Embedded Computing Design

Connectivity has never been a more important element in the design of any embedded computing system. Without reliable, resilient connectivity, devices at the edge lose much of their power and everything else loses what the edge can inform them about.

In this episode of Embedded Insiders, we dive into the challenges and solutions shaping AI and identity verification. Pavel Goldman-Kalaydin, Head of AI and Machine Learning at Sumsub shares how his team is tackling deepfake threats while addressing privacy and ethics concerns with cutting-edge, AI-driven tech.

Get ready to revolutionize your tech game at STMicroelectronics’ STM32Summit this December. First, on December 10 at 11:00 AM ET, you’ll hear from innovation leaders including ST, its customers, and partners, when they unveil game-changing announcements during a live Keynote Address. This is your front-row seat to discover cutting-edge advancements and brand-new products that will shape the future of engineering.

In today’s industrial landscape seamless device communication is key. The Controller Area Network (CAN) Bus—a reliable protocol initially developed for vehicles—now enables quick, decentralized data transfer across sectors without central control. This setup is ideal for manufacturing and automation, where consistent multi-node communication is crucial. Cervoz’s M.2 PCIe CAN Bus Expansion Cards offer tailored solutions for these high-demand environments.

Modern connected devices deployed today must provide secure and powerful edge computing capabilities within harsh, safety-critical industrial environments. These devices should enable seamless communication between modern IoT devices and legacy solutions and support data aggregation and preprocessing, remote monitoring and management, data security, reliability, and much more.

On this episode of Embedded Insiders, Editor-in-Chief, Ken Briodagh, sits down with Patrick Soheili and Kevin Donnelly of Eliyan to highlight the company's new Chiplet Interconnect PHY at 64Gbps in 3nm Process. The multi-die interconnect evolution marches on and Eliyan is getting a lot of attention for its ability to deliver performance and bandwidth like this in either standard or advanced packaging.

All entries are judged using a 15-point rubric, that assesses design excellence, relative performance, and market impact/disruption. Judging is managed by the ECD Content Team.

Entry-level factory automation applications are evolving with solutions designed to enhance productivity, reliability, and flexibility on the factory floor. These safety-critical environments require high-performing, rugged systems capable of seamless integration and advanced connectivity, often in a fanless, compact design.

Today’s growing number of FPGA-based applications, such as industrial networking, embedded vision, and automotive systems, can benefit from evaluation and prototyping tools that help developers bring low-power, cost-effective, and flexible solutions to market faster.

Electric vehicles (EVs) contribute to a greener, more sustainable future by eliminating NOx, CO2, and particulate matter (PM) emissions. To further optimize energy efficiency, performance, and range, many EV manufacturers adopt a holistic design approach, incorporating Wide Bandgap (WBG) semiconductors and focusing on the seamless integration and interoperability of key vehicle systems.

 

As a key player in the FPGA landscape, Enclustra is actively driving innovation in Vision AI applications. Embedded vision AI applications are revolutionizing industries by enabling highly complex real-time video stream processing and decision-making at the edge. These applications range from autonomous driving to smart manufacturing, where rapid analysis of visual data is critical. They demand real-time processing, low latency, and low power consumption to effectively analyze and interpret visual data.

In the world of Embedded Computing, power management is one of the key pillars to any system’s design. Keeping power use optimized and efficient is important, of course, but also, managing the risks of power surges.

The Embedded Computing Design editorial staff is pleased to present this year’s electronica Best-in-Show nominees in the following categories: 

Electronica will take place November 12 to 15 in Munich, Germany, and one of the highlights will be The IIoT Forum, which will be held at the Visionary Stage (B4:131) November 12 and 13.

On this episode of Embedded Insiders, we’re joined by David Bartlett, Head of Technology in the business unit at u-blox, to explore how low-earth orbit (LEO) satellites could elevate positioning, navigation, and timing (PNT) services. Are satellites closer to Earth the answer to providing reliable PNT in the toughest environments?

The agriculture industry faces numerous challenges driven by environmental, economic, and social factors. Climate change is a major concern, causing unpredictable weather patterns, droughts, floods, and shifting growing seasons, which impact crop yields.

Mission-critical industrial applications are often challenged with providing flexibility, reliability, connectivity, high-performance computing, and much more to environments that can sometimes be unpredictable and dangerous. 

Today’s industrial environments are pressured by the need for real-time data analysis and decision-making at the edge, especially for applications like machine vision, automated guided vehicles (AGV), autonomous mobile robots (AMR), and intelligent video-analytics applications that assist with sorting machinery, performing automated optical inspection (AOI) and defect inspection, and object recognition tasks.

Silicon manufacturing is ramping up faster all over the world, and with the growing desire for ever-more sophisticated (and power-thirsty) AI processing capability, that’s not likely to slow down any time soon.

In industrial automation, maintaining machine and process health is as crucial as the automation itself, evolving from a reactive approach to a more sophisticated, data-driven strategy. Initially, reactive maintenance fixed issues only after they caused costly downtimes and production delays. Preventive maintenance marked the next step, introducing regular inspections and part replacements to reduce such risks, but it still couldn't fully optimize asset utilization. Predictive Maintenance (PdM) now represents the pinnacle of this evolution in asset management, harnessing data, artificial intelligence (AI), and advanced hardware to anticipate and resolve potential issues before they escalate into failures, thus ensuring peak equipment performance and seamless operations.