sensors

While flying cars have been a science fiction mainstay for decades, new sensors, software and other technology put personal air travel vehicles within reach. MEMS and Sensors Industry Group (MSIG) interviewed Dr. Alberto Speranzon, Fellow at Honeywell Aerospace Advanced Technology, about his upcoming keynote Sensors and Software Enabling Autonomy for Urban Air Mobility at the MEMS and Sensors Technical Congress (MSTC 2021) virtual event, April 13-15. Dr. Speranzon will discuss Honeywell’s challenges in enabling air taxis and the path forward to building out the necessary infrastructure. SEMI: People have dreamed of flying cars for decades. What has changed recently that makes them a near-term reality? Speranzon: There certainly are multiple factors that have contributed to pushing both new startups and established aerospace companies to make this dream a reality. Advances in battery technology are bringing electric aviation closer to being viable. There is still more to be done to achieve higher energy density in batteries, but already with today’s technology we can have vehicles that can fly from the suburbs to the downtown of a large U.S. city. At the same time, urbanization has created a lot of congestion, so finding new, efficient ways to move people and goods across megacities is becoming a critical need. Undeniably, the autonomous car industry has contributed to demonstrating that it is possible to achieve levels of automation and autonomy that were unimaginable just a few decades ago. The advances in sensing and computation required to make self-driving cars a reality is certainly going to help the aviation industry to develop autonomy in the air. SEMI: An air taxi must be highly sensorized. What types of sensors pose your biggest development challenge? Speranzon: Aircraft based on today’s battery systems simply cannot accommodate the size, power requirements and weight of sensors used by standard airliners. So there still is work to be done to reduce the SWaP (Size, Weight and Power) of these systems. Honeywell, for example, has developed a multipurpose radar, the IntuVue RDR-84K, that is only about the size of a paperback book. It can detect traffic, terrain and even weather, and was specially designed for air taxis and cargo UAS (unmanned aerial systems). Today, however, we still rely on human pilots to make the very complex decisions and, despite all the limitations that human eyes have, we do rely on them in a multitude of complex situations. There is also growing interest in integrating cameras into autonomous air taxis and similar platforms. Cameras can’t work alone, because they are affected by foggy, rainy and dim conditions. But they are lightweight, inexpensive, and require little power. That can make them very useful when combined with a compatible radar system like the RDR-84K. While these sensors bring new opportunities to the aerospace industry, they also pose some big challenges. For example, today’s state-of-the-art algorithms for image processing are machine learning algorithms called deep neural networks. They’re capable of extracting high-level information from pixels. But when it comes to aircraft certification, these algorithms face major hurdles. There is no software of this kind in any certified air vehicle, and it is unclear how regulators would certify neural network-based software components. Developers could avoid these new machine-learning algorithms and use standard computer vision methods instead. But they still face the challenge of deciding the type and quantities of images sufficient to declare the software “bug-free.” A similar set of questions will be also be true for radars, as they will be used to feed data more directly into the autonomy modules of future air taxis. So in the short term, we need to tackle the challenge of reducing the size and weight of sensors. But in parallel, we need to develop new ways to take advantage of machine learning: utilizing cameras and radars for autonomous decision making while still ensuring the highest standards of safety. SEMI: How is autonomous air mobility more or less challenging than autonomous ground vehicles? Speranzon: They are both challenging in their own ways. Autonomy on the ground – and I am thinking specifically of autonomous cars – is challenging as their “normal” behavior is very complex. We humans can drive from point A to point B over the public road network without a second thought. But to a machine, the heterogeneity of the people driving on the road, their sometimes unpredictable behavior, the changing weather conditions and shifting environments pose huge challenges. These things make what we call “normal driving” a very difficult problem to solve. At the same time, however, “off-nominal” scenarios in ground autonomy, while complex, are not orders of magnitude more complex than “nominal” scenarios. Ground vehicles can brake and stop, change lanes or move to the side of the road to avoid a crash or manage a malfunction. For autonomous air vehicles, the difference between nominal and off-nominal scenarios is more extreme. “Nominal” flying can rely on some of the existing aviation infrastructure, like communication between air traffic control and other aircraft. Air taxis can follow predefined paths and long-established aviation procedures as they move from vertiport A to vertiport B. This results in more automation than autonomy: everything is prescribed in advance and the onboard computer will follow what is pre-defined. Thus, nominal conditions will be fairly simple. However, in case of accidents or emergencies, aircraft face situations that are orders of magnitude more complex than nominal scenarios. An air vehicle cannot easily just “stop.” It could be 1,000-2,000 ft above ground, possibly above a bustling city. Human pilots go through rigorous training to be able to deal with emergencies like these. Consider the split-second judgments and airmanship behind the 2009 “miracle on the Hudson” landing. Asking autonomy to make the right decisions and execute emergency behaviors is a huge challenge. And these systems will need to be certified to the aviation industry’s very high standards. At present, we do not even have a well-established set of certification rules that an autonomous flying vehicle should comply with. SEMI: How soon might I be able to take an air taxi ride? Speranzon: Initial deployment of air taxis will happen around 2025. They will have human pilots but will use simpler interfaces than today’s cockpits. This first step will provide technologies that make it easier to take off and land, and to avoid traffic. That will reduce the need for highly experienced pilots and should help alleviate the overall shortage of pilots in the aviation industry. Fully autonomous air taxis are likely not going to show up until after 2030. In the beginning, they will likely fly only in regions where the weather is good most of the time. The autonomous car industry has already adopted this strategy, mostly deploying their technology in regions where the weather is dry and sunny. Soon, however, we’ll start seeing operations in “all-weather” scenarios and an increasing number of air vehicles within the same airspace. There is one critical stepping stone on the way to fully autonomous passenger aircraft: the success of fully autonomous cargo drones. For light parcels we will see initial deployments in 2022 or 2023, followed by larger UAS capable of transporting heaver cargo in 2024-2025. But whatever the timing, these are very exciting times. The aviation industry is witnessing a revolution with new vehicle manufacturers, new technologies and, likely, new applications we have not even dreamt of yet. Learn more about Honeywell’s work in urban air mobility and unmanned aircraft at aerospace.honeywell.com/uam. Alberto Speranzon is a Fellow within Honeywell Aerospace Advanced Technology. He received a Ph.D. in Electrical Engineering from the Royal Institute of Technology (KTH), Sweden in 2006. Since joining Honeywell, Alberto has been working on various aspects of autonomous systems for urban air mobility, leading such research areas as program manager and principal investigator. He is an IEEE Senior Member and a member of the Board of Governors of the IEEE Control Systems Society. Nishita Rao is product marketing manager at SEMI.

MEMS actuators transform electronic signals into something that can be sensed or touched by the end user of an electronics device. A case in point: MEMS actuators such as print heads in inkjet printers transform electronic files into text or beautiful images. In 3D printers, actuators can produce real objects. Inside smart glasses, tiny MEMS mirrors can create virtual objects. Little surprise, then, that integrating these powerful devices into the end products is a multidisciplinary enterprise. STMicroelectronics has been successfully leading the deployment of dedicated MEMS actuator solutions with customer products in various market segments. SEMI spoke with Anton Hofmeister, group vice president and general manager of the MEMS Actuator Division at STMicroelectronics, about MEMS actuator trends. Hofmeister shared his views at the SEMI MEMS Imaging Sensors Forum as part of the virtual SEMI Technology Unites Global Summit. Watch the STMicroelectronics’ presentation on-demand until March 26, 2021. Registration is open. SEMI: What is the difference between MEMS devices that sense and MEMS devices that actuate? Hofmeister: MEMS sensors gather data from the world around us including motion, pressure and air temperature and transform them into an electrical signal. Actuators work the other way round. They receive an electrical signal and transform it into some well-controlled actuation such as ejecting a fluid, moving a membrane or deflecting a laser beam. SEMI: How can MEMS actuators’ integration be simplified to be embedded in new applications so they appeal to consumers? Hofmeister: The challenge of integrating MEMS sensors into devices has been simplified by demo kits and evaluation boards, which customers use to embed the sensor into a system. MEMS actuators are more difficult to integrate. They often power the core function of a system and therefore require deep system understanding. Reference designs are a big step forward in simplifying integration. My presentation at the SEMI MEMS Imaging Sensors Forum showcased some examples. MEMS micro-mirror projection for augmented reality (AR) glasses is an example of a complex system that requires multiple types of components to function. Together with several partners, STMicroelectronics recently announced the LaSAR Alliance, which will develop reference designs to enable the AR glasses market. SEMI: MEMS sensors and actuators are considered the backbone of many consumer products. Are MEMS actuators also mostly used in automotive? Hofmeister: The widest use of MEMS actuators has so far been in print heads for inkjet printers. In recent years, we have seen actuators adopted in emerging applications ranging from piezo heads for 3D printers to MEMS mirrors for laser beam scanning systems or 3D sensing solutions for consumer applications. The first high-volume application in automotive will likely be MEMS mirrors for LIDAR systems. SEMI: What market growth trends do you see for MEMS sensors and actuators? Hofmeister: The sensorization trend, which aims to collect data from homes, cities, factories, cars and personal devices, continues to drive the adoption of sensors and actuators for a wide variety of applications. While the last wave of MEMS growth was triggered by one end product – the smartphone – the next wave will be driven by multiple applications and use cases in industrial, medical, automotive and personal electronics. SEMI: How can technology unite us? Hofmeister: In recent months, we have all experienced vividly how vital technology has become. MEMS, and semiconductors in general, are an integral part of many products and services that make our lives easier. Communications technologies have been particularly important during this pandemic, whether using the personal devices as our interface to the digital world or the complex infrastructure that they operate through. I hope that my participation at the summit helped increase awareness of the new possibilities and opportunities that technologies like MEMS actuators have to offer to create products and services that further improve people’s lives. Anton Hofmeister is group vice president at STMicroelectronics, general manager of the company’s MEMS Actuator Division and managing director of its German subsidiaries. Hofmeister has been with STMicroelectronics for more than 30 years, working in Germany, France, the U.S. and Italy. He has held managerial positions in key account management, product and strategic marketing, advanced R D and general management. For the past 10 years, he has managed various product divisions in the MEMS sector. Hofmeister has also served as a board member of the Singapore-based molecular diagnostics company Veredus Laboratories. Serena Brischetto is senior manager of Marketing and Digital Engagement at SEMI Europe.

The automotive industry is changing. Our vehicles are getting electrified, connected and automated. As this trend is accelerating, it’s having an impact on how semiconductor devices, including MEMS sensors, are designed and qualified for automotive. As automotive semiconductor designers carefully consider product definition, product validation, and long-term reliability, MEMS sensor suppliers are responding to new opportunities created by electrified and automated vehicles by developing inertial measurement units (IMUs) for automated driving as well as battery pressure monitoring sensors for Li-ion EV batteries. The most complex MEMS device of all The automotive MEMS IMU is probably the most complex MEMS device that will be used inside a vehicle. This type of IMU is a System-in-Package (SiP) comprised of multiple gyroscope and accelerometer sensing elements plus a signal processing ASIC, integrated into one package that creates an inertial sensor able to measure up to six degrees of freedom (6DoF): yaw, roll and pitch for rotational movements, and lateral, longitudinal and vertical acceleration for linear movements. Degrees of freedom in a vehicle For vehicles with Level 3 autonomy and above (per SAE definition), the IMU is mandatory for taking over the trajectory control of the vehicle in case other sensors, such as the camera, radar or LiDAR, become impaired. Should such a failure occur, the IMU will function as a guidance sensor to bring the car to a safe stop within a short period of time and distance. The IMU is also used to control the regular movement of the car while driving in automated mode. While IMU technology already exists for aerospace applications, there are significant challenges to adapting it for automotive. The automotive IMU requires high performance at costs that are compatible with the automotive industry. Because automotive life cycles are long, MEMS sensor suppliers must produce the device in high volume for an extended period of time. They must also guarantee the sensor’s performance and reliability over a 10- to 15-year lifetime with no maintenance or recalibration of the sensor required. Only a few MEMS suppliers have the capability and willingness to embark on this kind of journey. Electrification is creating new applications for MEMS sensors The conversion from internal combustion engines to electrified propulsion is going to affect the powertrain MEMS market. For example, pressure sensors used in engine management for air pressure and fuel pressure will simply go away with electrification. However, the use of large Li-ion batteries in electrified vehicles has created a new application for MEMS sensors. One of the known risks of Li-ion batteries is the small probability for a battery cell to go into a thermal runaway situation that will lead to a fire. The press has reported multiple cases of EV batteries catching fire. Thermal runway effects When it comes to thermal runaway events, every second counts. Detecting the event as early as possible enables the vehicle safety system to take all necessary measures to warn occupants of an imminent fire and activate timely countermeasures (e.g., trigger fire extinguisher and call fire brigade) to mitigate the impact of the fire. Published studies have shown that measuring the pressure inside the battery pack is a good indication that a thermal runaway is starting. The outgassing of a battery cell, plus a sudden rise in temperature, will increase pressure inside the battery pack, which will generate a pressure pulse. To detect such a pressure pulse, a MEMS pressure sensor must permanently measure the pressure inside the pack. It must also report to the battery management system any suspicious change in pressure, independent of atmospheric pressure changes. It’s important to keep this kind of sensor on all the time to detect any pressure anomaly in the system, even when the vehicle is completely off. NXP has developed a pressure sensor to specifically address this new safety application in EVs, and several automotive manufacturers are already using this solution. NXP battery pressure management sensor The quest for zero defects While the automotive industry is targeting zero fatalities as its ultimate goal, the semiconductor industry and module suppliers are targeting zero defects for each and every semiconductor device. For safety-critical automotive MEMS sensors complying with the Automotive Electronics Council (AEC) Q100 qualification for semiconductors, it’s necessary but clearly not sufficient to guarantee a zero defects production launch and long-term reliability of the device. To boost the reliability and robustness of automotive sensors, NXP has developed Above and Beyond (AaB), a new methodology that studies advanced reliability and robustness well ahead of the device’s qualification and production release. Based on risk-mitigation analysis, AaB consist of extensive testing, such as test-to-fail, corner lot testing, and new use-case testing combined with advanced statistics, all of which help NXP understand how these different parameters interact with each other. As sensor suppliers must integrate AaB into their project planning, it does add time and cost to the project. The upside is that this early investment pays off as long as weaknesses in the device can be detected and corrected before a production launch. Field failures, on the other hand, can lead to unplanned redesign and requalification of a device. Worst-case, they can lead to a recall campaign that costs a huge amount of money. We’re systematically using the AaB methodology at NXP for safety-critical MEMS sensors because its potential benefits far outweigh its costs. For more information about NXP MEMS sensors, register for the upcoming webinar series, MEMS to Market: Ingredients for Success, where NXP will discuss The Growing Importance of MEMS Reliability (May 5, 2021). Register by March 10 to watch all the webinars LIVE. Each webinar will also be available to watch on-demand at your convenience. Contact the author via LinkedIn or learn more about NXP sensors. About the Author With nearly 30 years of experience in the field of automotive and MEMS sensors, Marc Osajda is responsible for European automotive MEMS sensors business development activities at NXP Semiconductors. Osajda holds an engineering degree in mechanics and electronics from the French Ecole Nationale Superieure d’Arts et Métiers (ENSAM). NXP Semiconductors is an active member of MEMS Sensors Industry Group®(MSIG), a SEMI technology community that connects the MEMS and sensors supply network in established and emerging markets to enable members to grow and prosper. Visit us today.

The air we breathe is precious yet neglected as anthropogenic pollutants continue to pour into the earth’s atmosphere. Still, there’s hope that greenhouse gas emissions – and the human behavior behind them – can be brought under control for the good of the planet with the help of gas sensors that gauge pollutant levels.Of the many air pollutants, some are more detrimental to our health than others. Figure 1 lists the top seven pollutants, their chief sources and health effects. The Air Quality Index is calculated by combining values from particles and four gases (carbon monoxide, ozone, sulfur dioxide, nitrogen dioxide). The good news is that gas sensors are available in the market that can monitor each of those pollutants.Figure 1 – Top seven pollutants and their health effects. Source: EPA Air Sensor Guidebook The challenge is that many gas sensor end users today have little understanding of how to compare the performance characteristics of sensors offered by various vendors. SEMI is working to help end users clear that hurdle. SEMI-MSIG this year created a group within its Device Working Group focused on developing gas sensor standards aimed at growing the market and defining guidelines affecting areas including testing methods, reliability requirements, packaging and communication interfaces. Importantly, the standards will also make it easier for end users to make a clear choice among rival products.The SEMI-MSIG Device Working Group comprises devoted experts from leading gas sensor companies as well as OEMs. We welcome companies involved in deploying gas sensors to join this fast-growing group to improve air quality standards in sectors including residential construction, factory automation, automotive, consumer electronics and healthcare. One potential market is consumer electronics such as smart phones since concerns about air quality is growing among device users.The MEMS Sensors Industry Group (MSIG) Device Working group was formed in early 2019. Its mission is to develop a series of technical specifications, industry standards and best practices for MEMS and Sensor devices and platforms. The goal is to advance the use and expansion of MEMS and sensors worldwide.Table 1 – Top seven pollutants and their health effects. Source: EPA Air Sensor Guidebook In the past, we focused on inertial sensors (See IEEE2700 standard for inertial sensors as an example of an output of this team). In 2020, our focus shifted to gas sensors and we plan to expand our work to include other types of sensors in the near feature. Industry leaders such as Bosch, TDK Invensense, Renesas, Infineon, Analog devices, STMicroelectronics, GE and Intel meet every month to strategize on a series of initiatives.If you’re interested in joining the SEMI-MSIG Device Working Group, please contact Carmelo Sansone, Director of MEMS Sensors Industry Group.The MEMS Sensors Industry Group (MSIG) is a SEMI technology community that enables the MEMS and sensor industry to address common challenges, innovate and accelerate business results.Carmelo Sansone is director of the SEMI-MSIG. He has focused his career on building products and system solutions that have large impact in the marketplace. Sansone launched several sensor processor platforms for low-power applications, including the first microcontrollers with DSP capabilities, the core of today’s portable devices intelligence. Sansone has led the successful integration of the MSIG organization into SEMI by expanding its services and global reach. Carmelo holds a master’s degree in Electronic Engineering with a specialization in Biomedical from the University of Pisa and an MBA from Golden Gate University, San Francisco.

Not long after STMicroelectronics opened its first semiconductor plant in Singapore more than 50 years ago, a facility chiefly focused on chip assembly and packaging, the company realized that it had constructed the site in an area with a blossoming chip ecosystem with a bright future. Before long, the company became the first to start a wafer fab facility in the so-called Little Red Dot. Today, our STMicroelectronics Singapore campus sports several buildings that dwarf the original site in the sprawling Ang Mo Kio Industrial Park 2. The facilities feature advanced 200mm manufacturing lines but still produce huge volumes of chips with more than 1,000 pieces of 150mm manufacturing equipment.Much of the wafer equipment dates back to the past century so is no longer supported by the manufacturers, if they’re still even in existence. Yet decades later the chipmaking gear continues to operate with a surprising reliability that far surpasses the longevity called for in its manufacturing specifications thanks to replacement parts and frequent upgrades with more sophisticated handling robots and chucks. Now, as smart manufacturing begins to establish a foothold in the semiconductor industry, Industry 4.0 technology is breathing new life into these aging workhorses.Despite its age, all of the equipment adheres to industry manufacturing standards. The gear is remotely controlled using the SECS/GEM interface protocol that was either originally integrated with the equipment controller or custom-made. We’ve also maximized its usage through advanced recipe management, advanced alarm and event handling, and secured lot identification.Crucially, we decided to systematically deploy a real-time fault detection and classification (FDC) solution using a third-party product based on what today is known as an edge computing architecture. Every piece of critical processing equipment is progressively paired with its dedicated FDC instance running on a virtual machine in the wafer fab data center, and the FDC solution monitors vital equipment parameters at high frequency – depending on the SECS/GEM capabilities of the equipment – and analyzes incoming manufacturing data in real time using classic SPC (statistical process control) algorithms and even AI-class protocols.Our use of the FDC edge solution as a sensor signal aggregator has given our equipment a second life. The solution processes real-time signals from sensors connected through a typical TCP-IP. Sensors have been the old equipment’s saving grace with their ability to de-multiply equipment capabilities and overcome fundamental shortcomings and design weaknesses. The STMicroelectronics Singapore plant first used off-the-shelf sensor nodes with built-in power amplifier and analog input nodes. While very practical and easy to implement, deploying the nodes can be costly. After developing more expertise in sensor integration using FDC, our wafer fab equipment experts decided to design an in-house solution based on the famed STM32 microcontroller. Leveraging Arduino – an open-source electronics platform with easy-to-use hardware and software – the equipment teams can now design and program a variety of in-house sensors for measurements including temperature, humidity, waterflow and pressure. The sensors are integrated with process equipment using the FDC solution. Integrating the sensors with the FDC engine on the edge computer extends the capabilities of old equipment without jeopardizing the integrity of the machines themselves. While the integration can be quick, it must be robust to ensure the reliability of the new measurements. Similarly, ever-increasing connectivity requirements present clear cybersecurity risks that must be managed upfront and each solution must be hardened to minimize security vulnerabilities. Even so, the challenges and risks pale in comparison to the benefits! Jean-Marc PHILIPPE is DIT Director at STMicroelectronics Pte Ltd. He oversees the deployment and support of Digital Solutions to enable STMicroelectronics front-end operations in Singapore and manages manufacturing productivity and automation programs at site level.

Innovations in the public sector are springboards for new products in digital health and personalized medicine. Since 2013, SEMI NBMC, funded by the Air Force Research Laboratory (AFRL), has been evaluating industry needs and soliciting proposals for new research into the foundations of device development and manufacturing of medically actionable devices.SEMI NBMC has run 17 separate programs with more than two dozen organizational participants developing materials, electronics, microfluidics, manufacturing processes and algorithms to create low-cost, wearable sensors. Most of these integrated sensing systems communicate wirelessly and incorporate high-performance silicon devices that are designed to move with the individual. Each of the projects was the result of a proposal received during NBMC’s annual proposal cycle. ​What’s Next in MedTech Device Development?We invite you to join the teams at SEMI, NBMC and AFRL to answer that question in a virtual series of sessions over the four weeks in August.For the past five years, NBMC has been conducting similar sessions for roadmapping the development of non-invasive human performance monitoring technology and manufacturing. The information feeds into the topics for upcoming RFPs, including the one we expect to release in September 2020. Previous Workshops (formerly entitled Blood Sweat and Tears) brought together industry and university innovators to explore current product research and provided excellent insights for the proposal evaluation teams. We believe the insights are also very useful to the business and technology planning direction for researchers and developers working on these products.Our focus is on early-adopting markets – medical professionals and their patients, Army and Air Force personnel and high-performance athletes.​ In this time of social-distancing and overall hesitancy to approach hospitals and medical offices, medical monitoring that provides medically-actionable intelligence is of even greater significance.But Doesn’t FitBitTM Have that Covered?Advancements are coming fast and furious – but medical professionals and insurance companies are struggling to distinguish innovations that provide actionable intelligence from those that provide generalized, non-actionable data.The workshop will focus on the medically relevant information that requires a great deal more accuracy, testing and certification before decisions are made. It is the innovations in this field that will lay the groundwork for new products in digital health and personalized medicine. Additionally, they are leading to advancements in aeromedical monitoring and diagnostics to support the U.S. Air Force’s mission to improve patient care during emergency air transport. The targeted future state is real-time monitoring of biochemical and physiological markers that can guide optimization of human performance and health. ​The SMART MedTech Virtual Workshop Series will link markets with manufacturing for medical relevancy – addressing both ends of the ecosystem. This forum will bring together the players across the growing range of industries that are entering or advancing human monitoring applications to:​ share competitive ideas that may be applied to product development​, assess roadblocks in bringing human monitoring products to market, and form partnerships that have become key in overcoming obstacles to successful manufacturing and product development. ​ Join the experts who are at the cutting edge of product design and manufacturing techniques. Indeed, the success of previous workshops was based on the unique membership of NBMC, where product and manufacturing-oriented engineers from industry, universities, and government labs form teams and pool resources (financial as well as technical) to accelerate human monitoring product development into manufacturing prototypes.Can’t Attend the Workshop?All sessions will be recorded and available for watching and re-watching on-demand. Join our interest list to receive regular updates on SEMI NBMC activities, including notification of the RFP expected to be available in October 2020.Find out more about the Smart MedTech Initiative and the NBMC Programs at our website.Rene Krantz is Director of R D Programs Business Development at SEMI. She is the primary manager of SEMI Smart MedTech Initiative and NBMC programs. Contact Rene at [email protected].

(The following is an excerpt of an article published by i-Micronews.)We are today entering a new era when sanitary checks will be regularly required to travel, do shopping, or have a social and cultural life. In this article and the related new Yole Développement (Yole) report, Thermal Imagers and Detectors 2020 – COVID-19 Outbreak Impact – Preliminary Report, we analyze how the COVID-19 outbreak could affect the thermal technology market and industrial landscape.To resume normal air traffic, air passenger screening to detect travelers with signs or symptoms of infectious disease will require new modalities. Thermal imagers could be used as a fast primary testing solution. This won’t be the first time actually. In the previous SARS, H1N1 and Ebola epidemics thermal cameras were used in some airports to screen travelers for fever. Of course, the size of the previous epidemics was not big enough to give this technology much attention. The way forward would be a triage process. Thermal imagers based on microbolometer technology can be installed at airports. If a fever is detected, then the traveler could be taken aside to get further tested with a more accurate handheld contactless thermometer. If the fever is proven, then they can be isolated for further examination, either a history check, and/or a diagnostics test, provided that it gives results in a reasonable amount of time.Airports are not the only places where thermal imagers can be the new norm. In April 2020, more than 50 Amazon warehouses had cases of COVID-19. Typically, workers were having their temperatures checked by handheld thermometers at the entrance. Amazon installed thermal cameras at some of their sites, which allows for faster screening. If needed, a secondary, forehead temperature check is performed if the employee is flagged from the camera, according to Reuters. Other companies that have explored using the thermal camera technology include Tyson Foods Inc and Intel Corp. Even some schools in China have started using them. This is an example of how businesses and infrastructure are turning to methods for containing the spread of virus by using technologies that previously went unnoticed by the general public.More businesses can adopt thermal cameras. In all countries, between 5% and 10% of enterprises employ more than 50 people, according to the OECD. To return to work, they could use thermal cameras to monitor body temperatures of employees as well. Here we are talking about cameras in the order of hundreds of thousands units.But this might not be enough. Everyone will probably want to have the ability to check their body temperature at any time. We have here a big market opportunity for integration of thermal imaging into smartphones or wearables. This integration has been in process for years. And it has long been perceived as the next sensor to be integrated in a mobile phone after pressure, inertial MEMS, or CMOS imagers. However, when 3D sensing technology was launched by Apple in 2017, all smartphone manufacturers focused their effort on this application, and were not interested in thermal imaging. Nowadays, because of the COVID-19 pandemic, people are much more sensitive to checking their own temperature and those of people around them, usually several times per day. Integration of a contactless thermometer could make sense. So there could be a revival of the use case of thermal imaging capability or temperature measurement in a smartphone or a wearable in the future.Click here to read the full article in i-Micronews.Eric Mounier Ph.D. is Fellow Analyst at Yole Développement (Yole). Dimitrios Damianos, Ph.D. is a Technology and Market Analyst at Yole Développement (Yole) working within the Photonics, Sensing Display division.Yole Développement is a member of SEMI and the MEMS Sensors Industry Group (MSIG), a SEMI Strategic Association Partner.

As government and business leaders start to talk about “returning to normal,” and looking to thermal cameras to help, questions remain about how and whether the latest technology can help prevent the spread of COVID-19.Across industries, everyone is looking for the right tools to help detect, slow and eventually stop SARS-CoV-2, the virus that causes COVID-19. By now we’ve all come to recognize that resuming operations in any way will require demonstrating measures to protect the health and wellbeing of people in a variety of situations, including travel and work.One proposed solution is thermal scanners. Unlike most medical imaging approaches, infrared (IR) thermography doesn’t require irradiation or expensive equipment, and presents no health hazard. Infrared radiation emitted from our skin can be detected and used along with information about the ambient environment to estimate core body temperature — which may indicate someone is running a fever, a common early symptom of COVID-19. While thermal cameras can’t detect a virus or a specific infection, they can help by quickly narrowing down a large pool of possibly infected individuals. And today, this represents the only viable non-contact mass screening approach for fever. The accuracy of the infrared system can, however, be affected by human, environmental and equipment variables. Understanding this multitude of variables — including the ways in which the science, technology and applications themselves interact — will help both users and system makers deliver the best results.Consideration #1: Think about the methodThermal detection has been used for fever detection for 20 years now. While older thermometers and thermal cameras, including the type used to detect a different coronavirus, severe acute respiratory syndrome (SARS), had their weaknesses, newer generations deliver significant performance improvements. More intelligent systems now offer features such as real-time calibration to ambient temperature with sub-degree °C accuracy, providing more accurate readings far more quickly than older generations.Newer camera systems are also more user-friendly and more reliable, featuring automated target recognition, improved resolution, pairing with a visible-light camera, automated alarms for febrile cases, and clearer outlining of hot spots. This higher degree of granularity improves insight, allowing for a more efficient and faster screening process, and provides on-site health professionals with necessary information to take additional steps when required. Advanced image processing features in new radiometric thermal cameras. Consideration #2: Know your baselinesBecause the environment can influence temperature measurements, some system makers have devised different ways to establish functional baselines. An early approach, recording a population baseline at each site on each day, proved too time- and resource-intensive. A newer approach, using a reference temperature source, or black body, offers evolutionary improvement. Designed to maintain itself at a specific temperature, the black body device allows the thermal camera system to automatically calibrate. Even better is a radiometric camera, which can intepret the intensity of an infrared signal reaching the camera. This requires more rigorous design and testing by the manufacturer, but it delivers much more precise measurements.Diagram of a fever detection system with black body emitter Consideration #3: Looking in the right place While thermal cameras can only detect surface temperatures, different parts of the human body more closely correlate with body temperature. Based on recent scientific research, the most reliable spot in the human face is the canthus, the small corners over the tear duct of your eye where the upper and lower eyelids meet. This kind of precise targeting requires accurate pixel calibration capabilities. The best surface target for estimating core body temperature: the canthus at the inner eye Consideration #4: Checking your performance Operating an IR fever screening system in the lab is one thing, but out in the field, the situation becomes more complex. Users need a camera system that is reliable and stable when it comes to critical performance factors like resolution, sensitivity and frame rate. Understanding the performance considerations when imaging a subject at a distance, for example, and realizing the minimum number of pixels required to get an accurate measurement are both essential in staging a fully optimal fever-detection platform.Consideration #5: Finding your way in the “wild west” of thermal imaging in early 2020People from the many industries that have been devastated by this pandemic – including travel, sports, manufacturing, food and hospitality, and entertainment — are looking for ways to reopen businesses safely while reducing the probability of a second wave of COVID-19. Deploying technology such as IR fever screening systems as part of a range of preventative measures will hopefully support that effort.As is the case with any promising emergent technology, there is a fair degree of chaos around the nuanced considerations of system design and performance. What standards apply to IR fever-screening devices? Which are being enforced? Who makes them? Will they work? IR camera manufacturers such as Teledyne DALSA and the expert system integrators we work with can play an important role in helping manufacturers and integrators to navigate this chaos, enabling us to work together to potentially save lives.For an even more in-depth look at this topic, visit this page, download our whitepaper Thermal Imaging Technology for Fever Screening, or browse.Jean Brunelle, product manager for infrared imaging, is a technical leader in sensor integration at Teledyne DALSA. He works on developing new image correction and calibration algorithms as well as qualification and production tests for the company’s visible and LWIR lines of digital cameras. Having earned a bachelor’s degree in engineering physics and a masters in surface chemistry, he has a passion for all things sensors, from how they work to how they are fabricated and used. His focus for the past few years has been on micro-bolometer-based LWIR cameras. Most recently, he was involved in the development and testing of Teledyne’s very own WLP micro bolometer and its integration into a thermal camera.Teledyne DALSA is a member of MEMS Sensors Industry Group (MSIG), a SEMI technology community that enables the MEMS and sensor industry to address common challenges, innovate and accelerate business results.

The seemingly simple act of commanding consumer devices by voice is a choice that nearly 118 million Americans now make every day, according to a recent report from eMarketer, the digital marketing research firm.While the voice interface is convenient for users, its implementation comes at the potential loss of individual privacy. The reason? Always-on, always-connected voice-first devices such as Amazon Alexa and Google Home require a wall plug and an internet connection to powerful cloud processors, making it possible for cloud companies — however benignly — to collect data on personal habits, location and conversation that were never intended for sharing. Move processing to the edgeTo address concerns over user privacy, device designers are attempting to do more of the audio processing within the consumer device, rather than sending users’ voices into the cloud. Moving more processing to the edge is a trend across the Internet of Things (IoT) industry, and not just for voice data but for other types of sensitive or proprietary data as well.Yet designers have realized limited success because the conventional approach to always-listening edge processing is notoriously inefficient: It digitizes and processes 100% of incoming sound data even though up to 90% of the data is irrelevant noise. This digitize-first approach wastes vast amounts of system power digitizing and analyzing the audio signal as it searches for a wake word when there isn’t even speech present, making it impractical for use in small, battery-operated devices.Workarounds don’t workTackling this power issue is critical to keeping private data secure. Unfortunately, it’s also exceptionally difficult. Design engineers have tried workarounds to decrease power consumption in an always-listening system, including duty cycling and reducing the power of each individual component in the audio signal chain that handles the data. The reality is that these kinds of approaches don’t address the root cause of the problem: too much data.To truly tackle the problem, we need to change our approach to a system solution, not a component solution. By moving to a more efficient edge architecture that intelligently minimizes the amount of data that moves through the system, we can focus the system’s energy resources on analyzing voice and not on searching for a wake word in irrelevant noise. Analyze, THEN digitize It’s time to move away from the digitize-first approach that has dominated voice wake-up device architecture since the invention of voice-first applications.Inspired by the way the human brain efficiently filters incoming information, differentiating, for example, a dog bark from a baby’s cry, an ultra-low-power analog machine learning technology is changing this paradigm. For the first time, device designers can use low-power analog machine learning to detect which data are important for further processing and analysis prior to data digitization.Leveraging an analyze-first architecture, a new analog neuromorphic semiconductor platform allows the higher-power-processing components in the system to stay asleep until voice has actually been detected, and only then does it wake them to listen for a possible wake word.Delivering a post-microphone audio chain that draws as little as 25µA of current when always-listening and collecting preroll data, this analyze-first architecture allows designers to extend battery lifetime significantly. That’s the difference between smart earbuds that run for weeks instead of hours or a battery-powered smart speaker that runs for months instead of weeks.More importantly, it’s the difference between the current always-listening devices that indiscriminately record and send all sound data to the cloud, and one that has the localized intelligence to select and send only the relevant data, reducing the user’s vulnerability to the loss of private data.Balance convenience with privacyThe trade-off between making our lives easier and keeping our personal information private is a choice that we are asked to make throughout our day in a hundred different ways. Bringing more audio processing capability to the mobile device without draining the battery is the first step toward delivering more secure voice-first solutions. But to succeed in this effort, we must shift to a bio-inspired architecture that determines which data are important and requires further processing at the earliest point in the signal chain. Once we move to the analyze-first approach, only a small fraction of the tens of zettabytes of data collected by the forthcoming generation of always-on IoT devices will require further processing in the device and in the cloud.A better balance between cloud and edge processing is a better balance between convenience and privacy, and that’s a win for everyone.About the AuthorTom Doyle is CEO and founder of Aspinity. He brings over 30 years of experience in operational excellence and executive leadership in analog and mixed-signal semiconductor technology to Aspinity. Prior to Aspinity, Tom was group director of Cadence Design Systems’ analog and mixed-signal IC business unit, where he managed the deployment of the company’s technology to the world’s foremost semiconductor companies. Previously, Tom was founder and president of the analog/mixed-signal software firm, Paragon IC solutions, where he was responsible for all operational facets of the company including sales and marketing, global partners/distributors, and engineering teams in the US and Asia. Tom holds a B.S. in Electrical Engineering from West Virginia University and an MBA from California State University, Long Beach. For more information, please visit https://www.aspinity.com/Technology.Aspinity is a member of MEMS Sensors Industry Group (MSIG), a SEMI technology community, that enables the MEMS and sensor industry to address common challenges, innovate and accelerate business results.

Technology advancements seem to be coming at us fast and furiously. Every time you turn around, another company is introducing a breakthrough product with claims of far-reaching implications on how we live and work. But how often do consumers really experience disruptive innovation, like the kind that smartphones and cloud computing have had on our lives? Instead of astounding people, many new products that hit the market today are merely upgraded versions of their predecessor – perhaps offering smaller footprints with faster processors, more attractive packaging, or add-on features. These upgrades tend to underwhelm customers, offering no compelling reason to justify their accompanying price hikes.What consumers want is disruptive technology that truly enhances their lives, whether at work, at home or at play. And that’s exactly what product manufacturers want to deliver. So what’s holding them back?The Limits of Traditional BatteriesThe challenge doesn’t lie in envisioning exciting new offerings. Vendors are great at that. Rather, when it comes to consumer-focused, electronics-based products, the culprit is often conventional, rigid and thick batteries that limit what can be designed around them.But it doesn’t have to be this way.Advances in flexible and thin batteries can spark a whole new level of product differentiation. Even though such batteries have been available now for a few years, they are still a foreign concept to many product designers accustomed to conventional off-the-shelf energy storage that is fixed in rigidity and shape. It’s hard for some people to believe that batteries can fold and flex while maintaining their performance and safety. As a result, they design products around rigid battery parameters. The Promise of FlexibilityFortunately, flexible battery technology is available today, even for high-volume production.While the allure of flexible battery technology is strong, we find ourselves having to reassure manufacturers that flexible batteries are every bit as dependable as their rigid progenitors. Our testing shows that performance-integrity in flexible batteries is strong. They can be flexed, bent and even rolled in any direction without deteriorating performance. For instance, we tested a flexible battery by bending it 10,000 times to prove that it has essentially the same capacity as a non-bent battery. This flexibility gives designers and engineers a new level of freedom in hardware design: Manufacturers can now place batteries in spaces not possible or practical before. Take smartwatches, for instance. Instead of locating batteries in only the head case, engineers can embed a flexible, thin battery in the strap band to increase accessible energy or lengthen battery life. As market demand grows for wearables and hearables, smart apparel and other personal battery-powered products, consumers want more natural-feeling experiences. Unlike fixed off-the-shelf energy solutions offered in a limited range of form factors and capacities, flexible batteries can support customization by size, thickness and capacity, enabling development of products that are smaller, lighter and more comfortable.Rigid batteries are problematic on a whole other level, and that’s safety. Electrolyte advancements ensure flexible batteries are safer. The latest gel-polymer electrolyte is safer than liquid electrolyte because it does not contain liquid that would leak if the battery is pierced or penetrated – yet it still delivers the same high level of ionic conductivity. This is a great advantage for manufacturers of wearables in medical devices, sports equipment and fabrics, industrial applications, and consumer electronics. Knowing that their devices contain safer components not only brings peace of mind to manufacturers and consumers but also increases both adoption and usage rates. Staying competitive in any technology-driven market requires a steady stream of innovation. To rise above the pack, companies must fearlessly embrace advancements that will differentiate them in the marketplace. Your choice of battery is critical to your hardware design – especially if consumers will be in direct contact with the battery. The performance and enhanced safety inherent in next-generation flexible batteries can free you to create disruptive products that deliver a compelling user experience. To learn more about flexible batteries, visit Jenax.EJ Shin delivered an engaging presentation at 2019FLEX Japan (May 22-23, 2019, in Shinagawa, Tokyo), where she discussed Jenax’s flexible and customizable rechargeable battery, a technology that allows batteries to integrate seamlessly into a new generation of medical devices.FLEX Japan is a hosted by FlexTech and MEMS Sensors Industry Group, SEMI technology communities.EJ Shin is Global Director at Jenax Inc., a company that pioneered the next-generation flexible, thin battery that can be bent and rolled in any direction. She has been with Jenax since the company initiated its battery development. EJ helps device and wearable companies leverage Jenax’s customized battery solution for their innovative products. Earlier, she held communications consulting positions at Fleishman Hillard and G20 Summit in Korea. EJ holds an MBA from Yonsei University, South Korea, and a B.A. in International Relations from Tufts University, U.S.