Campus Laundry Monitor
A problem in the dorm buildings was that many students needed to walk down two or three flights of stairs only to find the washing machines were occupied. This problem was solved by this device I designed. It features an accelerometer and an ESP32 to measure vibrations, run a classification model, and then send statuses to an external database that can be viewed on a website.
Wesleyan Laundry Monitor Block Diagram
This is a general block diagram of the IoT system. There is one node per washer or dryer, and the total network monitors the status of many machines.
For the database, a Firebase real-time database was implemented along with a simple HTML, CSS, and JavaScript front-end.
The supervised learning model was done in Python along with the Pandas, Matplotlib, and scikit-learn libraries.
Top Skills Used
PCB Layout and Routing (w/ KiCAD)
Machine Learning
Hardware Debugging w/ Oscilloscope
