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...UNO format mcufriend shields) can use with the STM32 Nucleo 64/144 range or the UNO format ESP32. ILI9341 and ST7796 SPI-based displays are recommended as starting points for experimenting with this library. The library supports some TFT displays designed for the Raspberry Pi (RPi) that are based on a ILI9486 or ST7796 driver chip with a 480 x 320-pixel screen.
Advanced hardware data vault designed to maximize the cost of unauthorized access to your data.
https://midbar-official-website.netlify.app/
Attention: The latest ESP32 version of Midbar compiles successfully in Arduino IDE 1.8.9 with ESP32 package v2.0.8. There might be compatibility issues with other versions of the ESP32 package for Arduino IDE.
STM32F401CCU6 + Arduino Uno Version V1.0: https://www.instructables.com/Midbar-STM32F401CCU6-Arduino-Uno-Version/
RTL8720DN + Arduino...
...However, after exploring it for roughly an hour, I started thinking about its practical applications and where I could use it. Eventually, I realized that I could use it to generate unique images and then display them on the 2.4 Inch TFT LCD with ILI9341 connected to the Raspberry Pi Pico.
If you wish to learn how to do the same, follow along with this tutorial: https://www.instructables.com/Miniature-Digital-Photo-Frame-With-AI-generated-Im/
The KhadashPay project is an open-source payment system.
The KhadashPay project is my attempt to make a payment system from scratch.
As for the customers of the store where the KhadashPay is deployed, Khadash pay doesn't keep any logs whatsoever and doesn't require a bit of your personal information to create an account.
You can find the tutorials here:
V2.0 (ESP32 Version): https://www.instructables.com/KhadashPay-V20/
V2.0 (Raspberry Pi Pico Version): https://www.instructables.com/KhadashPay-V20-Raspberry-Pi-Pico-Version/
V3.0...
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...I only take credit for writing down the instructions, creating and uploading the img files. I modified the original code to make it functional on a wide range of devices, not just a TFT.
The process was tested on a Toshiba laptop first, running debian, then on a Raspberry Pi 2 - from which the images were created.
All other credit is WELL deserved by the original citizens that wrote the software used in this project.
Raspberry pi + adafruit cap tft + ada fruit case +python code
Raspberry pi
adafruit capacitive touch tft
ada fruit case for pi
ldr +capacitor for background light level
dfc77 receiver for time
python code based on wiringpi2, pygame