Bluetooth version numbers show up on every phone, laptop and earbud spec sheet, and they tell you less than you’d think. The Bluetooth SIG (Special Interest Group), the industry body that owns the standard, publishes a Core Specification every so often; “Bluetooth 5.3” on a box means the product was qualified against version 5.3 of that spec. It does not mean the product supports every feature in 5.3. Almost everything added since 4.

Matter and Thread are two separate standards that usually get mentioned in the same breath, and mixing them up is the source of most smart home confusion. Matter is an application language: it defines what a light, lock or thermostat is and how an app tells it what to do. Thread is a low-power wireless mesh network that carries some of that traffic. A Matter device can run over Thread, over WiFi or over Ethernet.

This page covers six small open infrastructure projects that each do one job: an embedded database for connected devices, a reverse proxy, browser tools for key-value stores, a policy language that keeps answers ready as data arrives, a setup compiler for AI coding agents’ machines, and a network sandbox for agents. They’re separate projects, each with its own site and repository. What they share is an old habit. SQLite showed that a database can be one file linked into a program; nginx showed that a web server can be small and fast.

The spec sheet for a Raspberry Pi reads like a modest embedded processor. What people actually build with one reads like an infrastructure engineer’s fever dream. Over the years, the platform has accumulated a body of real-world deployments that range from cost-effective home network appliances to production-grade industrial monitoring systems. This post examines a cross-section of those deployments — not hobbyist proof-of-concepts, but functioning systems solving real operational problems. The case studies below span home labs, small businesses, agriculture, aviation, scientific research, and industrial environments.

WiFi above 2.4 GHz gets shorter range, higher throughput, and most of the industry’s attention. WiFi below 1 GHz gets the opposite: longer range, lower throughput, and almost no consumer coverage despite being standardized in 2016. 802.11ah — marketed as WiFi HaLow — is a genuinely distinct technology addressing problems that neither standard WiFi nor cellular IoT handles well. It deserves more attention than it receives. Why Sub-1 GHz Matters for IoT The physics of radio propagation favor lower frequencies for range and obstacle penetration.

The average connected home in 2026 has around forty WiFi devices. Of those, perhaps six to ten are traditional computing devices — laptops, phones, tablets — with current operating systems, automatic security updates, and vendors who issue patches. The rest are smart bulbs, thermostats, door locks, cameras, robot vacuums, speakers, appliances, and sensors. These devices run embedded software that may not have been updated since the day they shipped, respond to default credentials that have not been changed, and have attack surfaces that their manufacturers have not fully audited.

The Arduino ecosystem has grown from a single hobbyist board into one of the most expansive open-source hardware platforms on earth — spanning over 100 official boards, 32,000+ libraries, and a community responsible for more than 50 million boards sold. Whether you are building a home automation node, a CNC controller, or an edge AI inference device, the ecosystem almost certainly has a purpose-built piece of hardware and a ready-made library to match.

Digital twins start as a simple idea—build a virtual version of something real—but they don’t stay simple for long. Once connected to live data, that replica becomes less like a model and more like a living system that reflects, reacts, and sometimes even anticipates what’s happening in the physical world. Sensors feed it continuously, updating conditions in near real time, so what you’re looking at isn’t yesterday’s snapshot or a rough estimate.

Edge AI sounds like a technical rearrangement—just moving computation from the cloud to local devices—but it ends up changing how systems behave in subtle, very practical ways. Instead of sending data somewhere else to be processed and waiting for a response, the device itself becomes capable of understanding and acting on what it sees. A camera doesn’t just record; it interprets. A sensor doesn’t just measure; it decides whether something is off.