About a year and a half ago, I decided to take a different approach to setting up a Zephyr environment for a new project at Intercreate. Instead of using my trusty VMWare Workstation Linux VM, I opted for WSL2. I was curious to find out: Would hardware pass-through for debugging work reliably? Would all of the tooling dependencies be supported? What about build system performance?

The Industrial Internet of Things (IIoT) industry is experiencing rapid growth and transformation, driven by advancements in connectivity, data analytics, and automation technologies. The number of connected devices and sensors is constantly growing and is expected to be around 18.8 billion by the end of 2024. More and more manufacturers rely on automation every day. ‍

The EU Cyber Resilience Act is coming. I’ve talked about this piece of upcoming regulation in some depth before, having covered its background and stipulations in previous pieces on our website and for the Forbes Technology Council, and explored what it means for the businesses who consume open source in later articles (you can also read a version of this blog on Forbes).

With the increased adoption of the Industrial Internet of Things (IIoT), connected devices and sensors generate vast amounts of data, and you’ll need an effective way to capture, store, and visualize all of it. With effective data visualization and analysis, you can transform raw data into actionable insights and make informed decisions. This post will break down tools like Grafana, Node-RED, and time series databases, including their benefits to your IIoT workload.

The state of industries has come a long way since the Industrial Revolution with new technologies such as smart devices, the internet, and the cloud. The Industrial Internet of Things (IIoT) is a network of industrial components that share and process data to gain insights. But as IIoT involves sensitive data and life-critical operations, this also comes with various IIoT cloud security challenges. Therefore, it is important to strengthen security.

In this article, we will learn how memory usage patterns can affect the real-time performance of an embedded application, drawing from a recent experience tracing an audio DSP application running on an embedded Linux platform. First, I will introduce the product in question and the real-time audio software I developed for it. Then, I’ll describe the issues I encountered with audio callbacks and the strategy I followed to determine the cause of the issues, ending with my solution and lessons learned.

Technology focused on building a more sustainable future continues to advance at incredible speed. The Industrial Internet of Things (IIoT) and real-time analytics are opening up new horizons for renewable energy. This post looks at the intersections of innovation and ecology, where small chips and sensors play major roles in the renewable energy sector.