Mirror Frame

 The mirror's frame was constructed with a 2x4 beam cut to length to enclose the monitor. White trim was placed around the outside for added decoration and further securement. Our monitor was mounted inside using another small 2x4 to keep it suspended at eye level. The Raspberry Pi was installed using its own built-in mounting holes, and attached to the interior. Finally, one-way acrylic was placed in front of the monitor, and all wood was drilled together.

The ultrasound proximity sensor was connected to our Raspberry Pi with a solderable breadboard and several resistors. We then utilized OpenCV4 and generated a virtual environment to run Python for coding purposes. When movement is detected, the camera scans for a face. If a face is recognized, the Magic Mirror facial recognition function would prompt a custom greeting message. Lastly, the monitor and Raspberry Pi were connected by HDMI, and each required a standard 120-V AC outlet for power. Click below to see the image enlarged.

This application allowed us to program the  information we wished to present onto our monitor. The app is downloadable, and is compatible with OpenCV4. Using six modules, we displayed messages, weather, time, date, weekly forecast, and even local bus routes. However, the facial recognition module was only compatible with OpenCV3 and Python 2. Thus, its functions on the mirror were severely limited. Click below to see the image enlarged.

The poster my team created to present at the Fall 2018 CU A&S Design Expo. It demonstrates our project overview, requirements, coding procedures, manufacturing processes, and lessons learned. Click below see the poster enlarged.

As a result of our ingenuity, consistent efforts, and synergy as a team, we were awarded the 2nd Place, People's Choice Award at the expo. We are honored to receive this award, and thank the CU College of Arts and Sciences for recognizing the hard work that went into this project.