WLED on an ESP32-S3
Go to https://wled-install.github.io/ and just select the correct ESP32 board and flavour of WLED you want. I just tried the Audio reactive User mod on my ESP32-S3 4MB
Go to https://wled-install.github.io/ and just select the correct ESP32 board and flavour of WLED you want. I just tried the Audio reactive User mod on my ESP32-S3 4MB
Found the YouTube video How To Reverse Engineer A Bluetooth Device and started to follow it but it did not really work as expected so record all differences here.
\FS\data\misc\bluetooth\logs but rather in \FS\data\log\bt.sudo rfkill unblock all<br />sudo hciconfig hci0 upsudo hcitool lescan | grep "C7:57"I found https://github.com/koosoli/ESPHomeDesigner before Christmas and it seemed to be a really nice tool so decided to try it out. And soon I was contributing some. Here is some notes from that.
cd /tmp
git clone https://github.com/koosoli/ESPHomeDesigner.git
cd ESPHomeDesigner
git switch testing
git pull
cp -r custom_components/esphome_designer /homeassistant/custom_components
One of my friends told me about the Guiton capacity touch display with GT911 and an integrated ESP32. And it did not cost that much. The Guiton ESPHome config made it easy to get it working in Home Assistant

Hi-Link manufactures a number of different sensor modules with millimeter wavelength radars which are great to detect humans with.
Some time ago I read about these and they were did not cost much. I bought these from AliExpress. So I ordered some different ones. Recently I found some time to experiment with one of them, the LD2450 (The AliExpress item I bought). On the product page there is a link to a Google drive with documents and software for this module.
I had previously tried one of the others briefly but unsuccessfully. So this time I took a bit different path.
I read that several (maybe all?) of these has built in Bluetooth so I downloaded the HLKRadarTool (iOS or Android) to my phone and powered up the module and connected the phone to it. It worked directly and it was easy to evaluate how the device performed.
Once I know it worked well it was time to connect it to an ESP32. The manual made it easy to understand what pins to use on the radar module. I had some ESP32-C3 modules at home so I decided to use it. The model I had was Tenstar Robot Super Mini and the pinout made it easy to figure out how to connect RX and TX on the sensor to TX and RX on the ESP32.

I then used ESPHome device builder in Home Assistant and the information on the ESPHome LD2450 page to create and install a configuration for the sensor. And soon it appeared in Home Assistant.
After that I looked for a case and found a nice simple case that could easily be pointed in different directions but was not too bulky.

I have an ESP32-CAM unit I wanted to try to connect to Home Assistant. This is how I managed to add it.
First I Googled and found the esp32_camera component for ESPHome so it was a natural start since I already have several other ESPHome devices.
After a while I found that the esp32_camera component came with a number of configuration examples. After a little investigation among checking the https://github.com/raphaelbs/esp32-cam-ai-thinker project I realized that I should be able to use the Ai-Thinker Camera-example.
I also wanted to be able to control the LEDs on the board, both the status LED and the Flash and added those as well.
This was my final yaml configuration which I added to the rest of the ESP yaml in the ESP Builder
esp32_camera:
name: ESP32 camera
external_clock:
pin: GPIO0
frequency: 20MHz
i2c_pins:
sda: GPIO26
scl: GPIO27
data_pins: [GPIO5, GPIO18, GPIO19, GPIO21, GPIO36, GPIO39, GPIO34, GPIO35]
vsync_pin: GPIO25
href_pin: GPIO23
pixel_clock_pin: GPIO22
power_down_pin: GPIO32
resolution: 1600x1200 # Native resolutions CIF 400x296, SVGA 800x600, UXGA 1600x1200
jpeg_quality: 10
vertical_flip: false
horizontal_mirror: false
output:
- platform: gpio
id: camera_flash_led
pin: GPIO04
light:
- platform: status_led
name: "Camera status LED"
pin:
number: GPIO33
inverted: true
- platform: binary
name: "Camera Flash LED"
output: camera_flash_led
Wanted to experiment a bit with Home-Assistant while travelling. And wanted to be able to run as much as possibly locally on the laptop instead of connecting to my home setup since network connectivity is not always reliable.
So here is a short summary how I set it up.
I already had Docker Desktop setup with a free Docker Personal account. If you do not have it setup already, download and install it.
I found these two articles; Installing Docker, Home Assistant and Portainer on Ubuntu Linux and Configuring the Mosquitto MQTT Docker container for use with Home Assistant but they are dedicated to run Docker on Linux and since my laptop is a Mac I had to do some modifications.
Create a folder on your laptop. I called mine home-assistant and then a number of subfolders in it:
mkdir home-assistant
cd home-assistant
mkdir homeassistant
mkdir homeassistant/config
Then run code docker-compose.yml and add
version: '3.0'
services:
homeassistant:
container_name: homeassistant
image: "ghcr.io/home-assistant/home-assistant:stable"
volumes:
- ./homeassistant/config:/config
- /etc/localtime:/etc/localtime:ro
- /run/dbus:/run/dbus:ro
restart: unless-stopped
privileged: true
ports:
- 8123:8123
Optionally if you want to run Mosquitto for MQTT
mkdir mosquitto
mkdir mosquitto/data
mkdir mosquitto/logmkdir mosquitto/config
Then run code mosquitto/config/mosquitto.conf and add
persistence true
persistence_location /mosquitto/data/
log_dest file /mosquitto/log/mosquitto.log
listener 1883
## Authentication ##
allow_anonymous true
And add to docker-compose.yml
mosquitto:
image: eclipse-mosquitto
container_name: mosquitto
volumes:
- ./mosquitto:/mosquitto
- ./mosquitto/data:/mosquitto/data
- ./mosquitto/log:/mosquitto/log
ports:
- 1883:1883
- 9001:9001
Then start the the container or containers with docker compose like
docker-compose up -d
You now have both Home Assistant and Mosquitto running but before connecting the two you want to setup authentication in Mosquitto. This is just a simple setup with only one account.
In Docker Desktop, view your containers by clicking Containers in the left menu. Find the mosquitto one and click on its name. Then select the Exec tab and execute the following command
mosquitto_passwd -c /mosquitto/config/password_file hass
Enter the password you want twice.
Then edit the /mosquitto/config/mosquitto.config in VSCode and change the following section
## Authentication ##
allow_anonymous true
to
## Authentication ##
allow_anonymous false
password_file /mosquitto/config/password_file
Then restart the mosquitto docker to reload this config.
Then visit localhost:8123 to create account and start using Home-Assistant.
Click Setting in the left menu once you have logged in. Then click Devices & services.
Click “Add Integration” and type MQTT. Select MQTT and then click MQTT(the top alternative). You should see something like

Fill in all fields like in this example

And click Submit. Now you have added your Mosquitto instance to Home Assistant!
Some documentation of my wiring to the MakerX VESC since I am about to connect a BRemote instead of the Maytech one.

| VESC | First cable | Second | Third | Fourth | Maytech Rx | BRemote Rx V1.3 |
|---|---|---|---|---|---|---|
| PPM | ||||||
| Sig | Yellow | Orange | Yellow | Orange | PWM | SRV |
| 5V | Red | NC | ||||
| GND | Black | NC | ||||
| COMM | ||||||
| AUX | Brown | NC | ||||
| MISO_ADC_EXT2 | Orange | NC | ||||
| TX_SDA_NSS | White | Purple | Pink | Purple | RXD | TX2 |
| RX_SCL_MOSI | Blue | Grey | Grey | Grey | TXD | RX2 |
| SCK_ADC_EXT1 | Green | NC | ||||
| GND | Black | Black | Blue | Black | GND | GND |
| 3.3V | Yellow | NC | ||||
| 5V | Red | Red | Red | Red | 5V | 5V |
| Other | ||||||
| Battery + | Green | Green | Brown | Grey | BAT | BMS+ |
| Motor phase | Blue | Blue | White | White | MOT |
This article on the Snapmaker forum outlines how to do it. https://forum.snapmaker.com/t/extruder-calibration-a-must/7724/33
I use the calibration card to measure and cut the filament at 10 on the card, i.e 100mm plus the dead space before the 0. But since I measure the extruded distance also with this space it can be ignored.

Make sure the hot end has reached the correct temperature for the filament you are calibrating with. And issue the command to start feeding the 100mm of filament. Once that finished measure the amount of filament left.

I had 23mm left this time. Then it is time to do the calculation. I find it easiest to start the developer tools in the browser. In the console there I just enter the expressions in the article.

Then use the Luban console to enter the newly calculated value and permanently store it. If you want to understand the M-commands like M92 this page was good, https://snapmaker.github.io/Documentation/gcode/M092

Finally make a test run with the same command that feeds 100mm of filament. Mine fed a few mm of extra filament.

This time I ignored the difference but if you want you can re-calibrate. Use your calculated S value as the new E in the calculation and enter how much filament that has been fed. Repeat until you are satisfied.

I found the OpenMQTTGateway project and got really interested since it can open up for a lot of interesting integrations to Home Assistant. I bought a LilyGo to start experimenting and could get it to read 433Mhz devices like Nexa. All this is possible due to the RTL_433_ESP library.
I wanted also to be able to write to the devices since I have several power plugs that use Nexa. That is not possible with just the LilyGo and the radio module on it. With the STX882 it should be possible to transmit. So I bought both a STX882 and a SRX882. This page describes how to connect these to a ESP32 or NodeMCU.
Have not yet tried to make the full setup and connect everything. Will update this post once I have tried that.