MicroPython ESP32-S3 Projects and Environment Sensing This repository contains guides, basic scripts, and machine learning models for working with the ESP32-S3 microcontroller using MicroPython. It covers basic hardware interactions (NeoPixels, buttons, DHT11 sensors) and extends into environmental data prediction.
Repository Contents Based on the file list in image_869f9c.png, this project contains the following files:
BASIC LED.py: Simple script to control the onboard NeoPixel LED.
DHT Sensor Read and write.py: Script to read temperature and humidity data from a DHT11 sensor.
MicroPython Installation Guide in Thonyl... (PDF): A step-by-step PDF guide for setting up the ESP32 with Thonny.
PREDICTION WITH DHT SENSOR.py: Python script for making local predictions based on sensor data.
PREDICTION WITH DHT SENSOR+WEB.py: Python script integrating sensor predictions with a web interface.
environment_dataset_50k.csv: A 50,000-record dataset used for training the environmental prediction model.
DHT_train_model.ipynb: A Jupyter Notebook used to train the machine learning model on the CSV dataset.
Hardware Requirements ESP32-S3 Development Board (e.g., S3-DevKitC-1 N16R8)
DHT11 Temperature and Humidity Sensor
Push Button
Micro-USB or USB-C cable (data capable)
Setup Instructions Step 1: Install Thonny IDE Download and install the Thonny IDE from the official website.
Follow the standard installation prompts for your operating system.
Step 2: Download MicroPython Firmware Go to micropython.org/download.
Locate the firmware for the ESP32-S3.
Download the appropriate .bin file (e.g., ESP32_GENERIC_S3-SPIRAM_OCT-...bin).
Step 3: Flash Firmware to the ESP32 Open Thonny IDE.
Go to Run > Configure interpreter (or click the bottom-right corner).
Select MicroPython (ESP32).
Click on Install or update MicroPython (esptool).
Select your Target Port (e.g., COM7 or COM9).
Select the MicroPython family (ESP32-S3) and browse for the .bin file you downloaded.
Check Erase all flash before installing and click Install.