The future of engineering innovation, like invention, is born out of necessity. A primary necessity today is to achieve technology breakthroughs faster than those accomplished in previous generations.
Consider the electronic sensor. Sensors are at the core of the Internet of Things/Industrial Internet of Things (IoT/IIoT). They have the potential to be in everything.
According to the International Data Corporation (IDC), worldwide IoT spending is expected to sustain a compound annual growth rate (CAGR) of 14.4 percent during the 2017-2021 forecast period, surpassing the $1 trillion mark in 2020 and reaching $1.1 trillion in 2021. IoT hardware is forecast to be the largest technology category in 2018, with $239 billion going largely toward modules and sensors, along with some spending on infrastructure and security.
Each IoT/IIoT device represents tens of thousands of hours of engineering effort at the component and system level. Engineers are under tremendous pressure to design, develop, and deliver innovation faster than ever before. Design cycles are shrinking from years to months.
Sensors promise to make possible many advancements, including: expanding the universe of connected things comprising the IoT/IIoT; improving the connections and data communications associated with 5G; enhancing automotive comfort, performance, and safety on the road to driverless cars, and contributing to better healthcare through biomedical advancements.
In startling contrast to the need for invention at a turbocharged pace is the lack of innovation in the universal methods of the prototyping underpinning these breakthroughs. Many engineers in the business of sensor design are currently constrained by costs, time, and risk associated with using outdated legacy computer aided engineering (CAE) tools and limited on-premise high-performance computing (HPC).
Let’s first look at some of the near-term breakthroughs being discussed in four areas (IoT/IIoT, 5G, advanced driver-assistance systems (ADAS), and healthcare) touched by sensors. We’ll then examine how multi-physics solvers, cloud CAE, and HPC working together can spur engineering innovation.
At the 2018 Sensors Expo, Alissa Fitzgerald, president of MEMS design and consulting firm AMFitzgerald and Associates, presented a session on upcoming sensor developments. Fitzgerald identified several areas that are presently under development, but cautioned the audience that most of these are still a long way off from being ready for commercial prime time. As reported in ECN, here are some of the IoT/IIoT highlights Fitzgerald included in her session:
Event-driven sensors are the closest to commercialization, which she projects will come within the next 5 years. She cited the example of a project that Northeastern University is working on: a sensor built to detect infrared light waves that would essentially remain off until an event is detected. This would mean standby power requirements are almost nil. Future applications for event-driven sensor technology are IoT and security.
The race to make 5G commercially available is ramping up. One of the technology hurdles to overcome is making antennas small enough for use in smartphones, but also capable enough to harness millimeter wave (mmWave) radio frequencies that deliver fiber-optic-like speeds. In July 2018, Qualcomm announced it has developed an antenna that achieves this, even as some industry experts questioned the technical feasibility of miniaturized antennas that could tap mmWave frequencies—or at least doubted it was possible to produce these by the time the first 5G wireless networks begin rolling out in 2019.
Designing next-gen IoT sensors that will work over 5G networks requires extensive prototyping and testing, rendering the sluggish (potentially weeks-long) simulation times of legacy platforms unacceptable.
The use of ultrasound sensors is expected to become increasingly more prevalent for ADAS. In their present state of evolution, self-driving cars require a combination of sensing mechanisms including: radar, optical cameras, lidar, and ultrasound. Many industry experts suggest that as the GPS used in mobile phones improves to where it is capable of predicting where a phone is within an inch, the automotive industry will adapt this technology to meet the stringent requirements of self-driving cars, streamlining the types of sensors the vehicles rely on. The use of ultrasound sensing as high-resolution, shorter-distance sensing, when compared with radar and lidar, holds great promise for automobiles. Adapting a consumer technology to cars where lives are at stake, requires hours of extensive testing. The industry is ready for a scenario where this testing could occur simultaneously and in parallel, because costs were contained, and resources were abundant and on demand.
In addition to Fitzgerald’s IoT/IIoT predictions at Sensor Expo 2018, her session also identified several sensor breakthroughs emergent in the biomedical field.
According to ECN’s story on Fitzgerald’s presentation, piezoelectric technology is being looked at to act as ultrasonic transceivers located inside the body. Such transceivers could improve applications such as imaging telemetry, health monitoring, and wearable sensors; although, the concept still needs a lot of testing. Even further down the research pipeline is a dissolvable, paper-based battery that uses bacteria as an electron source. The battery could provide power for temporary medical implants, environmental sensors, and disposable consumer electronics. This idea is now in the early stage proof-of-concept and is at least a decade away, Fitzgerald noted.
For the medical device companies we work with, they are looking at developing technology in the fields of sensors, imaging system technologies, machine learning algorithms, and augmented reality applications. A key pain point is limited computing resources.
Accelerating Innovation via Cloud Resources
All engineering innovation requires sufficient trial and error. With the increasing complexity and sophistication of technologies, the stakes are higher than ever. One solution is to move trial-and-error processes to the Cloud, where sophisticated CAE and other virtual prototyping can replace expensive, time-consuming, and risky physical prototyping. Cloud CAE has the potential to enable massive new technology innovations.
Imagine when rapid innovation and expedited time to market for next-generation products are the norm. When the combination of Cloud and HPC and fully integrated multi-physics solvers removes the guesswork and trial and error of today’s engineering and prototyping processes. So engineers do more up-front simulation, optimization, and virtual prototyping to arrive at the optimal design quicker. The future of engineering innovation accelerates in Cloud CAE, and it starts now.