This tutorial demonstrates how to set up a MicroPython web server on an ESP32. A web page will show the temperature and humidity from a DHT22 sensor connected to an ESP32. Another web page will provide remote color and brightness control of a NeoPixel RGB LED.
This tutorial demonstrates how to connect a DHT22 temperature and humidity sensor to an ESP32 running MicroPython. The sensor data is transmitted wirelessly to a Raspberry Pi using MQTT protocol and the results are displayed on I2C OLED display.
This tutorial demonstrates how to set up and program an ESP32 device running MicroPython from a Raspberry Pi.
This tutorial demonstrates how to control bi-polar stepper motors on a Raspberry Pi in Python using a DRV-8825 stepper motor driver.
This tutorial demonstrates how to use serial communication on a Raspberry Pi to connect to a solar charge controller and transmit the data using a python web server REST API to web enabled devices.
This tutorial demonstrates how to measure DC power consumption with a Raspberry Pi and an INA219 breakout board. The I2C board is combined with a 16×2 LCD display to track voltage, amps and watts.
This tutorial demonstrates how to control and measure the speed of a brushless DC motor from the Raspberry Pi using a low cost electronic speed controller. A TCRT5000 reflection sensor is used to measure RPM, the results are displayed on an I2C 7 segment numeric LED display and a push wheel switch allows user input for throttle control.
Tutorial demonstrating how to connect analog sensors to the Raspberry Pi using SPI and I2C analog-to-digital converter chips such as the MCP3002 and the ADS1115. Examples include low cost analog water level/detection and water pressure sensors.
Tutorial demonstrating how to build a Raspberry Pi audio spectrum analyzer using a bi-color LED matrix and a Holtek HT16K33 I2C LED controller driver. A 4 channel I2C-safe bi-directional logic level converter is used to handle communication between the 3.3V Pi and the 5V HT16K33.
This tutorial demonstrates how to send and receive emails using the SendGrid API from within Python and Node.js applications running on the Raspberry Pi. In addition webhooks will be used to monitor and respond to incoming emails.