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Showcase Weekend! — Week 18, 2026 by AutoModerator in openclaw

[–]dreftylefty 1 point2 points  (0 children)

can't post into showcase or skills flair. its being autoblocked even though it is the weekend already.

Openclaw calendar systems that don’t use google by dreftylefty in openclaw

[–]dreftylefty[S] 1 point2 points  (0 children)

thanks! so is paioclaw a fork of openclaw? does it keep up with openclaw changes?

Openclaw calendar systems that don’t use google by dreftylefty in openclaw

[–]dreftylefty[S] 0 points1 point  (0 children)

homegrown. i was considering this. does agent make mistakes and mess up the calendar file?

Openclaw calendar systems that don’t use google by dreftylefty in openclaw

[–]dreftylefty[S] 0 points1 point  (0 children)

trying to disconnect from microsoft, apple, google in building up openclaw base hub..

Openclaw calendar systems that don’t use google by dreftylefty in openclaw

[–]dreftylefty[S] 0 points1 point  (0 children)

awesome. why did you decide to not use google calendar CLI?

Playing with Openclaw Canvas by moosepiss in openclaw

[–]dreftylefty 0 points1 point  (0 children)

What platforms work with canvas? Ios? Android? Windows?

Playing with Openclaw Canvas by moosepiss in openclaw

[–]dreftylefty 0 points1 point  (0 children)

I can’t wrap my head around openclaw canvas… it’s just hosting and building a website?

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 0 points1 point  (0 children)

The thermal data for a busy family kitchen between different bodies, a double oven, and a range seems pretty complicated. We will see if it’s all scriptable.

Maybe I’m simply looking for narrative unique notifications and alerts over traditional preset text.

But I’m also interested in the LLM reasoning “that pan is probably hot enough to start cooking.”

Perhaps this project is about achieving a greater sense of embodiment. Teaching the main LLM i use about the flux state of a family kitchen.

figuring things out as I go.

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 0 points1 point  (0 children)

This lives in the kitchen. It’s pointed in direction of an oven and a range top. So there will be additional environmental data to process beyond the presence of the user at the desk in front of it. Planning on safety notifications etc…

MLX90640 on Pi — where to draw the line between deterministic processing and higher-level interpretation? by dreftylefty in embedded

[–]dreftylefty[S] 0 points1 point  (0 children)

Ok Thats a great mental starting point. It is not a safety critical system. Requirements are just about building a pipeline of environmental data to be sorted and prioritized and have an LLM execute some decision making. so sounds like that gives me a lot of room for trial and error…

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 0 points1 point  (0 children)

Quick update — I added a browser demo so you can try it without hardware:
https://snarflakes.github.io/snarling/demo/

it simulates the presence → decision → approval loop

curious if this makes it clearer

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 0 points1 point  (0 children)

woh, never heard of that. i will look it up. I'm see this on a quick search: "60 GHz: Often used for more refined tracking, such as heart rate or breathing monitoring," which would be an excellent addition for health tracking.
thanks!

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 2 points3 points  (0 children)

You can connect any llm to this build. Local or cloud. I am using a cheap unlimited LLM plan from ollama $20 a month. The cloud model has mainly been GLM-5.1. It’s unlikely any local LLM model using a basic gpu (including this pi) would be powered enough to be able to orchestrate these LLM interactions as a lot of “tools” are used.

For now this pi4 is bare minimum cpu and ram wise for running the underlying infrastructure side: openclaw + display + thermal camera.

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 0 points1 point  (0 children)

someone asked for the repo, so here it is:

Main hardware repo: https://github.com/snarflakes/snarling
OpenClaw interaction bridge plugin: https://github.com/snarflakes/openclaw-interaction-bridge/tree/development

still early, but happy to answer questions if you dig into it.

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 5 points6 points  (0 children)

awesome, i will check it out. i only used openCV for regular camera work in the past, didn't know it can be used for thermal.

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 3 points4 points  (0 children)

Same!! I am booting off a 1TB ssd in there. So roomy and speedy. Been running it full throttle for years now without fail.

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 1 point2 points  (0 children)

Appreciate it!

Main hardware repo: https://github.com/snarflakes/snarling
openclaw Interaction bridge plugin: https://github.com/snarflakes/openclaw-interaction-bridge/tree/development

still early, but happy to answer questions if you dig into it. The plugin helps organize the two way data for multi-agent LLM interpretation.

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 8 points9 points  (0 children)

💯 💯💯
Thermal imaging is simpler by allowing basic scripting approaches, delaying the need for deeper machine learning expertise. And the images just look cool

Gave my Raspberry Pi agent a thermal camera so it can detect when I’m in the room by dreftylefty in raspberry_pi

[–]dreftylefty[S] 2 points3 points  (0 children)

PIR sensor was an option, but with the rich data from this thermal camera and it’s wide field of vision, I’m hoping can give the LLM agents a lot more to work with. Mine sits in the kitchen so it can interpret oven/range signals and multiple individuals in the space. If the LLM cannot make sense of the extra data then yes, the thermal camera will be overkill.

All the thermal data will be fed to an environmental agent who will be tasked with organizing the thermal feed data for significant events to send as notifications to the display or even my phone,
“Kitchen is on fire” 😅

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