Patching the pain out of life on the edge

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Hello readers,

Welcome to the IoT For All newsletter! This week we’re talking about edge AI, the challenges of developing embedded systems, fleet management, and more!

Living on the edge

There's a reason more and more companies are investing in edge computing for AI and IoT. A bunch of them, really. Lower latency, better privacy, more control. But ‘better’ doesn't mean ‘easier.’ For all their benefits, edge AI implementations can come with a lot of problems to solve: integration overhead, inconsistent hardware support, and fragmented software environments.

But at least one of those issues looks to be improving. Late last month, Canonical announced Ubuntu 24.04 will support Qualcomm's new Dragonwing processors. And not just the stripped down Ubuntu Core, but a full, stable, familiar desktop development environment at the edge. This isn't a panacea of course, but it's a step towards ameliorating one of the largest obstacles to getting the edge up and running.

Qualcomm's Dragonwing platform is new, but the silicon juggernaut has weight to throw around, and Ubuntu support gives it a foot in the door. Developers building smart retail kiosks or vision-enabled industrial monitors can run full Ubuntu Desktop environments directly on-device, eliminating reliance on cloud-based compute if they opt for Dragonwing devices.

It helps, of course, that this isn't the first place Ubuntu is establishing a foothold at the edge. Ubuntu Desktop already supports x86 Intel Atom hardware and Canonical recently announced NVIDIA Jetson support via Ubuntu Core. This doesn't mean edge AI hardware is instantly plug and play. But it does mean that setup times can shrink and deployment can get faster.

Increasing standardization won’t solve every challenge facing edge AI, but it smooths the path. The more familiar and consistent these environments become, the more viable real-world deployments get. It’s not necessarily about making things dead simple. That’s not always possible when you’re trying to accomplish something complex. But making things feasible at scale? That’s the baseline for growth.

📖 Top Articles

Designing for Chaos: What Embedded Systems Actually Face at the Industrial Edge

IIoT isn’t a plug-and-play upgrade. It’s a systems engineering problem. One that spans hardware constraints, software complexity, organizational silos, and decades of architectural debt. Until companies accept that, most deployments will stay stuck in pilot purgatory.

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🔥 Rapid Fire

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🎙️ The IoT For All Podcast

No new podcast this week, but check out our latest episode where we talk to Maor Efrati, CTO and co-founder of Monogoto, about software-defined connectivity. The conversation covers private 5G networks, satellite connectivity, the importance of APIs for seamless integration and automation, SIM, IoT security, and embracing cellular solutions for next-gen connectivity.

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