"Someone ought to open up a window!"
A thermostat for your windows--get a sense of when to open your windows for fresh air with WindowSense. Set your thermostat for comfort and save money on heating and cooling by letting in the breeze at the best times.
WindowSense integrates the temperature forecast with your Nest thermostat comfort settings to visualize when the outside air will be just right to throw open the windows for fresh air that won't make your home too hot or cold.
The RGB LED matrix display uses a rainbow of colors to signal how the temperature will change over the next eight hours, so you can plan ahead and maximize your home's comfort and efficiency.
WindowSense uses a stylized graph in a rainbow of colors to show when it will be cold, warm, or comfortable outside in the coming hours. The 8x8 RGB LED matrix represents each hour's forecasts, with now, on the left, and then the next seven hours, from left to right.
Your thermostat's comfort range, as defined by the heating and cooling setpoint, is represented by the middle two rows in green. Outside temps closer to the top of your comfort range place the green square higher; cooler temps closer to the bottom of your comfort range place it lower.
Each row of the graph represents steps of equal size, to give a relative impression of how much colder or hotter it is outside than you would want it to be in your home. If your comfort range is heat to 65F / cool to 75F, for example, then each block is 5 degrees F. Additionally, if the forecast will be below freezing, the bottom row will turn white to indicate the possibility of snow & ice.
With this information available at a glance, it is easy to know when you can open your windows to be comfortable and efficient. You can also plan for your day, see the ebb and flow of daily temperatures, and prepare your home or garden if temperatures will drop below freezing.
- Reading the Nest thermostat's heat & cool setpoints via Google's smart device access API
- Getting the weather forecast from OpenWeatherMap's API using the pyowm library
- Dynamically calculating and drawing a graph that relates the outside temps to your personal comfort settings
- Interactive button commands, including:
- Ambient temp & humidity readout from the Nest
- Thermostat heat & cool setpoint readouts
- LED brightness adjustment
- Manual forecast & graph refresh
- A safe shutdown process
Additionally, temperature forecast data is written to a .csv file for future data analysis, and the Nest thermostat traits are written to a JSON file to allow investigation of deeper integration opportunities.
There's something special about air that's just the right temperature such that you can't feel it at all. Last fall, when the days were still warm and the nights getting cold, my wife and I were trying to open the windows as much as possible for fresh air. However, as the resident steward of the thermostat, I also wanted to make sure we were not letting in hot late-afternoon air that would kick on our air conditioning or leaving the windows open too long and allowing the house to get too cold from the chilly, nighttime air. Depending on the day, there was sometimes just a narrow window of opportunity to let in fresh air that would feel just right and not waste energy. So the idea was born to create a smart device to tell us when it would be comfortable--and efficient-- to throw open the windows for a cross-breeze.
This repository includes the Python script which runs WindowSense, as well as some additional resources, including:
- Raspberry Pi OS Setup: Guidance for how to set up a fresh Raspberry Pi
- Software Installation: Instructions on how to set up the software and get the script running
- Hardware Assembly: Information on the hardware and 3D-printed case
- Learning Resources: Supplemental learning resources for those interested in learning more about the technologies used to create WindowSense
I want to extend many thanks to the Raspberry Pi Foundation and the countless makers and teachers who comprise the incredible educational and open-source maker community that inspired and helped me to create this project.
This project was created as a self-directed educational experience and is in no way associated with Google, Nest, OpenWeatherMap, the Raspberry Pi Foundation, or any other company mentioned in this repository.