Similarly to the Marauder's Map in Harry Potter, we tracked employees and students on campus. We model this output in terms of choice of activity type in time. By discretizing time, this choice is represented as a path in a network. The choice set is generated using a Metropolis-Hasting algorithm based on attractivity measures, and the utility function describes satiation effects and time-of-day preferences. Such a methodology is useful to build an activity-based model for pedestrian infrastructure, estimate the demand and its drivers, and forecast it for different scenarios.