Turn that light off!

Repository for the "Turn that light off!" project of Make Zurich 2023.

The idea

• Place light and motion sensors in a room.
  • Currently only the light sensor has been implemented.
• If the light sensor detects that the light is on but the motion sensor detects that nobody is in the room, then either a message is shown on a display ("Turn the light off!") or another visual message could be shown to the user, such as a red LED turning on.
• The user then hae one minute of time to turn that light off.
• If the user turns it off within the agreed time window (default to one minute), then they get a point in a yet to be defined leader board.
• Once the user get ten points, then they can buy themselves an ice cream!

Tools

• Raspberry Pi Pico W
  • The "blue" Raspberry Pi Pico W sends uplink ⬆️ messages to the TTN
  • The "purple" Raspberry Pi Pico W receives downlink ⬇️ messages from Adafruit IO
• CircuitPython
• The Things Network (TTN)
• Adafruit IO
• seedstudio Grove
• Datasette

Tasks

• [x] Set up "blue" Raspberry Pi Pico W with light sensor.
• [x] Set up "blue" Raspberry Pi Pico W to send uplink data to the TTN.
• [ ] Set up "blue" Raspberry Pi Pico W to show the intensity of the light sensor using the onboard Neopixels.
• [x] Set up "purple" Raspberry Pi Pico W with light LCD display.
• [x] Set up "purple" Raspberry Pi Pico W to connect to WiFi.
• [x] Set up "purple" Raspberry Pi Pico W to subscribe to the mz23 topic from the Adafruit IO MQTT broker.
• [x] Install Datasette
• [x] Visualize mqtt.db SQLite database with Datasette
• [x] Develop subscribe_to_ttn.py Python script to subscribed to the MQTT TTN integration.
• [x] Develop subscribe_to_ttn.py Python script to store the received data to a local SQLite database.
• [x] Develop publish_to_aio.py Python script to read data from a local SQLite database.
• [x] Develop publish_to_aio.py Python script to publish data to the Adafruit IO MQTT broker.
• [ ] Dockerize the two Python scripts above.

Instructions

Datasette

Install Datasette in your Python environment:

pip install datasette

Run Datasette against a SQLite file on your computer using the following command:

datasette mqtt.db

Then open your browser at http://127.0.0.1:8001.