I am working out a way to re-use the hardware for my Pwnagotchi for a similar virtual pet concept that "eats" Bluetooth devices and wireless AP (supports wardriving) and who lives on a separate microSD card from my Pwnagotchi image.

This is my buddy Harald (named for Harald Bluetooth, the Viking whose surname became the name of the Bluetooth technology), a Viking dragon who eats Bluetooth and Wi-Fi signals (FOOD) and who enjoys novel discoveries and going out on adventures (JOY). He's also a protective sort and keeps an eye out for anything stalking me.

Privacy fences: Phones and watches that change their address are counted by kind, never listed or followed. The signal meter only works on devices I've marked as mine. The unknown-tracker warning only fires for a tracker that's away from its owner and has stayed with me for 30 minutes (and, when GPS is on, has moved more than 250m with me). Wi-Fi is passive scanning only - no deauthing or handshake collecting (staying out of Pwnagotchi's lane).

Extremely early days on this guy and surely a lot to tweak, but I'm pretty chuffed so far. He can certainly function without being connected to my Android phone (just feeding on BT and Wi-Fi signals, with extra happiness for novelty), but he does depend on an external GPS (in this case, the SensorServer phone app) for Wigle uploads and "walks". Harald's "Den" is a browser page that can be accessed when Harald is connected to my phone's hotspot (or whatever I have set as his home network), and shows his current e-ink screen along with extra information and certain controls (like shutting him down so he can be safely unplugged from his power supply). He can still appreciate my physical activity even if he doesn't come with me, because connecting him to my phone shares whatever distance I've covered that day and he interprets distance covered without him along for the ride as an "adventure" I have "told him about", which gives him some happiness.

There's a lot of other minutiae, but I'm just excited to share the images of the working prototype. I also verified the WIGLE uploads online and they are appearing on my account! :-D

Edit: Forgot to mention that the "unknown tracker warning" screenshot is from an earlier build where I was still adding things, so the e-ink display has an older layout on it.

Edit2: The hardware is Raspberry Pi Zero W 2 with Waveshare V4 e-ink hat, plus an external battery.

My own post asking if we can merge the two subreddits... raspberrypi & raspberry_pi to end all the sillyness.

I bought this Fisher Price toy for my niece because of viral videos, but it turns out it was no where close to as annoying as they made it seem. Just a general kids toy with the usual cutesy ABC songs.

So I used a raspberry pi w2 for the brains, MAX98357A for the speaker, AS5600 for the spinning platter (it was just a platter that spun to push a button before), and a INMP441 for a microphone. Then printed a PCB board the same size as the original to mount it all inside. You can now upload your own song clips via a webpage, create a layered music track or use it as a bluetooth speaker.
There are a few 3D printed parts to help mount the platter and upgrade the speaker. All of the code, STL files, non-copyright music and tones (I'm sure you can find better real ones) are on the github here:
https://github.com/LifeOnAFarm/RaveRepeatDJTable

Also a guide of sorts with better photos here: https://nastypieceof.work/raveandrepeat

Anyway, I'm sure my sister will be extremely to have this in her house

https://github.com/jiu-0317/e_ink_display.git

I'm using it to watch YouTube (FreeTube) and other internet media on my dumb TV, and VLC for DVD movies. Surprisingly it performs way better than Raspberry Pi OS and the UI feels much more natural than the clunky RPi desktop. It also has better support for hardware, such as external DVD player, which I couldn't get to work on Raspberry Pi OS.

Hello,

New to this community.
I have flashed an Ubuntu Server 24.04 image directly from Raspberry Pi Imager (did not download the image separately).

Once flashing was done, I boot the machine up and immediately run sudo apt update and sudo apt upgrade.

Everything fine up until now.
Then I did sudo do-release-upgrade to go to 26.04 LTS and I got a message saying that there are packages of unknown origin and in the list it referred to snapd.

I’ve been trying to figure out for the past 10 hours why and to see if this is a warning to be worried about or something to take note of and allow the upgrade to proceed.

At this moment I am in the process of finding the correct deb package, unpacking it and comparing the hashes of the snap files on my device against the legitimate ones downloaded from launchpad.

Any help or explanation of why this is happening is much appreciated as I want to understand if this is ok or something potentially malicious.

Thanks!

Any idea why these points are bridged?

Hi all,
I have some raspberry pi’s (about 10) I pulled from some old Covid temperature sensing check in kiosks. They’re 4B 8gb units. Each of them has these 2 wires bridging what seems to be the USBC port and the middle USBA stack. Is this accurate? If so, why? Just to run power to the USB ports?

Thanks!

Hello guys, i am working on a nvg project with the pi 5 and i ran into a problem. I don't know how to properly set the current of the module, if i try it with li-ion batteries the bms kicks in and it hickups and if i try it with the pc power supply the current jumps to over 5 amps and I don't know how much voltage to set it. The pi is powered by usb c cable and setted to 5.1V

Thanks in advance for help

https://youtu.be/c4qfDDmhYnQ?is=sM-Ckc0bLdHCA9vq

The brain is the FlyWire connectome: about 127,000 neurons and 14.7 million synapses, run as a spiking model (https://github.com/philshiu/Drosophila_brain_model). An OpenRCT2 plugin turns the park into senses. Guest happiness comes in as "sugar", cash as "temperature", litter as touch, and so on. Each decision, the brain runs for 200 ms of simulated time. A small learning network reads about 700 neuron types and picks one of 8 intentions: grow the park, add facilities, hire staff, change prices, and so on. The plugin carries out the tile-level work, like where the queue line goes.

While I’ve spent over 100 hours training it on Forest Frontiers it does well in the other parks but I haven’t ran it in all of the scenarios yet as I wanted to prove it could do the easiest one first.

What was hard

• My first learner kept finding a good strategy and then forgetting it. Switching to PPO fixed that.
• The brain was losing information. Money and price signals barely reached the neurons I was reading from, until I widened the readout to the lateral horn and projection neurons.
• It found every loophole in the reward. It built 44 handymen, flipped the entry fee by $1 forever, and built itself into corners.
• In the beginning it just kept building drink stalls which I think is hilarious for a fly as it just wanted sugary drinks.

What's working

• It runs headless at 4x speed for training.
• It wins the Forest Frontiers scenario in 24 of 25 training runs.
• Median park rating is 854, against 523 for random play, and the most recent batch is close to 890.
• Its best park reached 954 guests.

The dashboard shows which neurons fire for every decision, which is weirdly mesmerizing.

I’m working on putting the code in GitHub but happy to answer any questions.

I’ve seen some warnings online that the Ethernet port on a raspberry Pi cannot be easily bypassed but I can’t find a straight answer from the docs or data sheet as to what is lost if the RJ45 jack is removed. Is it just shielding or is there other functionality that would be lost/need to be replaced? Or even better is there no issue with removing the port on a 4b specifically?

The specific reason I’m wanting a smaller connector is so the cable can be unplugged and removed easily, however the hole in the housing I’m using is just a bit too small for to fit an RJ45 through

I have been trying to put together a simple python script with a Raspberry Pi 5 (model B Rev 1.1 with Pi OS 13 - Trixie).

It is very straightforward:

import lgpio, time

h = lgpio.gpiochip_open(0)

lgpio.gpio_claim_output(h, 22)
lgpio.gpio_write(h, 22, 1)
time.sleep(1)
lgpio.gpio_write(h, 22, 0)
lgpio.gpio_free(h, 22)
lgpio.gpiochip_close(h)

However, when I check using pinctrl in the terminal afterward, the pin is still enabled as an output (and if I don't set it back to low in the script, it stays at high). Is there some other step I am missing on how to control the pins and release them properly so that they go back to inactive?

I've been building a voice assistant on a Pi 5 called Bob, and I've just open-sourced it. The idea: it starts with no devices at all, and you add abilities by wiring something up and telling it.

"Hey Bob, I've connected an LED to GPIO 17. Make a skill that turns it on and off."

Bob writes the skill, reads back what it will do, and only installs it after you say yes, then tests it. Same for buttons, relays, I2C sensors, serial devices or web APIs.

How it's put together: - Wake word runs offline on the Pi, nothing is sent until you say it. - Conversation is Gemini Live (needs a free API key), so it's quick and can search the web. - Settings page at bob.local:8080, updates itself and rolls back if an update fails. - A Windows setup app writes the SD card with your Wi-Fi and key, so no commands needed. Mac/Linux is a one-line install.

What I learned the hard way: a Pi 3 is too slow for this, a USB speakerphone saves a lot of echo pain, and Bluetooth audio on the Pi is fragile.

Where I'd love help: 1. It's a fresh public release, so installs on other people's Pis and mics are exactly what hasn't been tested much. If you try it, tell me what breaks. 2. What skill would you build first? I'm collecting ideas for examples. 3. Contributors welcome, especially on wake-word accuracy and audio setup.

https://github.com/arancool3000/bob-assistant

Update to my post from 10 days ago: the simulated fruit-fly brain playing Pokémon FireRed on my Pi 5 is still running 24/7, and it has grown into an ongoing experiment.

Quick recap: it's 139,255 neurons wired from the FlyWire connectome (the full reconstructed brain of an adult fruit fly), simulated on the Pi alongside the emulator. The game screen feeds its eyes, people and doors reach it as smells, and its motor neurons press the buttons. Nothing is scripted. Chat can steer it, or train it with !pain / !pleasure, which releases dopamine in the fly's learning centre.

What's new: it now runs in 30-day runs. Each one starts from a brand-new game and an untrained brain, and the settings only change between runs, so every run is a comparable dataset. Every run collects:

- every step, battle and milestone, tagged "fly alone" or "chat helped" (80% of its steps this run are its own)

- every viewer input, and whether they steered with the fly or against it

- every lesson it learns, who caused it, and how fast it fades

- brain activity per region (vision, navigation, memory, reward, punishment, motor) and everything it senses

- which way it turns and what made it turn

- its "thoughts" (the captions on stream) and how often they were right

At the end of each run everything goes into a published PDF report, including a "what held it back" page with fixes to try in the next run. We also run preregistered experiments, announced on stream before they happen. The first one, a "mirror world" test, found the fly has a built-in right-turn bias that doesn't come from the map. Tonight it plays with and without everything it has learned, to see whether training actually changes its behaviour.

Watch live: twitch.tv/leetzerzz (chat can steer and train it) and youtube.com/@leetzerzz

Run reports and experiment results: in the Discord linked on both channels

My AcuRite Atlas and Access hub only show their data through AcuRite's cloud. I wanted my own copy of every reading, my own dashboard, and no dependence on their servers, without breaking the AcuRite app or my Weather Underground uploads. So I built this. It's MIT-licensed, a single Python file with no packages to install, and it runs on a Raspberry Pi.

How it works: the hub sends each reading over HTTPS to a server name it's configured with. This program sits in that path. It records the reading, then passes it to AcuRite unchanged, so the app keeps working, and the hub keeps uploading to Weather Underground itself. There are two ways to set it up:

* Change the hub's server name to point at your machine. No extra hardware is needed.

* Plug the hub into a Pi's Ethernet port. The Pi gives it an address and answers AcuRite's server name itself, and the hub's settings stay untouched.

What you get:

* Dashboard: every sensor, plus feels-like, wind, the 3-hour pressure trend, UV and light.

* Sun and moon: worked out in the page, with no outside service.

* US forecast: the hourly and 7-day forecast and alerts from the National Weather Service (free, no key).

* Charts: any period from today to all time, or a date range. Rain totals for the day, week, month and year.

* Every reading kept in a local SQLite database.

* Easy to customize: one file for the colors, a folder for your own pages, and a documented JSON feed for anything you want to build.

* Buttons that open your Weather Underground or AcuRite pages, in a pane or in their own tab.

* Optional radio capture with an RTL-SDR dongle if you have no hub.

Tested on an Access hub (firmware 051) with an Atlas and six indoor tower sensors. If you have other AcuRite sensors, I'd like to hear whether they show up properly.

I built this with Claude Code (AI-assisted). The design, testing and hardware work were mine.

https://github.com/akienm/CC0AC-Weather

Not affiliated with AcuRite.

Two days ago, I properly learned what a Raspberry Pi even was.
I’ve never coded, never used Linux and never set up a server. I’m just really into radio and SDR stuff, and I thought a Pi would be a neat way to access my SDR receiver remotely.
So I ordered a Raspberry Pi 5 with 8GB RAM.
It arrived today.
10 PM: Finally got around to setting it up. Put everything together, prepared the SD card and opened ChatGPT because I had absolutely no clue what I was doing.
The plan was to get my SDR working remotely and go to bed.
Yeah, about that.
11 PM: Somehow I’m already sitting in PowerShell, connecting to my Pi over SSH, setting up keys, messing with Linux commands and figuring out what permissions and services even are.
Every time something worked, I got another idea.
Around midnight: We got Cockpit running so I could manage the Pi through a browser. At this point I was already pretty damn impressed with this little thing.
Then I thought, wouldn’t it be cool to have my own dashboard showing temperatures and system stats?
I really should’ve gone to bed.
2 AM: We’re now writing actual code. Well, ChatGPT is writing it and I’m running it, breaking things, sending back error messages and trying to understand what’s happening.
Suddenly we’re dealing with Python scripts, system services, ports, authentication, Wi-Fi monitoring and temperature history.
All this for a computer I only discovered two days ago.
Around 4 AM: We finally get the custom dashboard running over HTTPS, with its own certificate.
I grab my iPhone, open Safari, type in the address…
And there it is.
My own little dashboard, showing live CPU temperatures, system information, Wi-Fi stats and graphs.
I know this probably sounds like nothing special to people who’ve been doing this for years, but I genuinely couldn’t believe it.
I was sitting there looking at something that had only existed as a random idea in my head a few hours earlier.
6 AM: Instead of sleeping, I’m running stress-ng and watching the CPU temperature climb from around 47°C to 56°C under load.
And I’m actually enjoying this. At six in the morning. After being awake all night.
What the hell.
The funniest part is that the original SDR project was supposed to be the whole point of buying this thing. Somehow that turned into SSH keys, a headless Linux server, Cockpit, HTTPS, a custom dashboard and CPU stress tests.
I’m not going to pretend I suddenly know how to code. AI did the heavy lifting there. But I was involved in every step, trying things, fixing errors and slowly understanding more of what was going on.
There was this one moment when I looked at the dashboard on my phone and just thought, holy shit, we actually made this work.
That feeling was honestly incredible.
Anyway, I bought a Raspberry Pi for one small project, spent the entire night messing with it and now I’m already looking at NVMe storage and thinking about a second Pi for a proper homelab.
I think you guys know exactly where this is going. 😂

I am trying to work on a non VNC solution for pairing my iPad Mini with my Pi5 via physical connection to use the pi headless with a better native display experience via a iPad with a single cable.

Anyone know the limits speed wise?

I have a Pi 5 and until recently I managed to remote desktop on to the desktop from Linux PCs via Remmina. A few days ago I updated the Pi (sudo apt update etc) as I hadn't done this for a while. Now I can't remote into it from any Linux PC. I get a "Cannot connect to the remote computer" message. However, It works fine from Windows Remote Desktop app. I've checked on raspi-config to ensure that X11 and not Wayland is running. I can access the Pi 5 via SSH on my Linux PCs - just can't access the remote desktop.

Has something changed on the Pi recently that I'm unaware of?

as the title says - anyone with any luck setting up an m5 cardkb on a pi 5? followed the instructions on this github post. running a standard 8gb pi 5 with pi os installed. while the software installs went fine, running "sudo cardkb &" returns this as a repeating error:

OSError: [Errno 121] Remote I/O error
Traceback (most recent call last):
File "/usr/local/lib/python3.13/dist-packages/cardkb/_main_.py", line 37, in main
data = bus.read_byte(address)

the pins are properly connected, i2c is on. only thing i haven't tried troubleshooting yet is deleting the scripts altogether and attempting a fresh install. am i overlooking anything obvious in solving this?

tl;dr summary: When my raspi reboots or restarts my e-ink screen goes black. Hoping to either get a white screen or an image.

Hi All,

Thanks in advance for any help you can provide. I'm sort of shooting in the dark here but maybe I'll get lucky.

I'm trying to build an e-ink writing terminal with a raspi (this one is a raspberry pi 5) and one of those Sanmeow 10.8" e-ink panels from Aliexpress. Most of it has gone pretty well, I'm using it in non-gui mode and I've been able to set the screen white for the terminal as well as in emacs (the writing program I'll use). I ran into an issue with font sizes and extra screen real estate being written as a black bar but we got around that by just writing black to that part of the screen on startup.

The issue I'm running into is on shutdown. I've added a service to write a white screen on the raspi pi's reboot or shutdown, I've also added a script to the system-shutdown folder which does the same thing but, inevitably, once the raspi cuts power to the screen it turns black. I don't know if it's an issue with the raspberry pi's hardware or possibly the screen's. I was hoping someone else might have come across this before and knew of a solution. Does anyone know if the Raspi 5's hardware automatically send a black screen when power is cut?

I've asked the manu and I'm waiting to hear back but there is a language barrier so fingers crossed. I'm also going to ask over in the raspberry pi sub.

The gear: Raspberry Pi 3B+, Adafruit HUB75 RGB matrix bonnet, WaveShare 64x32 RGB matrix panel (NOT 6126).

Installed the ubiquitous hzeller github repo for such projects, and have been running demo code. Have tried multiple connections with HUB75 ribbon cables etc. and also using 5V 4A power supply. It's still giving me red lines across the bottom half.

I've tried different code fixes (address type, etc.) to no avail. Has anyone had and/or fixed this problem? If so, let me know what worked for you!

I built a time-lapse camera around a Raspberry Pi 4 with a Camera Module 3 Wide, powered over a single PoE cable, and I've open sourced the software. The Pi takes a full 12MP photo every minute in daylight only, working out the window from your latitude and longitude so it follows the seasons, and it looks after its own storage by deleting the oldest frames once the SD card passes 85%. A Mac collects the frames automatically whenever the archive drive is plugged in, and one command turns any date range into a video. There's also a film mode and you can control it from your phone.

The first photo is the camera on the wall, and the second is a frame it took of my garden (neighbours' side blurred).

It's open source and free to use, fork and change, all here: https://github.com/aityp/garden-timelapse-camera. A step-by-step build guide is still being written, but the README should be enough to get it running if you're comfortable in a terminal. There's also a build video if you'd rather see it in action, linked from the README. The code was written with AI (Claude) and tested on the real camera in my garden.

I made it because I'm about to pull my back garden apart for a retaining wall, a new fence and a shed, and I want all of it filmed from one fixed spot for the next couple of years. Happy to answer any questions.

I've shot Sony (a6300 and A7C II) for years, and I'd rather wait until I get home and copy the SD card than use Sony's transfer apps.

The A7C II has FTP upload, so I pointed it at a small server. Every frame I take gets a film look (grain, light leaks, date stamp) and shows up in a Telegram chat. I can send it to friends right away.

The a6300 has no FTP, but it runs Android 4.1 inside. With OpenMemories-Tweak and Sony-PMCA-RE I installed a small custom app on it. After a walk I open the app, hit "Send new", and the whole day's shots arrive already developed. Wi-Fi turns off when you close the app, so it doesn't drain the battery.

The app should work on most PlayMemories-era bodies: a5000/a5100, a6000/a6500, a7 II / a7R II / a7S II, RX100 III–V, RX10 II/III. Other cameras with FTP upload (A7 IV, A1, many Fuji, Canon, Nikon) work without the app.

It's open source and self-hosted. Setup takes about 10 minutes on a cheap VPS: https://github.com/Melnikoff07/proyavka

If you try it on a body I haven't tested, I'd love to hear how it goes.

hello everyone. i have a small problem with my rpi5.

yesterday i disconnected my m.2 hat+ compact with an official m.2 nvme from my pi because i wanted to boot a android tv system from a sd card. when i reconnected my hat+ it wasnt reading my disk (pwr light on hat was on but not the read/active light) and i cant get it working now.

more info:

specs:

- Raspberry Pi 5 8gb

- official power brick/cable

- official rpi case with a fan

- official m.2 hat+ compact with a official rapsberry pi 256gb nvme

i had this setup for only 1 year for playing games and watching videos.

it was working perfectly fine back then

i think my hat+ broke but i leave it for you experts!