GymTracker

The Gym Tracker is the first publicly available project of the Aachen Data Science Club (ADSC), designed to predict the capacity of the RWTH Gym using machine learning models.

We developed a system that leverages an OCR model to read the current gym capacity, extracting real-time data and storing it in our database. By analyzing historical capacity data, we trained a machine learning model that integrates various factors to generate accurate predictions for each day of the week. Our analysis considers several key factors, including historical gym capacity patterns from previous weeks and months, weather conditions in Aachen, national and regional holidays that impact gym usage and academic calendar events (such as exam periods and semester breaks). Our model aims to provide reliable forecasts, helping gym-goers plan their visits more effectively and manage their workout schedules better. This project not only enhances the user experience at the RWTH Gym but also showcases the potential of data science and machine learning in solving real-world problems.