When I wrote LPWAN Meshes: Reticulum, Where I Landed earlier this year, I covered Reticulum as Mark Qvist’s reference Python implementation: rnsd, Sideband, NomadNet, all built on RNS. That was accurate at the time, and it undersold what was already starting to happen underneath it. Reticulum was never meant to be a Python project. It is a protocol specification, and a protocol specification with only one implementation isn’t decentralised yet, it’s just a single point of failure with good branding.

Part one and part two of this series covered how Reticulum and MeshCore actually move a sensor reading: LXMF’s delivery methods and Propagation Nodes on one side, a purpose-built sensor role and CayenneLPP encoding on the other. Both are genuinely decentralised, no shared infrastructure required beyond the nodes themselves. This closing part asks the question that decides whether that matters for a given deployment: what does the alternative, LoRaWAN, actually require to do the same job?

Part one of this series looked at sensor telemetry over Reticulum, and landed on a specific trade-off: Reticulum gives you cryptographic primitives (Destinations, Links, LXMF’s delivery methods) and leaves the shape of a telemetry deployment up to you. MeshCore takes the opposite approach. It has an actual sensor node role, a standard payload encoding, and a query model built around telemetry specifically, not general-purpose messaging repurposed for it.

LPWAN Meshes: Reticulum, Where I Landed covered Reticulum as a communications stack: transport-agnostic, cryptographically addressed, built for chat and file transfer over LoRa, packet radio, or whatever medium is available. This post is narrower on purpose: it breaks down the specific mechanics of moving a sensor reading, not a conversation, through Reticulum: which delivery method to pick, what a reading actually costs in packets and bits per second, and what already exists in the open-source community to build on rather than reinvent.

If you have spent any time in the off-grid radio scene over the last few years, you know the frequency divisions. You either ran on the sub-GHz bands (915 MHz in Australia and the Americas, 868 MHz in Europe) for long-range, bush-penetrating reliability, or you accepted the high-congestion limits of local Wi-Fi. It was a trade-off we took for granted. If you wanted to send a message across 10 km of dense stringybark, you needed the long waves. If you wanted global hardware standardisation, you looked elsewhere.

There is nothing quite like the mild panic of joining a meeting only to be greeted by a void where your face should be. On the latest Ubuntu 26.04 and the 24.04 LTS (Wayland), this has become a recurring theme for anyone unfortunate enough to rely on the Zoom Snap package.

You check your settings. The camera is detected. It works perfectly in Firefox. It works in Cheese. You’ve even checked the Snap permissions and everything looks “correct”. Yet, Zoom remains a stubborn black screen.

In the world of Internet of Things (IoT), the sub-GHz spectrum is a frontier of immense promise, offering the holy grail of long-range and low-power communication. Two fundamentally different philosophies are vying to define this frontier. On one side stands Wi-Fi HaLow (IEEE 802.11ah), a direct evolution of the familiar, IP-based Wi-Fi standard, engineered for higher bandwidth and seamless integration. On the other lies the diverse and adaptable LoRa landscape, a collection of distinct networking protocols all built upon the same remarkable long-range radio technology.

Over the past few weeks, I’ve pulled apart four different LPWAN mesh technologies. Now it’s time to bring those findings together and look at which tool fits which job on the property or in the community.

There is no “perfect” protocol. What we have is a set of tools with different trade-offs. I’ve evaluated all four across five parameters to help cut through the marketing noise and get to the technical reality.

The ClusterDuck Protocol (CDP) was where my mesh networking journey truly began. The story behind Project OWL (Organisation, Whereabouts, and Logistics), students building emergency communication networks after Hurricane Maria, resonated deeply, highlighting a technology designed not for hobbyists or industry, but for saving lives when infrastructure fails. While I found its concepts “much better thought through” from the outset, the project’s slow pace and patchy hardware support meant my personal involvement never truly moved beyond some initial tinkering.

ASUS ExpertBooks are popular enterprise laptops with a well-priced combination of hardware and solid build quality. However, installing Ubuntu on these laptops can be challenging due to UEFI issues. In this blog post, I am documenting the challenges and the steps to overcome these issues and successfully install Ubuntu on ASUS ExpertBooks.

After years of experimenting with various LPWAN mesh networking technologies, I’ve settled on Reticulum as my primary LoRa mesh platform. It emerged as the clear frontrunner not because it’s simpler than the rudimentary Meshtastic (it isn’t), nor because it’s overtly more feature-rich than the structured MeshCore, but because its design philosophy fundamentally aligns with what matters most: privacy, resilience, and true decentralisation. It supports multiple bearer protocols, making it a powerful tool for building a future decentralised network.

While Meshtastic serves as a solid introduction to LPWAN mesh networking, MeshCore represents a move toward more structured networks, particularly when the limits of ad-hoc flooding become a bottleneck. It addresses the “airtime” congestion common in simpler protocols, offering a far more robust path for community-scale infrastructure where a “best effort” approach isn’t enough. MeshCore is built for managed deployments and regional sensor networks where reliability and structured routing are the priority.