Optimizing event coverage in theme parks

Theme parks can be modeled as geographical areas where large crowds of people move among different attractions. The operators of a theme park are interested in quickly and efficiently handling events occurring at various locations in the park. We propose a model which deploys a wireless network with mobile sinks to facilitate event coverage. The event coverage problem can be divided into two sub-problems: the static problem of mobile sink positioning and the dynamic problem of event handling decisions of the mobile sinks. For the mobile sink positioning problem we propose two strategies: crowd density based probability estimation (CDPE) and hot-spot based probability estimation (HSPE). For the event handling decision problem, we propose an approach which represents movement opportunities in the park as a graph with dynamically changing weights, and searches for the shortest path in this dynamic graph. The proposed approaches are simulated on scenarios which model the movement of the visitors using two sophisticated human mobility models.