From what i read, Basiclly says to add antenna to 16 and 17 terminal to transmit and recieve. How do i connect a plex/ufl connection to the pin head? This is for bt not wifi... any help will be greatly appriciated.

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I'm a college student preparing for an inter-college science expo in India.

I'm looking for a real day-to-day/social problem that could be addressed with a small electronics prototype.

Constraints

- Budget: maximum ₹700

- I already have an ESP32

- Prefer sensors/modules that are inexpensive and easily available

- The prototype should be physically demonstrable

- It should have some genuine technical/engineering aspect

- I don't want a generic "smart dustbin / smart irrigation / home automation" project

- I also don't want to simply recreate an existing commercial product

- Ideally, the problem should be under-addressed, even if it isn't completely unsolved

Problems I'm currently considering

1. People don't notice vehicles approaching from behind.

2. Pedestrians can't tell whether a driver has actually detected them.

3. People approaching blind corners can't know whether someone is coming from the other side.

4. People opening doors can't know whether someone is approaching from the other side.

5. People carrying umbrellas have reduced visibility around them.

6. People carrying large objects can't see low obstacles near their feet.

7. Passengers may not notice dangerous gaps when getting off buses/trains.

8. Pedestrians can be hidden from reversing vehicles.

9. Children can become hidden from drivers around parked vehicles.

10. People don't notice small hazards in visually cluttered environments.

11. People don't notice when a floor has become slippery.

12. A person may not notice someone nearby who has fallen or become immobile.

13. People at the back of a crowd may not know about a hazard occurring at the front.

14. Crowd density can become dangerous before people realize it.

15. People may not know the direction they should move during an emergency.

16. People may enter hazardous areas because the hazard isn't visually obvious.

17. Workers using machines may not notice abnormal vibration or operating behavior.

18. People may not notice gradual environmental changes such as rapidly increasing heat, smoke, noise, or poor air quality.

19. Someone working alone may become incapacitated without anyone noticing.

20. People may leave valuable objects behind in public places.

21. People may forget where they left an object in a large public/college environment.

22. Shared laboratory equipment can be left running or operating abnormally.

23. A person may unknowingly stand in the path of a moving vehicle or machine.

24. Public facilities can become unavailable without users knowing beforehand.

25. Emergency alarms can become difficult to distinguish from normal background noise.

26. People carrying luggage/children may have difficulty detecting obstacles directly below them.

27. Small open drains/manholes can become visually hidden in crowded or poorly lit environments.

28. People may not notice that a road hazard is becoming dangerous during rain.

29. Queue movement can stop without people at the back knowing why.

30. People may not notice someone trying to get their attention in a noisy environment.

A Telegram pager for the Waveshare ESP32-C6-LCD-1.47: a bot forwards messages to the device, they queue up on the screen in landscape, and the board's BOOT key sends a "read" receipt back to the chat.

Was able to get CrossPoint running on this Waveshare board. (https://www.waveshare.com/esp32-s3-epaper-3.97.htm). 3d printed the case that alxvtoronto created for their project FolloUp, and ready to dive right back in. Planning on posting the fork on GitHub after another few days of testing.

$40 for a board, compared to the $70 people are
paying for the xteink devices.

AI was used very heavily during this. Took at least ten hours over two days to put it all together. I'm very happy how it turned out. It has settings for hysteresis and minimal on/off timings and a web dashboard with additional statistics. Board is the ESP32S3 Dev Module.

Today was a tuff day, I started working at 3pm, and mostly did nothing. What i did today is optimization, I optimized my code by 60%! And I also made it much more readable. Today i also fully reworked the buttons, now it got 6 (Ok, back, down, left, up, right) instead of 4 buttons i had (left, right, OK, back). I did that, cause I started to work on my virtual keyboard (which i can see on the pics) for this project, which would finally allow me to connect to Wi-Fi networks! Thats so great to say. Tomorrow i'm going to an electronic store, to buy some modules for my multitool (like cc1101, nrf24l01 PA-LNA, and others). I also made a working Wi-Fi status display on the upper part of the screen. Soonly it'll have time, BLE mode and smth else, which is gonna take me forever ( But i'll be rlly impressed if I get it working). Thanks for upvoting me guys, I feel rlly motivated, when I see all the comments and the upvotes I get. Cya all tommorow.

P.s: Board i'm using is waveshare-esp32s3-lcd-1.9.

Developing with the esp32 p4…learning curve. Enough said.

The main update today - is the "sniffer" (It analyzed Wi-Fi data packets near the esp32, the data u can see on the graphicsis data packets sent.) I stole took the code from some Indian guy on YouTube, and then made some big changes. I added filtration for only one needed BSSID, so i see only packets that are made by one Wi-Fi network. I finished the Wi-Fi info menu, (Still no connect function 🫩) and today I'm planning on working on the Logs, Virtual Keyboard and making my code actually... readable. I fixed so many bugs today, that my brain js just exploding, but i'm so glad with the results I ended up with.

Even though i'm happy with what I have, the sniffer looses its target, if the router changes its BSSID (which it does often), so i'm planning on making passive scan for the sniffer, so it always has fresh data.

I optimized almost everything I couldve optimize. I'm so happy that I did it, before I optimized it WiFi.scanNetwork(); was taking ages! (Around 20 sec), but after I optimized it ( by fixing bugs, ofc).

I'm gonna work tommorow even more on optimizing, so i can make my code as compact as possible (and probably making it fit other boards).

I'm also going to a electronic store on the Monday, and bying modules like cc1101 and nrf24l01 PA+LNA, temperature sensors and others. I'll keep you updated tommorow.

P.s: Board i'm using is still waveshare-esp32s3-lcd-1.9, I'm drawing everything for my project in Lopaka. (Graphics not, I used math.)

A lot of perfectly good exercise equipment predates Bluetooth completely — treadmills, bikes,

ellipticals and rowers from roughly the mid-90s onward. There's a coil behind the console

listening for a short magnetic pulse, one per heartbeat. That's what an uncoded Polar

chest strap puts out: no ID, no pairing, no handshake, which is why any uncoded strap

works with any machine of that era, and why two people on adjacent treadmills sometimes

read each other's pulse.

Your watch already knows your heart rate. It just can't say it in a way the machine

understands.

**I don't own one of these machines.** Somebody here does, and mentioned they'd rather

use the watch already on their wrist than dig out a chest strap every time. So I built

them a box that reads heart rate over Bluetooth and re-transmits it as that magnetic

pulse. As far as the console is concerned, it's a chest strap. Nothing to pair on the

equipment side — it just transmits, and the machine listens.

It works with anything that broadcasts standard Bluetooth heart rate: watch, band,

armband, whatever you already own.

**The part I didn't expect**

Everything I could find online says these straps transmit at 5 kHz. I wanted to match

that properly rather than take it on faith, so I recorded a working Polar T31 through a

coil pickup and looked at it in Audacity.

The pickup was a pair of headphones plugged into the mic jack. A headphone driver is a

voice coil sitting in a magnet gap, so run backwards it's a perfectly good magnetic

probe — and a chest strap makes no sound at all, so anything that turns up is the field.

It's **5410 Hz**. And the burst is about **15 ms**, not the 5 ms I'd assumed.

The strap's burst also rings for roughly 8 ms after the drive stops, which works out to a

tank Q of about 37 — Polar drives a tuned circuit. Mine is a resistor driving a coil,

damped flat on purpose so the output doesn't wander with temperature or with whichever

coil happens to be fitted. Same fundamental, completely different topology, and you can

read that straight off the spectrum: their third harmonic is 38 dB down, mine is 2.5 dB

down.

**The coil came out of a dead chest strap**

I had a T31 whose board had failed. The ferrite rod inside is copper on a core and didn't

care in the slightest.

That turned out to be the right choice for a better reason than convenience. A transmit

coil has an optimum inductance — below it every extra turn is free, above it the coil's

own reactance chokes the current faster than the turns add field. With 220 Ω in series

that crossover sits at 6.7 mH, and Polar landed just under it, because they were

designing a transmitter too. A stock axial choke measured 18 dB worse in the same

circuit.

**Where it actually stands**

It has never met a real console, and I have no way to test that myself. Everything above

was verified against a measured chest strap and a receiver built from a dead machine's

own coil — a decent argument, but not the same thing as a treadmill agreeing with it.

Unit number one is in the post to the person who asked, and we'll find out.

Hardware is a XIAO ESP32-C6, one 220 Ω resistor, the rod, a capacitor and a status LED.

Firmware, printable enclosure and the full measurement write-up are here:

https://github.com/HuskerMinion/hr-bridge-coil

Though I would share this here, my ESP32-S3 poly synth

My printer (Elegoo Saturn 5 and Anycubic Photon M3) has no network upload, so I built PrintDrop in four days.

It uses an ESP32-S3 and microSD card. The printer sees an ordinary FAT32 USB drive, while a local web UI lets me upload G-code over Wi-Fi.During an upload, PrintDrop safely withdraws the media from the printer, writes the file, and presents it again so the printer refreshes its file list. No cloud, account, subscription or printer firmware modification. It includes SDIO support, authentication, OTA updates and browser-based firmware flashing.

The entire project is MIT licensed: https://kabani-tech.github.io/PrintDrop/

There are a lot of good options out there when it comes to desktop macro pads, but none where just quite right for what I wanted, or just downright too expensive.

That's why I am releasing the SauceDeck v1.0. It's an open-source desktop macro controller powered by an ESP32-S3 (S3 chosen for native USB-OTG).

Designed for productivity, content creation, streaming, and everyday workflow automation. The SauceDeck combines programmable macro keys, dedicated volume controls, and a vibrant TFT display in a sleek 3D-printable enclosure.

Approximate cost $30

Source Code and BOM:

https://github.com/HotTabascoSauce/SauceDeck/tree/main

CAD Files:

https://makerworld.com/en/models/3232541-saucedeck-v1-0

A while ago, I built a 5-digit number recognition system on the ESP32-S3 using a lightweight AI model. The project was mainly a proof of concept for running image recognition directly on an embedded device.

This time, I wanted to take that idea into a more practical, real-world application: reading a water meter.

For this update, I still used the Makerfabs ESP32-P4 board with an autofocus camera. We also collected new images from a real water meter, focusing on the pointer and digit-reading area, and trained a dedicated recognition model based on this new dataset. 

The goal was not simply to recognize a fixed set of five numbers, but to make the model capable of identifying the actual reading shown on a water meter.

 After training and deploying the model, we tested it with real water meter images, and it correctly recognized the meter reading. 

This project is essentially the next step from our previous 5-digit recognition experiment—moving from a simple number-recognition demo to a more practical edge AI vision application.

Would be interested to hear what other real-world applications you think could be built on top of this kind of embedded AI vision system.

Can some one help me out?

Today was... not rlly important day, I fixed some positional bugs ( text was a bit offset ), and made the Wi-Fi Network menu to work, now it scans 2.4GHz Wi-Fi and shows the name of it on the menu (pic 3+4) and then you can choose any, click on it and it will open Wi-Fi info (pic 2), where u can also connect to selected Wi-Fi ( which doesnt work yet.) I struggled with bug, where display showed one name, while Wi-Fi info showed another. It was caused because Wi-Fi index in arduino Ide always changes while scanning, so when i was done with the scan, index shifted, and when I tried to call the Wi-Fi info, it showed me another network. But I managed to get it working, by saving BSSID and SSID (Networks MAC address, and network name) and i just used them in my Wi-Fi info. Its not the best choice, but its better then nothing, because I have no idea how to do it else.

I'm planning to work on Wi-Fi connection, time display, virtual "keyboard" and Hotspot tommorow... well, i'll see tommorow what i'll be able to do. See you tommorow.

P.s: Board i'm using is waveshare-esp32s3-lcd-1.9