The researcher aims at developing a system that assists crowd managers' decision making process regarding how best to manage the crowd during mass event. There are situations where these managers cannot rely on (previous) information featuring the crowd's behaviour and where they have to make decisions on the spot. Taking into account that crowd managers normally work with a response time of 15 minutes, this would mean that any decision on how to act and the resulting deployment of crowd management measures would comes too late.

The researcher gathers data with using automatic counting systems, smartphone applications, Wi-Fi sniffers and social media outlets. This data is combined into one dashboard by means of which different aspects of the crowd can be monitored. The innovative aspect of this dashboard is it can process data with semantically distinct features into a comprehensive analysis of the crowds state, including features such as the number of people, the level of crowdedness, the crowd's movement speed and the crowd's mood. The monitoring dashboard can recognise the state-of-affairs of the crowd in real time. The information regarding the current unfolding of events that is displayed in the dashboard supports and objectifies the crowd managers decision making process.