Embedded Computing Design

The importance of security in embedded designs can never be stressed enough. With the expanding cybersecurity threat landscape and lack of security professionals in the workforce, everyday engineers need to be able to implement hardware root-of-trust-grade security in a robust but simplified manner.

Ruggedized systems require high-bandwidth processing.

Artificial intelligence is the driving force behind so many applications today. From the developers’ perspective, it’s almost a given that AI will play some role in the end application. One such application where AI is making a lot of inroads is public safety and security. Such security is being utilized in everything from airports and railways stations to hospitals and manufacturing facilities. And it can scale from a single room to a large campus or even a city.

New and evolving hardware technologies are making real-time AI inferencing at the edge a reality. These include fluid edge-to-cloud connectivity, expansive networking capabilities, and sustained computational performance at efficient power consumption levels, all of which are designed into Premio’s RCO-6000-CFL AI Edge Inference Computer.

Every type of edge AI has three hard and fast technical requirements: low power, small form factor, and high performance. Of course, what constitutes “small,” “power efficient,” or “high performance” varies by use case and can describe everything from small microcontrollers to edge servers, but usually you must sacrifice at least one to get the others.

However, one solution that can address everything from edge clouds to endpoints without sacrifice is the FPGA.

Market research estimates the natural language processing market will grow from $20.98 billion in 2021 to more than $127 billion in 2028. Similarly, the AI vision market is expected to grow to $144.46 billion from $7.04 billion in 2020.

Clearly, artificial sensory perception is on the rise.

As the world’s demand for intelligence increases, real-time edge computing no longer refers simply to data processing. Increasingly, it implies AI.

In applications like traffic monitoring, defect/quality inspection, people counting, medical imaging, or autonomous mobile robots (AMRs), the demand for edge AI also means requirements for low latency, minimal power consumption, and sufficient thermal dissipation – all of course, at the highest performance levels possible.

Logistics automation is the straightforward act of applying industry standards to the operation of a factory or warehouse to simplify its operation and organize it in ways that are not possible through more manual methods.

Smart retail refers to the concept of adding “intelligence” to traditional shopping methods. The global pandemic has expedited the smart retail process, as it allows the consumer to complete a transaction with little to no human interaction if desired.

On this episode, Brandon and Rich review highlights from Smart Manufacturing Day, including a debate on what Industry 5.0 truly means, and discuss the potential peril of code-heavy software-defined factories and vehicles.

In the world of manufacturing for industrial and rugged applications, including robotics, and artificial intelligence, the Made in America moniker brings a lot of cache.

In operating rooms, electronic medical devices are indispensable to healthcare diagnostics, real-time patient monitoring, and surgical visualization. But as crucial as these systems are, they are also potentially quite dangerous. If they aren’t dust-proof, water-tight, protected against power failure, and immune to electromagnetic interference, they present a range of dangers from electric shock to hosting bacteria.

To ensure healthcare workers can continue to access the patient data and productivity technology they need in the safest, most, reliable, and most hygienic manner possible, Wincomm has released the WMP-24M-PIS, a 23.8” LCD screen medical panel PC based on 10^th generation Intel® Core® processor technology.

The more data that’s generated, the more that needs to be stored. The more data that needs to be stored, the more bandwidth and capacity required from storage solutions.

In consumer electronics and the data center, technology roadmaps are in place to help offset the exponential demand for data acquisition and storage. But what about industrial computing?

The NVIDIA/Arm transaction may have fallen through, but that isn’t the only momentous merger and acquisition that’s been on the table in the embedded technology space.

High-level processing and extreme reliability are two precursors for AI in mission-critical edge applications. And that means blending the old with the new.

Despite, or maybe because of, the pandemic, Verified Market Research projects that the global Smart Manufacturing Market will grow at a 12.4% CAGR through 2028 to USD 589.98 billion.

This week, the Insiders recap a COVID-era Consumer Electronics Show and debate one of CES’s hottest topics: the metaverse. Broadly speaking, the metaverse could be an in-between where physical reality and virtual reality collide, or it could be an entirely digital alternate universe.

The world is now built on data intelligence, and that means we need to be connected and secure. We also need a whole lot of Ethernet.

High-speed LAN solutions are on the rise in industrial automation, surveillance, and gaming markets. But as these higher-bandwidth connectivity options find themselves beyond the core network infrastructure they must compensate for interference issues associated with the size of PCIe form factors, many of which cannot fit into today's compact IPC system designs.

IoT edge devices are continuing to emerge in smart manufacturing with the help of artificial intelligence and machine learning (AI/ML). As these spaces continue to make use of edge intelligence, IIoT is becoming more beneficial to the management and visibility of automated manufacturing facilities that improve reliability and efficiency.

Of course, implementing AI and machine learning in industrial environments where space, cost, and safe operation are paramount is not as straightforward as flipping a switch.