Carnegie Mellon ECE Capstone, Spring 2022
Sophie Sacks, Sam Lavelle, Dina Razek
Students on campus have a very difficult time knowing how crowded and busy restaurants are in real time. Especially during COVID, students may be concerned about how crowded an indoor area is. By having scanners to measure how many people are in line, users can check an application to see the estimated wait time. Our project will consist of two RFID scanners programmed to identify when a person enters and leaves the line and approximate the waiting time to order using a machine learning model. This includes the physical hardware as well as the software program behind it. This program will be updated in real time with the most recent data sent over the Internet to the web application.