Category Archives: Sensors

Sensors at the Heart of IoT

IoT, or the Internet of Things, depends on sensors. So much so, there would not be any IoT, IIoT, or for that matter, any type of Industry 4.0, at all, without sensors. As the same factors apply to all the three, we will use IoT as a simplification. However, some basic definitions first.

As a simple, general definition, IoT involves devices intercommunicating with useful information. As their names suggest, for IIoT and Industry 4.0, these devices are mainly located in factories. While IIoT is a network of interconnected devices and machines on a plant floor, Industry 4.0 goes a step further. Apart from incorporating IIoT, Industry 4.0 expands on the network, including higher level systems as well. This allows Industry 4.0 to process and analyze data from IIoT, while using it for a wider array of functions, including looping it back into the network for control.

However, the entire network has sensors as its basis, supplying it with the necessary raw data. Typically, the output from sensors is in the form of electrical analog signals, and IoT creates the fundamental distinction between data and information.

This distinction is easier to explain with an example. For instance, a temperature sensor, say, a thermistor, shows electrical resistance that varies with temperature. However, that resistance is in the form of raw data, in ohms. It has no meaning to us, until we are able to correlate it to degrees.

Typically, we measure the resistance with a bridge circuit, effectively converting the resistance to voltage. Next, we apply the derived voltage to a measuring equipment that we have calibrated to show voltage as degrees. This way, we have effectively converted data into information useful to us, humans. However, we can still use the derived voltage to control an electric heater or inform a predictive maintenance system of the temperature of a motor.

But information, once we have derived it from raw data, has almost endless uses. This is the realm of IoT, intercommunicating useful information among devices.

To be useful for IoT, we must convert the analog data from a sensor to a digital form. Typically, the electronics required for doing this is the ADC or Analog to Digital Converter. With IoT applications growing rapidly, users are also speeding up their networks, thereby handling even larger amounts of data, making them more power efficient.

Scientists have evolved a new method for handling large amounts of data that does not require the IoT devices to have large amounts of memory. The devices send their data over the internet to external data centers, the cloud. There, other computers handle the proper storing and analysis of the data. However, this requires higher bandwidth and involves latency.

This is where the smart sensor makes its entry. Smart sensors share the workload. A sensor is deemed smart when it is embedded within a package that has electronics for preprocessing, such as for signal conditioning, analog to digital conversion, and wireless transmission of the data. Lately, smart sensors are also incorporating AI or Artificial Intelligence capabilities.

What are Olfactory Sensors?

We depend on our five senses to help us understand the world around us. Each of the five senses—touch, sight, smell, hearing, and taste—contributes individual information to our brains, which then combines them to create a better understanding of our environment.

Today, with the help of technology like ML, or machine learning, and AI, or Artificial Intelligence, we can make complex decisions with ease. ML and AI also empower machines to better understand their surroundings. Equipping them with sensors only augments their information-gathering capabilities.

So far, most sensory devices, like proximity and light-based ones, remain limited as they need clear physical contact or line of sight to function correctly. However, with today’s technology trending towards higher complexity, it is difficult to rely solely on simple sensing technology.

Olfaction, or the sense of smell, functions by chemically analyzing low concentrations of molecules suspended in the air. The biological nose has receptors for this activity, which, on encountering these molecules, transmit signals to the parts of the brain that are responsible for the detection of smell. A higher concentration of receptors means higher olfaction sensitivity, and this varies between species. For instance, compared to the human nose, a dog’s nose is far more sensitive, allowing a dog to identify chemical compounds that humans cannot notice.

Humans have recognized this superior olfactory ability in dogs and put it to various tasks. One advantage of olfaction over that of sight is the former does not rely on line-of-sight for detection. It is possible to detect odors from unseen objects, which may be obscured, hidden from sight, or simply not visible. That means the olfactory sensor technology can work without requiring invasive procedures. That makes olfactory sensors ideally suited for a range of applications.

With advanced technology, scientists have developed artificial smell sensors to mimic this extraordinary natural ability. The sensors can analyze chemical signatures in the air, and thereby unlock newer levels of safety, efficiency, and early detection in places like the doctor’s office, factory floors, and airports.

The healthcare industry holds the most exciting applications for olfactory sensors. This is because medical technology depends on early diagnosis to provide the most effective clinical outcomes to patients. Conditions like diabetes and cancer cause detectable olfactory changes in the body’s chemistry. Using olfactory sensors to detect the changes in body odor, with their non-invasive nature, provides a critical early diagnosis that can significantly improve the chances of effective treatment and recovery.

The industry is also adopting olfactory sensors. Industrial processes often produce hazardous byproducts. With olfactory sensors around, it is easy to monitor chemical conditions in the air and highlight the buildup of harmful gases that can be dangerous beyond a certain level.

As the sense of smell does not require physical contact, it is ideal for detection in large spaces. For instance, olfactory sensors are ideal for airport security, where they can collect information about passengers and their belongings as they pass by. All they need is a database of chemical signatures along with processing power to analyze many samples in real-time.

IoT Sensor Design

Individuals are progressively integrating electrical components into nearly every system possible, thereby imbibing these systems with a degree of intelligence. Nevertheless, to meet the intelligence requirements posed by diverse business applications, especially in healthcare, consumer settings, industrial sectors, and within building environments, there is a growing necessity to incorporate a multitude of sensors.

These sensors now have a common name—IoT or Internet of Things sensors. Typically, these must be of a diverse variety, especially if they are to minimize errors and enhance insights. As sensors gather data through sensor fusion, users build ML or Machine Learning algorithms and AI or Artificial Intelligence around sensor fusion concepts. They do this for many modern applications, which include advanced driver safety and autonomous driving, industrial and worker safety, security, and audience insights.

Other capabilities are also emerging. These include TSN or time-sensitive networking, with high-reliability, low-latency, and network determinism features. These are evident in the latest wireless communication devices conforming to modern standards for Wi-Fi and 5G. To implement these capabilities, it is necessary that sensor modules have ultra-low latency at high Throughput. Without reliable sensor data, it is practically impossible to implement these features.

Turning any sensor into an IoT sensor requires effectively digitizing its output while deploying the sensor alongside communication hardware and placing the combination in a location suitable for gathering useful data. This is the typical use case for sensors in an industrial location, suitable for radar, proximity sensors, and load sensors. In fact, sensors are now tracking assets like autonomous mobile robots working in facilities.

IoT system developers and sensor integrators are under increasing pressure to reduce integration errors through additional processing circuits. Another growing concern is sensor latency. Users are demanding high-resolution data accurate to 100s of nanoseconds, especially in proximity sensor technologies following the high growth of autonomous vehicles and automated robotics.

Such new factors are leading to additional considerations in IoT sensor design. Two key trends in the design of sensors are footprint reduction and enhancing their fusion capabilities. As a result, designers are integrating multiple sensors within a single chip. This is a shift towards a new technology known as SoC or system-on-chip.

Manufacturers are also using MEMS technology for fabricating sensors for position and inertial measurements such as those that gyroscopes and accelerometers use. Although the MEMS technology has the advantage of fabrication in a semiconductor process alongside digital circuits, there are sensors where this technology is not viable.

Magnetic sensors, high-frequency sensors, and others need to use ferromagnetic materials, metastructures, or other exotic semiconductors. Manufacturers are investing substantially towards the development of these sensor technologies using SiP or system-in-package modules with 2D or 2.5D structures, to optimize them for use in constrained spaces and to integrate them to reduce delays.

Considerations for modern sensor design also include efforts to reduce intrinsic errors that affect many sensor types like piezoelectric sensors. Such sensors are often prone to RF interference, magnetic interference, electrical interference, oscillations, vibration, and shock. Designers mitigate the effect of intrinsic errors through additional processing like averaging and windowing.

The above trends are only the tip of the iceberg. There are many other factors influencing the growing sensor design complexity and the need to accommodate better features.

Touch-sensing HMI

The key element in the consumer appeal of wearable devices lies in their touch-sensing HMI or human-machine interface—it provides an intuitive and responsive way of interacting via sliders and touch buttons in these devices. Wearable devices include earbuds, smart glasses, and smartwatches with a small touchscreen.

An unimaginable competition exists in the market for such types of wearable devices, continually driving innovation. The two major features over which manufacturers typically battle for supremacy and which matter particularly to consumers are—run time between battery charges, and the form factor. Consumers typically demand a long run-time between charges, and they want a balance between convenience, comfort, and a plethora of features, along with a sleek and attractive design. This is a considerable challenge for the designers and manufacturers.

For instance, while the user can turn off almost all functions in a wearable device like a smartwatch for long periods between user activity, the touch-sensing HMI must always remain on. This is because the touch intentions of the user are randomly timed. They can touch-activate their device any time they want to—there is no pattern that allows the device to know in advance when the user is about to touch-activate it.

Therefore, the device must continuously scan to detect a touch for the entire time it is powered up, leading to power consumption by the HMI subsystem, even during the low-power mode. The HMI subsystem is, therefore, a substantial contributor to the total power consumed by the device. Reducing the power consumption of the touch system can result in a substantial increase in the run-time between charges of the device.

Most wearable devices use the touch-sensing HMI as a typical method for waking up from a sleep state. These devices generally conserve power by entering a low-power touch detect function that operates it in a deep sleep mode. In this mode, the scanning takes place at a low refresh rate suitable for detecting any kind of touch event. In some devices, the user may be required to press and hold a button or tap the screen momentarily to wake the device.

In such cases, the power consumption optimization and the amount of power saved significantly depends on how slow it is possible to refresh the sensor. Therefore, it is always a tradeoff between a quick response to user touch and power consumption by the device. Moreover, touch HMI systems are notorious for the substantial amount of power they consume.

Commercial touch-sensing devices typically use microcontrollers. Their architecture mostly has a CPU with volatile and non-volatile memory support, an AFE or analog front-end to interface the touch-sensing element, digital logic functions, and I/Os.

The scanning operation typically involves CPU operation for initializing the touch-sensing system, configuring the sensing element, scanning the sensor, and processing the results to determine if a touch event has occurred.

In low-power mode, the device consumes less power as the refresh rate of the system reduces. This leads to fewer scans occurring each second, only just enough to detect if a touch event has occurred.

Ultrasonic Sensors in IoT

For sensing, it has been a standard practice to employ ultrasonic sensors. This is mainly due to their exceptional capabilities, low cost, and flexibility. With IoT or the Internet of Things now virtually entering most industries and markets, one can now find ultrasonic sensors in newer applications in healthcare, industrial, and smart offices and homes.

As their name suggests, ultrasonic sensors function using sound waves, especially those beyond the hearing capability of humans. These sensors typically send out chirps or small bursts of sound in the range of 23 kHz to 40 kHz. As these chirps bounce back from nearby objects, the sensor detects them. It keeps track of the time taken by the chirp for a round trip and thereby calculates the distance to the object based on the speed of sound.

There are several benefits from using ultrasonic sensors, the major one being very accurate detection of the object. The effect of material is also minimal—the sensor uses sound waves and not electromagnetic waves—the transparency or color of the object has minimum effect on the readings. Additionally, this also means that apart from detecting solid objects, ultrasonic sensors are equally good at detecting gases and liquid levels.

As ultrasonic sensors do not depend on or produce light during their operation, they are well-suited for applications that use variable light conditions. With their relatively small footprints, low cost, and high refresh rates, ultrasonic sensors are well-established over other technologies, like inductive, laser, and photoelectric sensors.

According to a recent study, the smart-office market will likely reach US$90 billion by 2030. This is mainly due to a surging demand for sensor-based networks, brought about by the need for safety and advancements in technology. Ultrasonic sensors will be playing an expanded role due to industry and local regulations supporting increased energy efficiency for automating different processes around the office.

A prime example of this is lighting and HVAC control in offices. Ultrasonic sensors are adept at detecting populated rooms in offices all through the day. This data is useful in programming HVAC systems, for keeping rooms hot or cool when populated, and turning the system off at the end of the day, kicking back on at first arrival.

Similarly, as people enter or leave rooms or areas of the office, ultrasonic sensors can control the lights automatically. Although the process looks simple, the energy savings from cutting back on lighting and HVAC can be huge. This is especially so for large office buildings that can have many unoccupied office spaces. For sensing objects across large areas, ultrasonic sensors offer ideal solutions, with detecting ranges of 15+ meters and detecting beam angles of >80°.

Additionally, smart offices can also have other smart applications like hygiene and touchless building entry devices. Touchless devices include automatic door entries and touchless hygiene products include faucets, soap dispensers, paper towel dispensers, and automatically lifting waste bin lids. During the COVID-19 pandemic, people’s awareness of these common applications has increased as public health and safety became critical for local offices and businesses.

Battery-Free Metal Sensor IoT Device

Many industrial, supply chain and logistics applications require advanced monitoring of temperature, strain, and other parameters during goods transfer. One of the impediments of such requirements is a battery-powered device, typically involving its cost and maintenance overheads. A global leader in digital security and identification in the IoT or Internet of Things, Identiv, Inc., has developed a sensory TOM or Tag on Metal label, collaborating with Asygn, a sensor and IC specialist from France. The advantage of this sensory label is it operates without batteries.

The new sensor label is based on the next-generation IC platform of Asygn, the AS321X. They can capture strain and temperature data near metallic objects. The AS321X series of UHF or ultra-high frequency RFID or radio-frequency identification chips is suitable for sensing applications and can operate without batteries. Identiv has partnered with Asygn to expand its portfolio of products. It now includes the new sensor-based UHF inlays compliant with RAIN RFID standards, enabling the identification of long-range products and monitoring their condition.

According to Identiv, their advanced RFID engineering solutions, combined with Asygn’s sensing IC platform, have created a unique product in the industry. Taking advantage of their production expertise, and the latest sensor capabilities of Asygn, these new on-metal labels from Identiv offer the first exclusive, on-metal, battery less sensing solution in the market.

Using their connected IoT ecosystems, Identiv can create digital identities for every physical object by embedding RFID-enabled IoT devices, labels, and inlays into them. Such everyday objects include medical devices, products from industries like pharmaceuticals, specialty retail, luxury brands, athletic apparel, smart packaging, toys, library media, wine and spirits, cold chain items, mobile devices, and perishables.

RFID and IoT are playing an increasing role in the complex and dynamic supply chain industry. The integration of RFID with IoT is developing automated sensing, and promoting seamless, interoperable, and highly secure systems by connecting many devices through the internet. The evolution of RFID-IoT has had a significant impact on revolutionizing the SCM or Supply Chain Management.

The adoption of these technologies is improving the operational processes and reducing SCM costs with their information transparency, product traceability, flexibility, scalability, and compatibility. RFID-IoT is now making it possible to interconnect each stage in the SCM to ensure the delivery of the right process and product at the right quantity and to the right place. Such information sharing is essential for improving coordination between organizations in the supply chain and improving their efficiency.

Combining RFID and IoT makes it easier to identify physical objects on a network. The system transmits raw data about an item’s location, status, movement, temperature, and process. IoT provides the item with an identification ID for tracking its physical status in real-time.

Such smart passive sensors typically power themselves through energy harvesting, specifically RF power. Each sensor is battery-free and has an antenna for wireless communication. As an RF reader interrogates a sensor, it uses the energy from the signal to transmit an accurate and fast reading. Many sensors form a hub that collects their data while communicating with other connected devices.

FIR Temperature Sensor

Among the many things that the COVID-19 pandemic taught us was the technique of assessing the human body temperature non-invasively. This was used in several locations, including hospitals, schools, and airports, employing an infrared sensor for measuring the surface temperature without making physical contact. Now, this is a popular method used commonly for taking body temperature. While being non-invasive, infrared thermometers also provide quick and reliable readings.

The accuracy of the infrared thermometer technique was affected by variables including the nature of the surface under measurement and its surroundings. However, scientists have largely resolved these issues, attaining medical-grade accuracy and compensation. In the process, they have also successfully lowered the size of the thermometer. Accordingly, Melexis Microelectronic Integrated Systems have developed a miniature infrared temperature sensor.

Based in Belgium, Melexis specializes in ICs and microelectronic sensors for applications involving consumer, automotive, digital health, smart devices, and energy management. For instance, Samsung is using one of Melexis’s products, the MLX90832 temperature sensor that works on FIR or far-infrared technology, for their GW5 smartwatch. The medical-grade version of the Melexis temperature sensor allows menstrual cycle tracking. Such continuous but reliable temperature monitoring opens up a vast range of newer applications in health, sports, and other domains.

The FIR sensor from Melexis is an SMD or surface-mount device that can accurately measure an object’s infrared radiation to record its temperature. The SMD packaging makes the sensor suitable for a large variety of applications, such as wearables, including hearables or in-ear devices, and point-of-care clinical applications that require highly accurate human-body temperature measurement.

Non-contact temperature measurement has several advantages over the more traditional contact methods. It can be helpful in several circumstances where making physical contact is undesirable, such as when the object is fragile, located in a dangerous area, or moving. It is helpful when a quick response is desirable, or when it is not possible to guarantee an excellent thermal contact between the object under test and the sensor. Moreover, the technique of measuring temperature without contact can be more accurate and yield results that are more reliable than contact temperature measurement methods.

The extremely small 3 x 3 x 1 mm3 QFN package of the Melexis MLX90832 is a full-solution device that incorporates the optics, a sensor element, digital signal processing, and digital interfacing, providing a quick and simple integration for a wide range of modern applications within a limited space.

With factory calibration, the MLX90832 offers high accuracy, while Melexis has ensured thermal and electrical precautions internally so that the device has adequate compensation when operating in thermally harsh external conditions. Internally, the voltage signal from the thermopile element undergoes amplification and digitization. After undergoing digital filtering, the raw measurement data resides in the RAM of the device. All the functions remain under the control of a state machine. An I2C interface makes available the results of each measurement conversion, while allowing access to the control registers of the internal state machines, the RAM for auxiliary measurement data and pixel readings, and the E2PROM for calibration constants, the trimming values, and other measurement/device settings.

Hall Effect Sensors for Position Selection

User systems often require the detection of position for operating in a specific switch mode. Such type of On or Off functionality is a straightforward requirement and many devices implement it with Hall-effect switches, including power tools, light switches, safety harnesses, and laptop lids.

The output of the sensor toggles its state as soon as the input magnetic field crosses the operating threshold. Likewise, the output reverts to the idle state when the magnitude of the magnetic field reduces below the release threshold. Hysteresis built into the device prevents the output from toggling rapidly where the magnitude of the magnetic field is close to the operating threshold.

Many applications use this functionality. For typical cases, two output states are adequate, thereby helping to reduce mechanical wear and preventing interference from grease and dust.

Although two positions may be adequate for detection in many applications, others require the detection of additional states. For instance, a tool may require a three-position power switch, denoting Off, Low, and High power modes. Detecting all three states is difficult using a single sensor. Initially, it may seem possible by adding a sensor for every switch position in the system.

A unipolar switch is well-suited for such an application. The designer places the magnet very close—so the air gap is small—thereby ensuring the pole of the magnet facing the sensor will always exceed the worst-case operating point. When the magnet is above the sensor, it results in an upwardly directed field vector. When the magnet has traveled greater than its own width, the sensor will not activate, as the direction of the field is now downwardly directed. Therefore, there can be an array of sensors representing any number of positions, provided the sensor spacing exceeds the full width of the magnet.

While the above arrangement is convenient for a low number of positions, the number of components required gets more difficult to manage as the number of positions increases. For such arrangements, dual-unipolar switches are more convenient.

Texas Instruments offers a dual-unipolar switch, DRV5032DU. It has two independently operating outputs. Each output is sensitive to an opposite polarity of the magnetic field. Where one sensor responds as it nears a North pole, the other will respond as it nears a South pole. This functionality allows the detection of three positions with a single magnet.

With the magnet mid-way between the two sensors, there is no component of the magnetic field available to activate the sensors, and therefore, both sensors remain deactivated. When the magnet moves to the left, it activates the N pole-sensitive output. Likewise, when the magnet moves to the right, the S pole-sensitive output activates. However, for this arrangement to function correctly, the magnet must have a length two times the distance of travel between the switch positions. When the magnet moves by one-half its length, one of its poles is directly above the sensor, thereby activating it.

Extending this format makes it possible to sense more than three positions. It requires an array of sensors spaced appropriately for creating additional unique positions.

Modern RTD-Based Sensors

The popular belief is to not fix things that aren’t broken. The idea is to not tamper with something performing reliably and proving its worth. This advice aptly applies to circuit designs using RTD sensors that efficiently and quietly measure temperature in industrial manufacturing facilities worldwide.

However, in meeting the requirements of Industry 4.0, where smart factories are the norm, it is now evident that the current RTD sensors in use are not fitting the purpose. Automation engineers today want industrial temperature sensors to be of smaller form factors, flexible with communications, and capable of remote reconfigurability. Incumbent solutions, sadly, are unable to support them. However, it is possible to easily redesign these sensors to equip them with the necessary features to meet the new industrial design.

The RTD industrial temperature sensor translates temperature, a physical quantity, into an electrical signal. The typical range of such sensors is between -200 °C and +850 °C, with a highly linear response across it. RTDs commonly use metal elements like copper, nickel, and platinum. Among these, PT1000 and PT100 platinum RTDs are the most popular. While an RTD can use either two, three, or four wires, the 3-wire and 4-wire versions are the most popular. Being passive devices, RTDs require an excitation current for producing an output voltage. A voltage reference generates this current, with an operational amplifier acting as a buffer for driving the current into the RTD, which produces an output voltage signal varying in response to changes in temperature. The voltage signal may vary from tens to hundreds of millivolts depending on the type of RTD in use and the measured temperature.

An AFE or Analog Front End conditions and amplifies the low amplitude voltage signal from the RTD before the ADC or Analog to Digital converter digitizes it. A microcontroller runs an algorithm over the digitized signal, compensating for any non-linearity in it. The microcontroller then sends the processed digital output to a communications interface for transmission to a process controller. A typical implementation of the AFE is by a signal chain of components with each performing a dedicated function.

This discrete approach requires a large PCB or printed circuit board for accommodating all the ICs and power and signal routing, setting a minimum size for the sensor enclosure. Rather, modern RTD-based sensors use a superior and more minimal approach—the AD7124-4, an integrated AFE.

The AD7124-4 is a compact IC in a single package. It includes a multiplexer for accommodating multiple-wire RTDs, a voltage reference, a programmable gain amplifier, and an ADC using the sigma-delta operating principles. The IC has the capability to provide the necessary excitation currents for the RTD. The entire arrangement effectively replaces five of the signal-chain components from the traditional setup. Not only does this significantly reduce the amount of board space necessary, but it also enables the sensor to use a much smaller enclosure.

Next comes the communications interface. Modern RTD-based sensors typically use the IO-Link which eliminates the use of expensive ASICs for implementing specific network protocols. IO-Link is a 3-wire industrial communications standard for linking sensors and actuators with all industrial control networks.

Miniature Temperature Sensors

During the COVID19 pandemic, it became necessary to use quick and non-invasive techniques for assessing body temperature. Various locations that included airports, hospitals, schools, and shopping centers used non-contact thermometry. This essentially employs an infrared sensor for measuring the surface temperature but without any physical contact. Not only was this technique very popular, but it is now a typical way of taking body temperature. While providing quick and reliable readings, infrared thermometers are also non-invasive.

The accuracy of infrared thermometers largely depends on variables such as the nature of the surface it is measuring and its surroundings. However, Melexis Microelectronic Integrated Systems has now successfully resolved these problems. They have developed a miniature infrared temperature sensor that offers medical-grade accuracy and temperature compensation.

Melexis specializes in and offers several microelectronic ICs and sensors for various applications. Their sensors are applicable to consumer, automotive, digital health, energy management, and smart device industries. Samsung has deployed one of the Melexis products in their GWS smartwatch series. This is the medical-grade version of the MLX90632 temperature sensor, which operates on FIR or far-infrared technology. The enhanced accuracy of the MLX90632 temperature sensor along with its non-contact temperature measurement technique allows its use for menstrual-cycle tracking. A wide range of new and possible applications in health, sports, and other domains is now possible because of the reliable continuous temperature measuring capabilities of the sensor.

The MLX90632 FIR temperature sensor is an SMD or surface mount device that measures the infrared radiation from the object for reporting the temperature. As the sensor has a tiny SMD packaging, it is suitable for use in a variety of applications, especially in wearables, hearables or in-ear devices, and point-of-care clinical applications. All these applications require high accuracy for measuring the human body temperature.

In comparison to traditional contact methods of measuring temperature, the non-contact temperature measurement methods offer advantages, primarily as they enable sensing and measuring the temperature without directly touching the measured surface or object. This is helpful in specific circumstances where it is undesirable to make physical contact with the object, especially when the object may be fragile, under movement, or located in a hazardous area. When a quick response is necessary, or there is no guarantee of good thermal contact between the object and sensor, a non-contact temperature measurement technique is more accurate. It can also yield better and more reliable results as compared to what the contact temperature measurement techniques can.

The MLX90632 sensor is a minuscule device in a chip size of 3 x 3 x 1 mm QFN package. Within this tiny space, it incorporates the sensor element, the signal processing circuitry, digital interfacing circuitry, and optics. The small size enables quick and easy integration within a huge range of modern applications, typically with limited space.

Melexis calibrates its sensors in-house, thereby ensuring high accuracy. They compensate for harsh external thermal conditions with internal precautions for electrical and thermal operations. After amplifying and digitizing the voltage signal from the thermopile sensing element, the IC filters it digitally and stores the raw measurement data in its RAM. This is accessible via an I2C interface.