Embedded Computing Design

The embedded community has been talking a lot about AI at the Edge. Apparently, it’s not just talk, as Renesas recently acquired Reality AI. That acquisition lets them leverage a large customer base as well as provides access to what the company is calling a "leading-edge toolset and series of AI models."

Interested in speaking at the Fifth Annual IoT Device Security (Virtual) Conference?

“The IoT industry needs to change.”

I say it often, "It’s just storage, what could be new or exciting about it?" And each time I express that opinion to one of the memory experts, I get an earful of what’s new and different.

The experts at Cycuity preach taking a holistic approach to security in your embedded system.

The LoRaWAN specification continues to introduce new products, technologies, applications, and use cases on a regular basis. The consortium recently held a large-scale conference to discuss, display, and tout the latest developments.

Atomera is a semiconductor materials and IP licensing company. They acknowledge that Moore’s Law is slowing down. Manufacturers are looking for ways to reverse that trend. And as you might expect, it comes at a significant cost.

Energy harvesting devices capture energy from the environment, convert that energy to electricity, and put it to work. The energy could come from the sun or other (man-made) light sources, or from vibrations, wind, or water. While this technology is not new, the ability to harness that power and use it as the sole source of energy for small embedded devices is.

What RTOS dominates the embedded space? Your first guess might be Linux, but you would be wrong, by a wide margin. FreeRTOS is the winner.

Many applications today are “software-defined.” Until recently, I would not have used that term to describe an automobile, but I’ve since been set straight.

When you look at the topics that garner the biggest spotlight these days, AI at the Edge is either at the top of the list or very close. As more processing power becomes available, the applications that can take advantage of this technology grow in leaps and bounds.

Upon visiting the STMicroelectronics booth at the recent embedded world trade show, I stumbled across some interesting software aimed at developing your own machine-learning applications.

When it comes to embedded computers for industrial applications, size does matter—sometimes.

Processors to handle AI at the Edge are quite complex. However, that hasn’t stopped so many companies from producing their variants.

I have done lots of these Embedded Executive podcasts, a few hundred in fact. This particular podcast goes in a direction I have never gone before, and involves the mafia (yes, you read that correctly).

Based on its shiny new RISC-V MCU that’s now ready for prime time, the OpenHW Group is releasing a development kit so developers can get started on their “open hardware” projects, particularly those that want to connect to the IoT.

For starters, Smith is the largest electronics distributer that I have never heard of. They are a multi-billion-dollar company. One of the strengths of the company is ensuring that its products are real (as opposed to counterfeits). 

Here at Embedded Computing Design, we spend a lot of time helping engineers/developers work through the pains of industrial designs.