The landscape of embedded systems and computing is changing. Fast. IoT in particular is driving widespread change in technology when it comes to standards, hardware, systems, and software, with the need for all of these components to work seamlessly as a complete infrastructure. Meanwhile, the demand for increased functionality at the edge has underscored the need for faster and more formidable compute power across entire systems or networks.
In a three-part blog series hosted on the Embedded-Computing Design site, SUSE covers best practices and common hurdles when facing embedded development for IoT systems. We also explore how machine learning and artificial intelligence are now guiding applications by analyzing when and where data is processed, as well as why security should remain at the forefront of any development cycle.
- The first post dives into the fundamentals and groundwork when faced with building an IoT system, and why open source technology is powerful and viable choice when connecting the edge to the cloud and data center.
- Part two covers the rolling momentum and growing importance of machine learning, and how and where data is being captured, processed and analyzed, including the edge.
- The final post of the series focuses on system and device security. This is a critical element that is frequently overlooked or de-emphasized in favor of more hyper-focus on hardware requirements and rapid development life cycles.
Read the posts that are most relevant to you, or consume all three in sequence to get the bigger picture. Then when you’re finished, contact the Embedded team by clicking ‘Get Started with SUSE’ at the top of this page to learn more about getting the most out of Linux and open source technology for embedded systems and solution development.