Just wanted to elaborate on the state of the project and the goal.
think of it as a modular field computer inspired by
Flipper Zero, but aimed at outdoors/survival/trades folks instead of security people.
Right now I'm deep in the software/OS layer - getting the core system working
(Qt/QML UI, Docker services, on-device AI with Phi-3, offline maps, Meshtastic
integration). Once I validate everything with field tests, I'll finalize the
hardware design. It's built on Raspberry Pi 5 + ESP32-S3 doing the heavy lifting
for LoRa mesh comms and always-on sensors.
The big idea is making something that's flexible like Flipper Zero but for
different use cases - you could run apps for hunting, survival navigation, plant
identification, whatever fits your lifestyle. The app ecosystem is key - I want
developers to easily build specialized tools that work in their workflow.
Communication-first design too - Meshtastic for long-range mesh when networks are
down, with graceful degradation from LTE → WiFi → LoRa → GPS beacon. The whole
thing is designed to work offline-first - max functionality with zero internet
dependency.
Still super early (hence the software focus first), but the goal is a rugged
platform that people can actually build on and customize for their specific needs.
Not trying to replace phones, just be the reliable tool that works when phones don't.
Agree with you on that, it was my concern too, but the way I think about it is access to information, the goal is not to provide hallucinations with a straight face (aka GPT), but rather use it as a way to extract necessary information fast. For instance, I have a built-in RAG that reads of growing collection on books on medical, survival, etc. (https://github.com/dmitry-grechko/waycore-knowledge) that AI agent is using to answer questions. Moreover, it has a built-in safety loop to always inform users on the accuracy of the information, but also if the information request has an impact on health & safety, it will warn users about it too.
So, I certainly see the inherited risk and problems, but mostly think about it as a means of information extraction
Good point. I’ll add it to the roadmap.
I still want to experiment with AI features as I feel it can add value despite hallucinations, but safety and transparency are crucial - completely agree.
wonderful... this is something I hope would come up going forward. I see this a little in the japanese electronic dictionaries still being developed and released
Yeah, ages ago, I installed all of Microsoft's Encarta on a CF card which I was using as a drive on my Fujitsu Stylist 2300ST --- it was way cool to be able to haul it out and look things up w/o a network connection (or a CD-ROM drive).
Wonder if that would run in a current version of Windows...
Thanks, haven't seen it before, but love the idea of it. It certainly takes the concept a lot futher that I intended with this project. My goal is far is to relyt on well-supported open source tools and frameworks, and give both the software and hardware flexibility for people to create what they need. Think of it like FlipperZero, but for outdoors
Love that I am not alone in this thinking! I test it on embedded systems (ex now Raspberry Pi 5) coupled with ESP32 as a sidecar. So, the core OS is running on the Pi and is reading data off the ESP32-connected sensors, basically.
There are only AI renders and photos of the first prototype works, but I’m working on the actual schematics and renderings that I’ll publish once the hardware open source repo is ready.
Another slop Show HN. The repository doesn't even have any particular relation to the bullet points here, theres no hardware, theres just a bunch of tokens spent.
There should be a requirement to put (AI) in the title if your project is entirely LLM built.
Thanks for the feedback. The repository contains the OS system that is powering the device, and another one for dataset. I’ve put a lot of effort into documenting both the vision, progress, and practical instructions, but if there are particular sections you think needs more work - would be very happy to hear.
The hardware component will be open sourced in a separate repo, once the prototype is tested in the field to validate the configuration. I hope to make it public in January.
Just wanted to elaborate on the state of the project and the goal.
think of it as a modular field computer inspired by Flipper Zero, but aimed at outdoors/survival/trades folks instead of security people.
Right now I'm deep in the software/OS layer - getting the core system working (Qt/QML UI, Docker services, on-device AI with Phi-3, offline maps, Meshtastic integration). Once I validate everything with field tests, I'll finalize the hardware design. It's built on Raspberry Pi 5 + ESP32-S3 doing the heavy lifting for LoRa mesh comms and always-on sensors.
The big idea is making something that's flexible like Flipper Zero but for different use cases - you could run apps for hunting, survival navigation, plant identification, whatever fits your lifestyle. The app ecosystem is key - I want developers to easily build specialized tools that work in their workflow.
Communication-first design too - Meshtastic for long-range mesh when networks are down, with graceful degradation from LTE → WiFi → LoRa → GPS beacon. The whole thing is designed to work offline-first - max functionality with zero internet dependency.
Still super early (hence the software focus first), but the goal is a rugged platform that people can actually build on and customize for their specific needs. Not trying to replace phones, just be the reliable tool that works when phones don't.
Will the screen be daylight viewable? (and no, trying to out-bright the sun on a battery-powered device is not a valid answer)
E-ink or transflective LCD or maybe the modified LED used by the Daylight Computer folks.
Agree that AI needs to go as not reliable enough for life-death situations.
Good point, I’ll be testing both. e-ink is great from power management standpoint, but I want to see how some apps will be rendering (ex maps)
> agentic AI
Yeah I don't want LLMs near anything life or death, where a hallucination can kill, thank you very much.
Agree with you on that, it was my concern too, but the way I think about it is access to information, the goal is not to provide hallucinations with a straight face (aka GPT), but rather use it as a way to extract necessary information fast. For instance, I have a built-in RAG that reads of growing collection on books on medical, survival, etc. (https://github.com/dmitry-grechko/waycore-knowledge) that AI agent is using to answer questions. Moreover, it has a built-in safety loop to always inform users on the accuracy of the information, but also if the information request has an impact on health & safety, it will warn users about it too.
So, I certainly see the inherited risk and problems, but mostly think about it as a means of information extraction
Putting the lookup in the AI means it can hallucinate the lookup. Putting the assesment of risk in the AI means it can fail on the assessment.
Please reconsider using a full text search index instead.
Good point. I’ll add it to the roadmap. I still want to experiment with AI features as I feel it can add value despite hallucinations, but safety and transparency are crucial - completely agree.
wonderful... this is something I hope would come up going forward. I see this a little in the japanese electronic dictionaries still being developed and released
Yeah, ages ago, I installed all of Microsoft's Encarta on a CF card which I was using as a drive on my Fujitsu Stylist 2300ST --- it was way cool to be able to haul it out and look things up w/o a network connection (or a CD-ROM drive).
Wonder if that would run in a current version of Windows...
This reminds me of https://radiant.computer/
Thanks, haven't seen it before, but love the idea of it. It certainly takes the concept a lot futher that I intended with this project. My goal is far is to relyt on well-supported open source tools and frameworks, and give both the software and hardware flexibility for people to create what they need. Think of it like FlipperZero, but for outdoors
Any relation to the Daylight Computer folks?
https://daylightcomputer.com/
Not on my side, but it looks awesome. +1 to the e-ink point above.
Very similar to something I have been building this year. Do you already have hardware side ideas anywhere?
Love that I am not alone in this thinking! I test it on embedded systems (ex now Raspberry Pi 5) coupled with ESP32 as a sidecar. So, the core OS is running on the Pi and is reading data off the ESP32-connected sensors, basically.
Is there any pictures of the device?
There are only AI renders and photos of the first prototype works, but I’m working on the actual schematics and renderings that I’ll publish once the hardware open source repo is ready.
Another slop Show HN. The repository doesn't even have any particular relation to the bullet points here, theres no hardware, theres just a bunch of tokens spent. There should be a requirement to put (AI) in the title if your project is entirely LLM built.
Thanks for the feedback. The repository contains the OS system that is powering the device, and another one for dataset. I’ve put a lot of effort into documenting both the vision, progress, and practical instructions, but if there are particular sections you think needs more work - would be very happy to hear.
The hardware component will be open sourced in a separate repo, once the prototype is tested in the field to validate the configuration. I hope to make it public in January.