Check Laundry 🤔 🧺

A simple service so I don't have to walk down 2 flights of stairs to see if the washing machines are available.

https://checklaundry.com

Device

Hardware

Sensors -> Raspberry Pi Zero W -> Sixfab 3G-4G/LTE Base Hat -> Tellit ME910C1-WW modem -> Twilio Super SIM -> Backend API

Software

Basic Python script that uses the sounddevice library to process audio input, compute loudness, and periodically update the backend with data.

Setup

You'll need to set up your Pi to work with your LTE modem. Here are some resources:

• Twilio

Copy the source code in the device folder into /opt/check-laundry on the Pi or somewhere else sensible:

export PI_IP=<the IP of your PI> # Connect via ethernet or WiFi, then you can use nmap and/or arp-scan to find the IP
cd device
rsync -r --exclude=.git --exclude=.venv --exclude=__pycache__ --exclude=.DS_Store ./ pi@$PI_IP:/opt/check-laundry

Setup:

# Add necessary system packages
sudo DEBIAN_FRONTEND=noninteractive apt-get -y install \
  python3-venv \
  libportaudio0 libportaudio2 libportaudiocpp0 portaudio19-dev \
  libatlas-base-dev

# Set up virtual environment
python3 -m venv .venv

# Install Python packages
. .venv/bin/activate
pip install -r requirements.txt

Next, you'll want to set up the Pi so that the process runs at startup. Also, we need to make sure the LTE modem gets set up on startup. Add this to /etc/rc.local, right before the exit 0 line:

# Start check-laundry process:
bash -c 'sleep 30 && cd /opt/check-laundry && ./run.sh' 2>&1 | tee /home/pi/laundry.log &

Lastly, you'll need to add an .env file for config. Add this to an .env file in the same directory as run.sh:

API_KEY=<your API key here>
API_URL=https://<your domain>/stationData
STATION_ID=<the laundry station ID, your choice>

Then, you can reboot the Pi to start the script:

sudo reboot

Backend

Pulumi API (AWS API Gateway + AWS Lambda) -> Pulumi Bucket (AWS S3)

We're using S3 for storage instead of a database since it's so cheap & our needs are minimal.

Frontend

Preact frontend, hosted on S3 and served w/ the same API used for the backend.

Cost

The Pi will report the status whenever the state of a unit changes.

• This request + response is around 10 KB of data (mostly TCP handshake & headers)
• Assume each washer is used twice each day (so, 2 on events and 2 off events)
• In addition, we'll want to add a ping to tell the backend that the Pi is still running even if no state changes. We can do that every 2 hrs. (so, 12 events)
• 16 events * 10KB * 30 days -> 4800KB -> 4.8 MB -> $0.50 per month on Twilio (Super SIM).

The backend will store the data and determine the state.

• 43,200 lambda invocations = ~$0.25 per month.

We can use S3 as database.

• storage & transfer costs = ~ $0.05 per month.

Twilio Super SIM charges $2/month per active SIM.

Total cost: ~$3 per month

🎉 🎉 🎉