Reducing Downtime with Remote Alarm Systems

Converting an automated plant to a smart factory is definitely a leap forward. However, it requires enabling a flexible and fully connected system to learn and adapt to new requirements, using a steady stream of data coming from production systems and connected equipment.

Nowadays, there is a convergence of extreme challenges facing manufacturing plants. Most consist of an aging workforce with issues of knowledge transfer, there is increasing demand for high-quality products, the need to use fewer resources, coupled with pandemic situations like that from COVID-19. Not only must these issues be navigated, but manufacturing plants must also maintain ongoing operations while controlling costs. Additional situations like unplanned downtimes can often cause financial disasters and logistical nightmares.

However, there is a silver lining to this dark cloud. IIoT, coupled with machine connectivity and monitoring solutions, is providing solutions for mitigating the above-unexpected problems including challenges of staffing.

A report from Deloitte and the Manufacturing Institute had forecasted an expected shortage of 2 million workers for US manufacturing during 2015-2025. The pandemic has only exacerbated the situation. In their latest report, Deloitte and the Manufacturing Institute claim that by 2030, roughly 2.1 million manufacturing jobs will remain unfulfilled. According to the report, this will cost the US economy about $1 trillion by 2030.

Manufacturing plants spend millions of dollars each year as capital for improving equipment and facilities to protect employees, increase product safety, and reduce costs. This is very important, as equipment may run from 16-20 hours a day, every day, 24/7, especially in food processing plants. Downtime primarily is from equipment failure, causing an astounding $30,000 per hour in these food processing facilities.

This is where the iFIX SCADA system along with the WIN-911 Advanced remote alarm modification software from GE can help ensure the plant continues to operate non-stop.

One of the main ideas is having a sensor monitoring if the machine is working properly, rather than having someone crawl under it to check it out. The other is to use a remote alarm monitoring notification software, allowing fewer people to monitor far more assets with devices they already have—smartphones and tablets. For continuous monitoring of systems, uninterrupted remote availability is essential. The advantage of the system is staff need not remain onsite, and the facility needs fewer people.

Earlier, remote monitoring involved emails, texts, and phone calls. However, monitoring critical plant systems now extend beyond these. They include apps featuring time-saving tools like team chats, real-time alarm acknowledgments for troubleshooting, and resolving plant problems. They also provide detailed reporting so that future incidents do not occur. While this leads to fewer emergency shutdowns, it also requires fewer resources and lower spending on maintenance and overtime.

The mobile alarm notification app is software integrating seamlessly with the HMI or SCADA software of an industrial operation. This allows employees to monitor, receive and acknowledge alarms from machines and plants on smartphones and tablets. This way they can remain free to work from any remote location such as their homes.

Optical Chip is Faster than GPU

Although a typical GPU setup can solve the Ising problem with ease, now a silicon photonics accelerator can also do the same, but at a speed a hundred times faster. The optical computing startup Lightelligence has demonstrated this feat.

The photonic arithmetic computing engine from Lightelligence is an integrated optical computing system, and it is known as Pace. It consists of about twelve thousand photonic devices that run at 1 GHz each. Compared to Comet, the earlier 100-device prototype from Lightelligence that they unveiled in 2019, Pace has a speed advantage of 1 million times. This is the first time that Lightelligence has demonstrated a use case on its hardware that goes beyond AI acceleration.

Lightelligence has designed Pace to run algorithms for problems that belong to the NP-Complete class. These represent one of the most difficult computational issues, requiring much higher speed systems compared to existing accelerators. Pace did not demonstrate optical superiority for all applications. However, it beat a typical GPU when executing the Ising problem by a factor of 100. In fact, it was even defeated by a factor of 25 a system that Toshiba assembled especially for solving the Ising problem—the simulated bifurcation machine running on FPGAs.

With a huge state space, NP-complete problems require very large computing resources for tackling them. The computing time depends on a polynomial of the size of the problem, scaling in proportion. This class includes the Ising problem, traveling salesman problem, and the graph max-cut/min-cut problem. In reality, NP-Complete problems can be found in scheduling, bio-informatics, material discovery, circuit design, power grid optimization, and cryptography applications.

According to their CEO Yichen Shen, Lightelligence decided to demonstrate the acceleration of NP-Complete problems as this best illustrated the advantages of optical computing.

The chief advantage of the optical compute engine from Lightelligence is it can compute matrix multiplications much faster than GPUs can. Typically, GPUs take several hundreds of clock cycles to complete a 64 x 64 matrix multiplication. According to Lightelligence, Pace can do it in about 5 nsec. As NP-Complete problems require several iterative matrix multiplications, Pace has the upper hand. Lightelligence wanted a problem that best demonstrated the superiority of this new technology.

The major factor for Pace is the iterative nature of the algorithms that the NP-Complete problems use. Moreover, the successive matrix multiplications depend on the result of the previous calculations. In GPUs, system electronic parts cause the bottleneck, as data must shuttle to and from the memory in between multiplications. With bigger commercial use cases, the read and write cycles in digital electronics increases tremendously such that the entire computing system slows down. Lightelligence is confident it will be able to demonstrate advantages at least several times faster, if not 100 times.

Optical computing has numerous advantages. Based on silicon photonics, Its main advantage is its speed—several orders of magnitude improvements in power efficiency and computing speed. Basically, the system directs modulated infrared light within silicon wires or waveguides. Scientists accomplished this by using standard CMOS processes.

Why ADC Grounding is Important

We commonly use analog to digital converters in electronic devices. For instance, we connect the output of a sensor to an ADC input and use the digital readings for our purpose. Digital signals offer good noise rejection, there is firm switching between levels, and the built-in margin available is also good. However, the analog side can be susceptible to noise.

If the analog input is noisy, it affects the digital output. Most noise levels on the analog side come from a single source—a lack of attention to the ground. To have better results with ADCs, understanding basic principles about grounding is important.

Grounding is simple for low- and mid-speed digital design. When testing the design on a breadboard, power and ground lines are well-defined. These are the two rails running along the two longer edges of the breadboard. The designer designates one of the lines as power, while the other is the ground. They connect the power and ground points in the circuit to the respective rails using short wires.

The importance of grounding increases as digital circuits start to operate faster, and the resolution of the analog side increases. In reality, the ground is not simply a zero-voltage level, it is also a return path for the current flowing in the circuit.

In ideal conditions, whatever may be the circuit behavior, it would not affect the ground. However, in the real world, the ground is rather imperfect. The return path from a narrow trace may have a tiny bit of resistance, such as that from a bad solder joint, or from a few ground pins on a chip. It is possible to see ground bounces in the form of voltage spikes. Add to this resistance some stray inductance, such as from leads of a chip package. Now, power supply noise increases as the operating frequencies go up.

When the ADC resolution is high, the step width in the digital output is in the millivolt range. This makes spikes and noise on the analog input a major problem. The input noise causes bits of error that add to the error sources within the ADC. Designers can take reference from good off-the-shelf board designs for improving the ground quality.

Boards with SoCs or microcontrollers often have a ground plane. Here, the ground is a thick copper layer that may occupy more than one layer on a multi-layered board. IC pins that need to reach the ground can do so with very short paths. Connecting resistance reduces drastically. Capacitors bypassing the power lines reduce stray inductance to a large extent. This helps to smoothen the noise from power supply lines.

Nowadays, there are smart sensors in the market. They contain built-in microcontrollers and ADCs. The input analog signals have a very small distance to travel. They have much less tendency to pick up noise. In addition, some sensors also present data in serial modes, such as on SPI or i2C interfaces, where the output is already in digital form.

Designers must pay special attention to boards with islands of unconnected ground, as these can cause the maximum level of noise at the input.

Improvements in Machine Vision

The way consumers now interact with retailers, banks, and the hospitality industry, has undergone a sea of change. There are many self-service kiosks and ATMs for the consumers to interact, and this is undergoing a revolution. However, these improvements mean the back-end systems must undergo a huge improvement in terms of new hardware, firmware, software, and connectivity.

New businesses are getting the most out of their kiosks, with the role of machine vision creating a seamlessly connected experience for their customers. Initially, they had started with a software platform that helped customers execute their requirements more quickly. However, they realized very soon that machine vision could integrate software and physical-device designs.

Customers typically try to create or replicate a better experience. It is not just about pushing through quicker, building lines, or going through traditional use cases. They want to create a richer and more engaging experience with the minimum number of touches. They relish a more personal experience.

The businesses deploying the kiosks want to offer their customers a more seamless experience. Machine vision is playing a massive part in these applications in making the entire process seamless. For instance, postal services can be quite complex, such as when a customer needs to send a parcel through, and machine vision makes sure they fill out their forms the right way.

Machine vision has improved to the extent of recognizing handwriting. It can automatically detect the destination and verify the address. As the customer fills in the form, machine vision, along with the AI system, cleans and corrects the data as the parcel goes through. This ensures the parcel reaches its destination.

Another example is a kiosk connected to a retail bank. Tokenization distinguishes the customer’s skill level when they use the kiosk. This allows it to bypass any instructional content, taking the customer right to the point. That is what the customer expects—when they have used the kiosk once or twice—-they prefer a seamless experience.

Machine vision and AI applications are very useful during hotel check-ins. Most hotels look for a universal premium experience for their customers when they are using the kiosk service, like check-in, valet, or similar services.

Most cases such as the above require tightly integrated machine vision and AI solutions within their kiosk applications. Customers also expect the high-traffic kiosks to stay clean and safe to use.

For this, businesses are opening their kiosks to various options, such as finger and eye-tracking. These new techniques do not require the customer to physically touch the device. However, most customers did not quite adapt to the touchless techniques, and these did not add to their best experiences.

Therefore, businesses have developed advanced techniques like antimicrobial and heat-mapping touched areas on the kiosk. It uses AI and a combination of touchscreen and pressure sensors. With the presence of physical cameras on the screen, the kiosk allows the creation of a complete digital manifest of areas that others have touched. After a threshold, the kiosk shuts down, until a local attendant physically cleans it. The kiosk maintains a complete manifest of who cleaned it and when.

Human-Machine Interaction in Automobiles

In automobiles, there is a need to realize sensing of force, proximity, ambient light dimming, and gesture control with digital optoelectronics components. Optoelectronics sensor devices enable HMI or Human-Machine Interaction. This requires sensing user inputs and lighting conditions, allowing drivers to keep their eyes on the road. It is possible to connect most optical sensors nowadays to the central controller via the I2C interface.

By setting the internal settings of ASICs or Application Specific Integrated Circuits, it is possible to adjust and fine-tune sensitivity, driving currents, measurement speed, and other parameters to the specifications of the application. This allows force measurement on a given surface for detection or inputs, proximity, and gesture control on the central console, and contrast regulation for adjusting the screen backlight.

Force sensing is necessary to detect an input or control function requiring a force or pressure, adequately strong, to trigger a function. Force sensing in automobiles can also detect false forces, such as from an accidental brush over a touch screen or button. Proper sensing of force allows expanding on input possibilities, like coupling it with menu selections. Low-profile, AEC-Q101-qualified proximity sensors with high sensitivity can have programmable driver current, adjustable in 10 mA steps, flowing through the internal infrared emitter.

Such sensors are popular in force sensing applications. Such applications typically require fine-tuning of sensor performance depending on the given mechanical setup. Implementation of this function requires placing the sensor underneath a surface where the application of force is likely. The high sensitivity of the sensor within a region of 3-10 mm allows the detection of small changes in the displacement of the surface.

Center displays in vehicles use AEC-Q101-qualified proximity sensors. This allows for both gesture and proximity control. Rather than use an internal emitter, the proximity sensor has three current drivers, each with a designated pin. These can directly drive external infrared emitters without needing additional circuitry. This results in a highly flexible solution, where it is possible to choose a specific external infrared emitter to use and their placement with reference to the sensor.

For detecting gestures, it is typical to use narrow-angle emitters. This allows properly defining the area wherein it is necessary to detect motion. For wide areas, it is customary to use wide-angle emitters, such that the sensor solution can cover a wide area. This allows the sensor to cover a wide area, and allows detection of user input, regardless of the direction of the user’s hand entering the sensor’s field of view.

Furthermore, it is possible to have individual ADCs on each channel to allow differentiation of the direction of detection. For instance, this allows detecting user inputs from the passenger side, without distracting the driver.

While proximity sensors gather information about happenings in front of the display, ambient light sensors help with the dimming of the display. The main challenge in such applications is the increasing use of dark cover material used in the interiors of vehicles. At times, these cover materials allow the passing of less than 1% of visible light. Therefore, it is necessary to use a sensor with high sensitivity.

Dual Board Net Systems in Automobiles

Modern electric vehicles are increasingly using dual board net systems. These contain both a 12 VDC bus and a 48 VDC bus. One of the key building blocks in the architecture of these vehicles is the high-power, bidirectional 48 VDC to 12 VDC converter. Energy flows in either direction between the two batteries—48 V and 12 V. This helps to optimize the overall efficiency of the vehicle. The direction of the energy flow depends on the demands the vehicle’s electrical system places on the batteries and their state of health.

Vishay offers a complete 3 kW 48 V / 12 V buck-boost type DC/DC converter for electrical vehicles. The design has a standard FR-4 controller board mounted on an IMS or Insulated Metal Substrate that sports a heat sink for the power stage. As these converter designs do not operate at maximum efficiency over a wide power range, Vishay has designed them as six modular power stages operating at 500 W each.

It is possible to switch the protection MOSFETs on/off in each stage. This allows the system to activate or deactivate each power stage individually. Vishay uses this topology for maximizing efficiency under various operating conditions. Moreover, this also provides built-in redundancy, preventing a total breakdown in the event of any failure in an individual power stage.

The converter design from Vishay has another important detail—the half-bridge design uses different MOSFETs. As the high-side MOSFET operates at one-fourth the output current, its on-resistance is not essential. Instead, the gate-drain charge and the gate-source charge of the MOSFETs are more significant. Rather than use the regular low-power thick film resistors, Vishay uses thin-film MELF resistors for driving the gates.

Thin-film MELF resistors can handle large pulses, while not drifting over time and temperature. This prevents an increase in switching losses at frequencies of 100-150 kHz. Switching losses are the dominating power-loss factors at these frequencies. To minimize the drain-to-source resistance in the low-side MOSFET, Vishay connects two of them in parallel, as this resistance is the largest factor dominating the power loss.

The DC/DC converter has a primary storage inductor. This inductor must support both the DC output current and the ripple current. The inductance value and the switching frequency determine the ripple current amplitude. Although increasing the inductance value or the switching frequency helps in reducing the ripple current, it is necessary to consider a tradeoff in performance and size. The designer must ensure the inductor rating is adequate for the output current it must handle, without saturation and high self-heating.

Vishay uses IHDM inductors for primary storage. These have a good combination of low core loss (AC), low DC loss, and very good saturation performance. The IHDM series of inductors from Vishay cover a wide range of inductor values, ranging from 0.1 µH to 200  µH. Their current handling capacity ranges from a few amperes to several hundred amperes. The inductor series also comes in several materials, allowing efficient operation when the converter is operating between 100 kHz and 5 MHz.

Developments in Autonomous Robots

The recent COVID pandemic had put a lid on air travel. But that is now slowly lifting, and more people are venturing out. Airports are responding with new robots offering food delivery services.

The International airport in Northern Kentucky is currently using these Ottobots, made by Ottonomy, a robotics company. The Ottobot is a four-wheeled autonomous robot.

At the airport, in the Concourse 8 area, travelers can use a dedicated app to purchase food, beverages, or travel products from select stores. The location of these stores may be anywhere in the airport. Once the travelers have placed their orders, staff, at the store, place the items within the cargo compartment of the Ottobot and send them on their way.

While making its way through the airport, the Ottobot robot uses sensors and a LIDAR module to avoid people and obstacles. Ottonomy has designed a contextual mobility navigation system for the robots to allow them to keep track of their whereabouts. Apart from the contextual mobility navigation system, the robots also use other indoor navigational systems like Bluetooth beacons, readable QR codes, and Wi-Fi signals.

Customers can see the Ottobot on their mobiles, thanks to the app, which alerts them once it reaches their location. The app also has a QR code specific to their order. Once the customer holds their QR code for the robot to scan, it unlocks and opens its cargo compartment lid to allow them to retrieve their purchase. User feedback from a pilot project in the airport helped design the current robotic delivery system.

Not only in airports but there are several urban delivery robots also that use four wheels to move along city sidewalks. The wheels are special, as they can pivot and are mounted on articulated legs.

Delivery robots usually have smart lockable cargo boxes and two sets of powered wheels on their bottom. While autonomously moving along a smooth pathway, this arrangement works fine. However, for moving over curbs, climbing upstairs, or for traversing regular obstacles.

Piezo Sonic, a Japanese robotics company, has developed Mighty, the special delivery robot. They have based their design on a concept for robots exploring the moon:—: it does not have smooth sidewalks.

Mighty has four independently powered wheels. They can point either straight ahead for normal movements, or pivot to point sideways to allow the robot to move sideways in one direction or the other. The four wheels can also pivot part of the way outward or inward, forming a circle for Mighty to spin around on the spot.

Additionally, each wheel has its own hinged leg. Therefore, when the robot moves over an uneven surface, each leg can bend independently to compensate for the difference in height. This helps to keep the main body of the bot level. Mighty can use this feature to climb shallow sets of stairs.

Mighty uses GPS to navigate cities like other delivery robots. It also has cameras and LIDAR sensors for dodging hazards and pedestrians. It can easily carry a 20-kg cargo, climb 15-degree slopes, and step over obstacles up to 15 cm tall, all the while attaining a top speed of 10 km per hour.

What is Multi-Point Bluetooth?

It is certainly advantageous to live a wire-free lifestyle—especially with Bluetooth connectivity. However, there is the experience of having to pair earbuds or headphones to consider. Most of the time, the pairing is difficult, takes up considerable time, and is not intuitive. Multi-point Bluetooth helps with these concerns.

Using multi-point Bluetooth, it is possible to connect one pair of earbuds or headphones to multiple devices at once. It may not be necessary to execute the annoying pairing process. Moreover, it allows telephone calls to come through even when the laptop or tablet is playing music through the headphones.

Regular Bluetooth has its deficiencies. The pairing process is troublesome, and switching between audio sources is an incredibly difficult exercise. That is why most users connect their earbuds and headphones to their phones or laptops once and leave them undisturbed. For them, it is more convenient this way than to pair them anew with another device.

Although the Bluetooth Special Interest Group introduced Bluetooth 4.0 with multi-point capability back in 2010, most earbuds and headphones available today lack multi-point capability. But those available with multi-point capability are superb performers.

For instance, a user wearing wireless earbuds is on a video call on a laptop. As the call ends, they decide to go on a jog, taking their phone with them. They start streaming their workout playlist on the phone. With a multi-point capability, they do not need to go through the Bluetooth pairing process, and they can enjoy the music right away through their earbuds.

What happens if a call comes through? Bluetooth multi-point can interrupt an audio streaming process. It can pause the music while the phone switches automatically. Once the call is over or the user chooses to ignore it, the headphones can switch back to the music.

However, it is not possible to play audio from two devices simultaneously when on multi-point Bluetooth. Although multi-point Bluetooth technology sounds fantastic, it is not yet a perfected technique.

When a device is set up with Bluetooth, it actually connects to a piconet or a tiny network. In practice, a piconet is made up of two devices—a single audio source and a pair of headphones.

The headphones in this piconet act as a leader. It dictates how and when the connection operates, and the audio source, whether the phone or the laptop, behaves only as a follower. The follower listens to any command the leader of the headphones sends—like play or pause—and complies with any rules—such as bitrate constraints or audio codecs—that the headphone sets.

With multi-point Bluetooth, a supporting pair of headphones has a piconet that includes a number of extra followers, or audio sources. But different models of headphones, headsets, or earbuds can have different types of multi-point capability. Typically, four types exist—Simple, Advanced, Triple, and Proprietary.

Most consumer headphones support the Simple multi-point capability, allowing connection with two sources. Business headsets support the Advanced multi-point capability. Although able to connect with two sources, any interrupted call is automatically put on hold. Triple connectivity allows connecting with three sources. Apple AirPods and Galaxy Buds of Samsung typically use the Proprietary capability.

Low Pressure Drop Digital Flow Meters

Sensirion offers low-pressure drop digital flowmeters that are highly accurate and update the readings very fast. These meters are available in fully calibrated form along with built-in temperature compensation.

The SFM3000 sensor is a digital flow meter that Sensirion has designed for applications with high volumes of flow. The flow meter allows measuring with superb accuracy the flow rate of air, oxygen, or other non-aggressive gases. Sensirion has designed the flow channel in a special way so that introduction of the flow meter into a flow system results in a very low-pressure drop. These characteristics of the SFM3000 make it extremely suitable for use in applications that are very demanding, such as in respiratory and medical ventilation systems.

Operating the SFM3000 is very easy, as the flow meter operates off a 5 VDC supply voltage. It also features a 2-wire digital I2C interface for connecting with the controller. Sensirion has designed the flow meter such that it automatically linearizes and temperature compensates all measurement results internally.

A CMOSens sensor technology, patented by Sensirion, is the basis of the outstanding performance of the sensor. They have combined the sensor element, signal processing electronics, and digital calibration within a single microchip. A thermal sensor element measures the flow rate of the gas, and this also ensures that the signal processing is done at a high speed. The innovative measuring technique also makes it possible to make bidirectional measurements, while offering the best-in-class accuracy.

The CMOS technology is well-proven and is a perfectly suited method for high-quality mass production of the SFM3000 flow meter in a demanding and cost-sensitive market. Sensirion offers a variety of custom options for implementing the flow meter for high-volume OEM applications. They offer options like different body form factor, calibration for other gases, custom flow rates, and many more.

Applications of the SFM3000 low-pressure drop digital flow meter include laboratory use, environment monitoring, spectroscopy, fuel cell control, burner control, process automation, and medical use.

Sensirion has used a silicon sensor chip SF05 of the fifth generation in the design of the SFM3000 flow meter. It also has a sensor element to detect the flow of thermal mass. In addition to the two above, there is an amplifier, an analog to digital converter, read-only memory, digital circuitry for signal processing, and the digital I2C interface. Sensirion has achieved significant cost benefits and performance achievements with the seamless integration of the circuitry for acquiring the signal and processing it on a single silicon die.

Users can solder the SFM3000 sensor using standard selective soldering systems. However, they must not use reflow soldering as it may damage the sensor. During soldering, the user must protect the sensor ports from solder splash and flux. As the characteristics of machines for selective soldering may vary, the user must test the soldering arrangement before production use.

For soldering, Sensirion provides the mask drawing of the sensor for a reliable PCB attachment. For a sturdy integration of the sensor, the user must consider using the screw holes of the SFM3000. The fittings of the sensor correspond to the international standard ISO5356-1:2004.

Smart Sensors from Sensirion

Sensirion is offering three smart sensors that make it easy for electronic system designers to incorporate them into their applications. These are the AMT4x Smart Gadget, the SCD30 Sensor Module, and the STC31 Thermal Conductivity Sensor for CO2.

As a simple circuit board for a reference design, the AMT4x Smart Gadget from Sensirion is a demonstration kit for the SHT4x temperature and humidity sensors. The gadget displays information for temperature and humidity on an LCD screen. The built-in BLE or Bluetooth Low Energy module allows communication with smartphones and other Bluetooth-enabled devices.

The kit for the Smart Gadget includes an SHT40 sensor for temperature and humidity, a liquid crystal display, a push button, a Bluetooth MCU module, batteries, and other supports. Sensirion also provides detailed resources for the hardware design and information for an app download.

The Smart Gadget offers designers a simple reference design along with a circuit board. They can use it for measuring temperature and humidity while displaying it on an LCD, The MyAmbiance app for iOS and Android phones enables remote access and export capabilities along with data logging.

To sense CO2, Sensirion is offering their SCD30 Sensor Module. SCD30 uses the NDIR sensor technology for sensing CO2. It also has an integrated humidity and temperature sensor. The sensor measures the humidity and temperature in the ambient atmosphere while monitoring and compensating for external heat sources, without using any additional components. The height of the sensor module is low, and this allows easy integration in systems for various applications. The SCD30 achieves high accuracy and superior stability with its dual-channel capability.

The SCD30 sensor, with its NDIR CO2 sensor technology, and integrated humidity and temperature sensor, offers outstanding stability owing to the compensation from long-term drifts provided by its dual-channel capability. The sensor has a small form factor of 35 x 23 x 7 mm. Its measurement range covers 400 to 10,000 ppm, with an accuracy of ±30 ppm +3%. Apart from measuring the absolute concentration of carbon dioxide, the sensor can also measure temperature and relative humidity.

Applications of the SCD30 sensor include IoT devices, Smart Homes, Air purifiers, Air conditioners, HVAC equipment, and demand-controlled ventilation systems.

Sensirion also offers the STC31, a thermal conductivity sensor for the detection and measurement of Carbon dioxide. The gas concentration sensor is chip-sized, offers 16-bit resolution for high range, and is accurate for high volume production CO2 measurement.

Sensirion has based the sensor on an innovative principle of thermal conductivity measurement, which results in long-term stability and superb repeatability. With a digital I2C interface, the STC31 sensor can directly interface with a microprocessor. Working from a voltage ranging from 2.7 to 5 VDC, and a 5 mA maximum current rating, the STC31 sensor operates ideally from batteries while delivering top performance at minimal power budgets.

The STC31 is RoHS and REACH compliant, and its measurement range covers 20 to +85 °C. At a measurement rate of 1 reading per minute, the sensor consumes only 15 µW of power. With a track record of above 15 years, the STC31 sensor is an industry-proven technology.