeds.

Autonomous vehicles must develop technologically. Autonomous driving basically requires an autonomous vehicle to quickly understand and perceive its surrounding environment. This requires the coordination of various sensors, allowing the car to see six directions and hear all. Reliable and decisive driving by an autonomous vehicle requires timely and accurate sensing of roads, other vehicles, pedestrians, and other objects around the vehicle.

Automotive electronics mainly uses radar sensors to avoid forward collisions, sideways collisions, backward collisions, automatic cruises, automatic start and stop, blind spot monitoring, pedestrian detection, and automatic driving of vehicles.

Magnetic Position Sensing in Robots

Robots often operate both autonomously and alongside humans. They greatly benefit the industrial and manufacturing sectors with their accuracy, efficiency, and convenience. By monitoring motor positions at all times, it is possible to maintain not only system control but also prevent unintentional motion, as this can cause system damage or bodily harm.

Such monitoring of motor positioning is possible to implement by contactless angle encoding. It requires a magnet mounted on the motor shaft and provides an input for a magnetic encoder. As dirt and grime do not influence the magnetic field, integrating such an arrangement onto the motor provides a compact solution. As the encoder tracking the rotating magnet provides sinusoidal and 90-degree out-of-phase components, their relationships offer quick calculations of the angular position.

As the magnet rotates on the motor shaft, many magnetic encoding technologies can offer the same end effect. For instance, Hall-effect and magnetoresistance sensors can detect the changing magnetic field. 3D linear Hall effect sensors can help with calculating angular positions, while at the same time, also offering compensations for temperature drift, device sensitivity, offset, and unbalanced input magnitudes.

Apart from signal-chain errors, the rotation of the magnet also depends on mechanical tolerances. This also determines the quality of detection of the magnetic field. A final calibration process is necessary to achieve optimal performance, which means either harmonic approximation or multipoint linearization. With calibration against mechanical error sources, it is possible for magnetic encoding to achieve high accuracy.

The driving motor may connect directly to the load, through a gearbox for increasing the applied torque, through a rack and pinion, or use a belt and screw drive for transferring energy elsewhere. As the motor shaft spins, it transfers the kinetic energy to change the mechanical position somewhere in the system. In each case, the angle of the motor shaft correlates directly to the position of the moving parts of the system. When the turns ratio is different from one, it is also necessary to track the motor rotations.

Sensorless motor controls and stepper motors do not offer feedback for the absolute position. Rather, they offer an estimate of the position on the basis of the relative change from the starting position. When there is a loss of power, it is necessary to determine the actual motor position through alternate means.

Although it is possible to obtain the highest positional accuracy through the use of optical encoders, these often require bulky enclosures for protecting the aperture and sensor from contaminants like dirt and dust. Also, it is necessary to couple the mechanical elements to the motor shaft. If the rotational speed exceeds the mechanical rating of the encoder, it can lead to irreparable damage.

No mechanical coupling is necessary in the case of magnetically sensed technologies like magnetoresistive and Hall-effect sensors, as they use a magnet mounted on the motor shaft. The permanent magnet has a magnetic field that permeates the surrounding area, allowing a wide range of freedom for placing the sensor.

AC-DC Core-Less Magnetic Current Sensor

Infineon has a new high-precision core-less magnetic current sensor, the TLI4971. It has an analog interface for measuring both AC and DC currents. This QFN leadless package is only 8x8x1 mm in physical size. The output has dual fast over-current detection. The new sensor from Infineon is UL certified, but a non-UL version is also available.

Current sensors are devices that generate a signal proportional to the amount of current flowing using a magnetic core. The core-less current sensor does not have a magnetic core. Rather, they use magnetic sensors like a Hall element to sense the current flow and generate a proportional voltage output.

Made with the robust and well-established Hall technology of Infineon, the TLI4971 allows highly linear and accurate measurements of current. The full measurement range covers ±120 A. Infineon has managed to avoid all negative effects that plague sensors using flux concentration techniques. This includes saturation and hysteresis. The TLI4971 has internal features for self-diagnostics.

Infineon has added its proprietary digital temperature and stress compensation to provide superior stability to the TLI4971. The analog concept of the sensor along with the digital assistance provides it with excellent stability over lifetime and temperature excursions. For operating in harsh environments, Infineon has provided the sensor with a differential measurement principle that allows substantial suppression of stray fields.

The insertion resistance of the integrated current rail sensor is typically 225 µΩ, enabling ultra-low power loss in the circuit. The small form factor of the SMD package makes it easy to integrate and saves real estate on the board. The sensor accepts a single supply voltage ranging from 3.1 VDC to 3.5 VDC. It is highly accurate and scalable, with the capability to sense and measure both AC and DC currents. The sensor supports a wide range of applications, as its bandwidth is greater than 120 kHz. Its sensitivity error over temperature is very low, typically a 2.5% maximum. Offset over temperature and lifetime is very stable. Voltage slew rates are highly robust up to 10 V/ns.

Infineon has provided galvanic isolation for TLI4971 up to 1150 V peak VIORM. The sensor has a partial discharge capacity of greater than 1200 V. The creepage and clearance distances available are 4 mm. With the application of the differential sensor principle, Infineon has ensured superior suppression of magnetic stray fields. They have also provided two independent fast OCD or Over-Current Detection pins on the sensor. These have configurable thresholds to allow protection for power circuitry of typically 0.7 µs. The operating temperature range is -40 °C to +105 °C. Infineon has precalibrated its sensor, which means it does not require calibration in the field.

There are several potential applications for this core-less magnetic current sensor. Primarily, it is useful in electrical drives up to 690 V, photovoltaic inverters, and other general purpose inverters that require AC/DC current sensing and measurement. The sensor is extremely helpful in detecting the overload and over-current situations. It is applicable in all types of current monitoring, and its huge range is a definite advantage in these situations. It is applicable to all types of power supplies and battery chargers where current measurement is necessary.

What is Moisture Sensing?

In agriculture, where plants require watering, people often use time-controlled watering methods. While this method irrigates plants in fixed time intervals, there is no way to assess whether there is an actual need for watering. Most often, this leads to either over-watering or under-watering. Depending on weather conditions, over-watering may cause harmful water-logging, while under-watering may lead to dry stress for plants. People often mitigate the amount of water flow by using a rain sensor or controlling the water delivery based on online weather information.

Using a sensor to sense the amount of moisture in the soil and control the watering works much better. Not only does the latter method allow optimal water supply to the plants, but it also substantially reduces water consumption. Threshold levels can be set using various strategies. Any experienced gardener can recognize the start of dry stress when they notice the plants wilting slightly, or when the leaf edges start rolling.

Excessive watering does not increase the moisture in the soil, rather, it results in saturation. By delaying watering for a while, the excess water usually drains off into the subsoil. Most gardeners set the lower threshold to about 60% of the saturation level. They observe the plants and the moisture trend during the early phases to adjust the threshold levels to allow an economical and optimal automatic watering. It is necessary to position the sensor properly in the soil near the root area. For drip irrigation, it is possible to achieve a good soil moisture cycle by placing the sensor somewhere where it is neither too far nor too close to the drip location.

For working with moisture sensors, it is necessary to consider sensor selection and integration. This is because moisture sensors have two functions in a watering system. The first is they provide information about the current status of the watering. The second is they help to economically use water as a resource. Many plants are intolerant to dry soil as they are to water-logging. Moreover, while there are numerous types of moisture sensors, they have different ways of working and their life spans vary widely.

The presence of moisture in the soil can have different definitions. There is the volumetric water content, which represents the amount of water in the total amount of soil. In natural soil, the maximum volumetric water content is about 50-60 % and represents the amount of water filling all the airspace in the soil. Organic materials and peat can hold more water.

The relative mass of water in the soil is its gravimetric water content. This is determined chiefly by weighing the soil sample before and after drying. As it requires a laboratory to do the measurement, this method is not suitable for continuous monitoring in the field.

A variety of principles of physical measurements form the basis of many types of electrical sensors for measuring soil moisture. The most inexpensive is the measurement of electrical conductivity. Next are low-frequency capacitive sensors. High-frequency capacitive sensors are more expensive. Then there are tensiometers that measure the soil moisture tension.

What are Floating Sensors?

Floating sensors support applications for environmental monitoring and agriculture. Designed by researchers from the University of Washington, floating sensors typically spread just like seeds of the dandelion plant do, when a drone drops them from a height. The sensors are battery-free devices, hovering over 100 meters. The sensors have electronics on board, including a capacitor for storing overnight charge, sensors, and a microcontroller for running the system. The entire structure resides in a flexible body.

The evolution of dandelions allows them to disperse their seeds further than a kilometer in the air. Although for valuable wireless sensors, it is not a good idea to drop them from great heights. However, the researchers did just that by creating a tiny device that can carry the sensor, with the wind blowing it at it tumbles towards the ground.

Just like the dandelion seeds do, the sensors too, float in the breeze. As the device is about 30 times heavier than a dandelion seed weighing one milligram is, it can travel only up to a distance of about 100 meters on a windy day. The researchers had to mimic the shape of the dandelion seeds as it was necessary to ensure that the device landed with its solar panels facing skywards.

The structure of dandelion seeds has a central point where little bristles stick out. These tend to slow down their fall. The researchers took a 2-D projection of the seed and used it to create the base design for the structure of their floating sensors. When they added more weight, the bristles started to bend inwards. The researchers then added a ring structure to make the bristles stiffer, and take up more area, allowing it to slow down the fall. The team tested more than 75 designs with various sizes and patterns using laser micro-machining.

The sensor can share data related to pressure, temperature, humidity, and light up to a distance of 60 meters. The researchers have added a capacitor to the design of their floating sensors, allowing it to store some charge for the night. As an experiment, the researchers used a drone to drop sensors from a height of 20 meters, sending the sensors sideways to about 100 meters towards a parking area.

According to the researchers, from an engineering point of view, imitating dandelion seeds allows for achieving some amazing capabilities. Although dandelion plants cannot move, they can disperse their seeds up to a kilometer away, provided the right conditions exist. The team has been trying for a similar achievement by automating the deployment of wireless sensors to create a network. Conventional methods of studying climate changes or monitoring the environment over really large geographic areas can be very expensive and time-consuming. Dandelion seeds and their dispersion methods provided the team with the necessary inspiration to create sensors that can disperse in the wind, and automate this process.

The team had to look at nature again to get good coverage over the area of interest. They mimicked the random process followed by plants to disperse their seeds. The researchers designed a large array of different structures to make them float for different periods.

Proximity Sensor Technology

Proximity sensor technologies vary with operating standards, strengths, and determining detection, proximity, or distance. There are four major options for compact proximity sensors useful in fixed embedded systems. It is necessary to understand the basic principles of operation of these four types for determining which to select.

Most proximity sensors offer an accurate means of detecting the presence of an object and its distance, without requiring physical contact. Typically, the sensor sends out an electromagnetic field, a beam of light, or ultrasonic sound waves that pass through or reflect off an object, before returning to the sensor. Compared with conventional limit switches, proximity sensors have the significant benefit of being more durable and, hence, last longer than their mechanical counterparts.

Reviewing the performance of a proximity sensor technology for a specific application requires considering the cost, size, range, latency, refresh rate, and material effect.

Ultrasonic

Ultrasonic proximity sensors emit a chirp or pulse of sound with a frequency beyond the usual hearing range of the human ear. The length of time the chirp takes to bounce off an object and return determines not only the presence of the object but also its distance from the sensor. The proximity sensor holds a transmitter and a receiver in a single package, with the device using the principles of echolocation to function.

Photoelectric

Photoelectric sensors are a practical option for detecting the presence or absence of an object. Typically, infrared-based, their applications include garage door sensing, counting occupancy in stores, and a wide range of industrial requirements.

Implementing photoelectric sensors can be through-beam or retro-reflective methods. The through-beam method places the emitter on one side of the object, with the detector on the opposite side. As long as the beam remains unbroken, there is no object present. An interruption of the beam indicates the presence of the object.

The retro-reflective method requires the emitter and the detector to be on the same side of the object. It also requires the presence of a reflector on the other side of the object. As long as the beam of light returns unimpeded, there is no object detected. The breaking of the beam indicates the presence of an object. Unfortunately, it is not possible to measure distances.

Laser Rangefinders

Although expensive, these are highly accurate, and work on the same principle as that of ultrasonic sensors, but using a laser beam rather than a sound wave.

Lasers require lots of power to operate, making laser rangefinders non-suitable for portable applications or battery operations. Being high-power devices, they can be unsafe for ocular health. Although their field of view can be fairly narrow, lasers do not work well with glass or water. 

Inductive

Inductive proximity sensors work only with metallic objects, as they use a magnetic field to detect them. They perform better with ferrous materials, typically steel and iron. A cost-effective solution over a huge range, the limited use of inductive proximity sensors to detect objects reduces their usefulness. Moreover, inductive proximity sensors can be susceptible to a wide range of external interference sources.

What is Tactile Sensing Technology?

Scientists have been exploring the field of soft robotics for use in healthcare systems. They aim to emulate the sense of touch. However, they have not had much success with tactile-sensing technology while fine-tuning dexterity.

In an experimental study, published in the Journal of the Royal Society Interface, scientists made a comparison of the performance of an artificial fingertip with that of neural recordings made from the human sense of touch. The study also describes an artificial biometric tactile sensor, the TacTip, which the scientists had created. According to the study, TacTip offers artificial analogs of the dynamics of the human skin and the nerves that pass information from skin receptors to the central nervous system. In simple words, TacTip is an artificial fingertip that mimics nerve signals on human fingertips.

The researchers created the artificial sense of touch. They used papillae mesh that they 3-D printed and placed on the underside of the compliant skin. This construction is similar to the dermal-epidermal interface on real skin and is backed by a mesh of dermal papillae and biometric intermediate ridges, along with inner pins that are tipped with markers.

They constructed the papillae on advanced 3-D printers. The printers mixed soft and hard materials, thereby emulating textures and effects found in real human fingertips. They actually reconstructed the complex internal structure of the human skin and the way it provides for the sense of touch in human hands.

The scientists described the effort as an exciting development in soft robotics. They claim that 3-D printing tactile skin would lead to more dexterous robots. They also claim that their efforts could significantly improve the performance of prosthetic hands by imbibing them with an in-built sense of touch.

The scientists produced artificial nerve signals from the 3-D printed tactile fingertips. These signals look very similar to the recordings from actual, tactile neurons. According to scientists, human fingers have several nerve endings known as mechanoreceptors that transmit signals through human tactile nerves. The mechanoreceptors can signal the shape and pressure of contact. Earlier, others had mapped electrical signals from these nerves. By comparing the output from their 3-D printed artificial fingertip, the scientists found a startlingly close match to the earlier neural data.

A cut-through section of the 3-D printed tactile skin shows a white plastic that forms the rigid mount for the flexible black rubber skin. Scientists made both parts on advanced 3-D printers. The inside of the skin has dermal papillae, just as the real human skin also has.

In comparing the artificial nerve recordings from the 3-D printed fingertip with the 40-year-old real recordings, the scientists were pleasantly surprised. The complex recordings had many dips and hills over ridges and edges, and the artificial tactile data also showed the same pattern.

However, the researchers feel that the artificial skin still needs more refinement, especially in the sensitivity area pertaining to fine detail. As such, the artificial skin is much thicker than the real skin is. Scientists are now exploring different means of printing 3-D skins that mimic the scale of human skin.

MEMS Pressure Sensors in Industrial Applications

A wide range of industrial applications requires the usage of pressure sensors. Continuous improvements in these sensors are necessary for new applications, including their use in more common applications like measuring fluid and steam pressure.

Recent power sensor technologies have made available devices with reduced size, better economics, more integration capabilities, and wider operating supply voltages, enabling OEMs to deploy sensors for applications like the Internet of Things. Additionally, with these sensors, it is possible to create products that are not only more sustainable but also feature additional embedded innovative features and less power consumption.

Along with a focus on applications, these sensors demonstrate a variety of methods and techniques for detecting pressure in industrial settings. Most notable among these are the MEMS or micro-electric-mechanical sensor technology.

Pressure is the force on a surface with a given surface area. Commonly, units for pressure measurement include the Bar, Pascal, and PSI or pounds per square inch. The sensor for a specific application typically defines the units it uses. For instance, it is customary to use bars or millibars to indicate pressure value in water-level applications. The automobile industry uses PSI to indicate pressure, such as in tires.

While measuring vertical distance or altitude, barometric air pressure is a common indicator. The reference here is the air pressure at sea level, which is equivalent to 1013.25 Mb or millibar. As the altitude changes, so do the air pressure.

In industrial applications, pressure sensors are generally of three types. These are the gauge pressure, absolute pressure, and differential pressure sensors.

A gauge pressure sensor uses the atmospheric or ambient pressure as its reference. This is typically 1013.25 Mb or 14.7 PSI at sea level. If the measurement is above ambient, it represents positive pressure, while a measurement below ambient is negative pressure. These sensors are useful in applications that require pressure measurement over longer periods, with little or no calibration.

Absolute pressure sensors use vacuum as the reference, with the absolute pressure of a full vacuum being zero PSI. Most absolute pressure sensors detect pressure below the atmospheric pressure. Altimeters are absolute pressure sensors using gauge pressure sensors.

Differential pressure sensors use a second pressure as a reference. This second pressure may be higher or lower than the pressure under measurement, or the atmospheric pressure. Differential pressure sensors are useful for measuring flow rates.

Industrial applications for pressure sensors have now evolved to the level where most sensors are smaller, smarter, and more conscious of energy consumption.

The various types of pressure sensors in use in the industrial environment, and the progress of MEMS technology, has enabled the semiconductor industry to make pressure sensors economical in high volumes.

With embedded compensation, low power consumption, and small size, these MEMS pressure sensors come in robust packaging. This allows wider use of MEMS sensors in industrial environments than was possible before. Most modern industrial systems now use a mixture of sensor technologies that not only run more efficiently but also waste much less energy. MEMS technology is the one leading in sensor applications in most industrial settings.

Digital Planar Liquid Flow Sensor

The chemical industry often requires measuring liquid flow in fluidic manifold systems. These often involve high-volume applications but with severe space limitations. For such applications, Sensirion offers a digital planar liquid flow sensor, the LPG10-1000. The sensor uses a planar microfluidic glass substrate that has down-mounted fluidic ports. Measuring only 10 x 10 x 2.35 mm, the LPG10-1000 is a highly compact unit capable of being integrated into any fluidic manifold system.

The sensor combines a digital microsensor and a microfluidic chip to measure the liquid flowing inside the planar glass substrate. The presence of the digital microsensor chip ensures full signal processing functionality. Its digital output is linearized, temperature compensated, and fully calibrated.

LPG10-1000 from Sensirion is an intelligent sensor providing solutions for measuring flow rates from a few microliters per minute to about 1ml per minute. Sensirion has provided a special glass for the wetted material, and it ensures optimum compatibility with the pharmaceutical and biological processes. The low thermal mass of the sensor allows response times lower than 30 ms. The sensor has built-in features for detecting real-time failures like leaks, air bubbles, and clogging.

The Sensirion sensor LPG10-1000 offers several advantages for measuring liquid flow. Its tiny size makes it extremely convenient for integration, even in small spaces. The engineering simplicity of the sensor’s design offers excellent repeatability. The output signal is digital, linearized, and calibrated. Media compatibility is excellent, and chemical resistance is high.

Sensirion has used the media isolated sensing principle for its sensor, as there is no direct sensor contact with the fluid it is measuring. The glass they use is of the inert type, so it is bio-compatible with the chemical process. The sensor offers a digital I2C interface for electronic compatibility.

The LPG10-1000 sensor offers a full-scale flow rate of 1000 microliters, and a sensor output limit of 1500 microliters. The response time for detecting the flow is about 40 ms, with 120 ms from power-up. The operating range for the sensor covers +5 to +50 °C, while the specified temperature range for storage is -40 to +60 °C. The sensor can operate reliably in 0 to 95% humidity and non-condensing conditions. The recommended maximum operating pressure is under 3 bar or 43 psi, and the sensor can withstand a burst pressure of up to 7 bar or 101 psi.

For a full-scale 16-bit output, the digital sampling time of the sensor is 74 ms. However, for a 9-bit output, the sampling time can drop to as low as 1 ms. The sensor operates within a supply voltage range of +3.3 to +3.6 VDC, consuming less than 6 mA operating current.

The internal substrate channel glass material is borosilicate and has a down mount fluidic connection. The introduction of the sensor in a fluidic manifold system causes a pressure drop of only 0.1 millibars at full-scale flow rates. The total internal volume of the sensor is about 11.7 microliters. The cross-sectional flow channel of the sensor measures about 0.9 x 0.9 mm, and the total mass of the sensor is only 0.32 grams.

MEMS Technology for CO2 Sensing

Most technologies for detecting CO2 are based on photo-detection, where smoke particles reflect light that photo-sensors can detect. However, MEMS technology now offers a more sensitive technology for detecting CO2. Using their knowledge in sensors and MEMS technology, Infineon has now introduced a disruptive gas sensor for sensing CO2 gas.

Coming in a minuscule form factor, the XENSIV PAS CO2 from Infineon is a real CO2 sensor. Infineon has based it on the principle of photoacoustic spectroscopy or PAS. Infineon uses a MEMS microphone, which they have optimized for low-frequency operation. The sensor has a cavity that can detect pressure changes generated by CO2. An integrated microcontroller in the sensor then delivers the CO2 concentration in the form of a direct ppm readout. As the absorption chamber of the sensor is acoustically isolated from external noise, the sensor guarantees highly accurate readings of CO2.

XENSIV PAS CO2 has impressive features. Its operating range extends from 0 ppm to 10,000 ppm, with a linear response giving an accuracy of 30 ppm +3% of reading between 400 ppm and 5,000 ppm. The operating temperature range of the sensor is 0-50 °C at a relative humidity (non-condensing) of 0-85%.

The sensor requires two supply voltages, 12VDC for the emitter and 3.3VDC for its other components, and its average power consumption is typically 30 mW when operating at 1 measurement per minute. With a package dimension of 13.8 x 14 x 7.5 mm, the sensor offers three interface standards—I2C, UART, and PWM.

XENSIV PAS CO2 has several potential applications. On account of its high accuracy, SMD capabilities, and compact size, the sensor is ideally suitable for indoor air quality monitoring with numerous potential applications. For instance, the sensor is highly suitable for home appliances for air conditioners and air purifiers. It is also suitable for smart home IoT devices like smart lighting, indoor air quality monitors, personal assistants, baby monitors, speakers, and thermostats. Apart from use in in-cabin air quality monitoring in aircraft, the sensor is eminently suitable for city management and CO2 emission control in advertising billboards, bus stations, and outdoor lighting.

While measuring the CO2 concentration, the sensor operates in one of two modes—active state and inactive state. In the active state, the integrated CPU is in an operating state and performs tasks like running a measurement sequence or serving an interrupt. However, when the sensor has no specific task to perform, the CPU enters an inactive state. The device may enter an inactive state from an active state at the end of a measuring sequence.

During an inactive state, the CPU controlling the device can enter a sleep mode to optimize the consumption of power. Several events can wake up the CPU from its inactive state—a falling edge on the PWM pin, reception of a message on the serial communication interface, or the internal generation of a measurement request when the device is in continuous measurement mode.

It is possible to program the sensor module via its serial communication interface to operate in one of three modes—idle mode, Continuous mode, and Single-Shot mode.