chirpstack-gateway-os VS Node RED

FWIW, for building your own private network, there is no need to rely on something like TTN. ChirpStack (https://www.chirpstack.io/) is a very mature and easy to deploy LoRaWAN suite that's worth looking at!

Next, setup your own LoRaWAN Server on the Raspberry PI using ChirpStack: https://www.chirpstack.io/

I saw that Reticulum (https://github.com/markqvist/Reticulum/) is already using I2P for Internet communication. What I would like to create is a similar infrastructure but a bit more advanced using Chirpstack (https://www.chirpstack.io/) servers connected between each other over I2P. Everyone who wants to use the infrastructure can connect a limited number of sensors for each Chirpstack server available nearby. If they want to join more sensors, or improve the infrastructure, they can give their contribute joining new Chirpstack servers to I2P network.

My setup involved https://www.chirpstack.io/ feeding data to self-hosted InfluxDB (or FarmOS via our code at https://github.com/mockingbirdconsulting/FarmOSMQTT), with dashboards in Grafana. I started to write my own dashboard that had dedicated overview screens etc, but it was a serious effort for very little reward.

You can easily setup your own offline LoRaWAN Server Stack on a Raspberry Pi, for example this one https://www.chirpstack.io/, thats what I did. Therefore I would definitely recommend the use LoRaWAN instead of only the LoRa Modulation.

https://www.chirpstack.io/ is a complete solution written in go & open source, including mqtt broker, app server, gateway, gateway bridge and more. It also comes with docker-compose for local development. I worked with it for a while, it's a good project.

If you want to get more involved and run your own infrastructure you could look at something like ChirpStack.

Hi! I'm a new Yocto user trying to develop a fork of Chirpstack's Gateway OS for Raspberry Pi based LoRaWAN gateways. Although I have successfully modified and added new recipes, I'm struggling with adding a USB cellular modem to my image.

Good question.

I expect that we're moving into a phase of AIs talking to AIs, and initially it'll be wasteful (because it'll be mostly English), but eventually, they'll derive their own language and seamlessly upgrade protocols when they determine they're talking to an AI. No clue how that will come about or what that language will look like, but honestly, it's kind of exciting.

Really interesting to think about how they might handle context, as well. Even though we have much bigger context windows (and they'll only get larger), context management is still a resource-management issue, which we'll probably continue to refine, as well. Imagine different strategies for managing both what is brought into the context of each request, as well as what form it could take (level of detail, additional references or commentary on it, etc). Things could get really unreadable even in English, and still be very interpretable for an LLM.

W.r.t. the graph-oriented interfaces, are you thinking something like Node-RED [1]? I'm seeing more and more people mention having LLMs produce non-text or structured outputs, like JSON, UI, and other things. Easy to imagine an LLM that wires together various open-source platforms, on-demand. Something like Node-RED for pipelines/functions, some UI tools for visualization/interactivity, other platforms for messaging, etc...

[1] https://nodered.org/

I skipped to chapter 9 in the article ("Clogged"), and it looked like Pipes failed because it didn't have a large enough team or a well-defined mission. As a result they couldn't offer a super robust product that would lure in enterprise users. "You could not purchase some number of guaranteed-to-work Pipes calls per month" is the quote from the article.

The reason I think that interesting is because that's the model these days for everything from AI tokens to Monday.com seats. It makes me feel like Pipes was before its time.

That said I've been collecting different "business glue" products that are similar to Pipes. To me, like you say, they aren't as interesting, exciting and intuitive as Pipes was, but maybe it just takes a little more digging. I tried to focus on open source tools but some aren't.

- n8n io: https://n8n.io/integrations/mondaycom/

- Node-RED: https://nodered.org/ (just read about this one in this thread)

- trigger dev: trigger.dev

- automatisch.io: https://automatisch.io/docs/

- Activepieces: https://www.activepieces.com/docs/getting-started/introducti...

- Huginn: https://github.com/huginn/huginn

- budibase: https://budibase.com/

- windmill: https://www.windmill.dev/

- tooljet: https://www.tooljet.com/workflows

- Bracket: https://www.usebracket.com/pricing (just SalesForce <-> PostgreSQL)

- Zapier: zapier.com/

Anyway I hope some of these are fun!

Source: https://github.com/node-red/node-red

I believe Node-RED (https://nodered.org/) the way to go. It's just an NPM package to install and you can run it how ever you wish (even on Windows). It has a friendly and helpful community with even the main developers tirelessly answering even beginner level questions. In fact the community forum its THE friendliest forum I've ever been a member of by a large margin. Node-RED's development is supported by the JS Foundation and it's completely free and open source. It's widely used in the industrial automation industry and even integrated by some PLC manufacturers such as Siemens.

Does anyone know if their are plans to implement something like this (or if there are already custom nodes out there). I'd like to experiment with things like looping and incrementing values (like a for loop) for a Ksampler for example. It's only an example though, so I am not looking for a ksampler specific solution; just a generic way to have a variable (e.g. Seed value), run some nodes that use that value, increment the value, and then loop back to the beginning until some sort of condition is met. Node-Red (an event driven node based programming language) has this functionality so it could defintely work in a node based environment such as ComfyUI (see here).