## 3 Related Works
### Crowd Monitoring
Finally, using the microscopic modeling approach is possible to achieve very detailed simulation. An example is the simulator ESCAPES (Evacuation Simulation with Children, Authorities, Parents, Emotions, and Social comparison) [18]. ESCAPES was developed to simulate evacuation scenarios within buildings combining multi-agent approach (_i.e._, individuals, families and authorities) while considering several psychological phenomena (e.g., fear, knowledge/certitude about occurred events, _etc._). This allowed the simulation of complicated behaviors, such as: families tend to gather all family members before looking for an exit; authority agents do not exit until all the other people (families and individuals) left. They also considered that only a part of the people involved (typically, the authority agents) might be immediately aware of the danger and hold all the knowledge about the surroundings. The others may learn (and forget) facts about the environment. Finally, as knowledge, also other feelings like fear may be transmitted among people. Due to the complex nature of the model, the ESCAPES simulator allowed only a limited number of agents. To summarize, among the several systems, a multi-agent system (microscopic approach) would probably provide the most realistic approach for crowd simulation. The more macroscopic approaches (e.g., based on fluid-dynamics paradigm) do not consider the different nuances of which a crowd of different people is composed. However, they allow the detection of potential bottlenecks or other architectural barriers and they may be usable to simulate events with a much larger number of participants with a lower computational cost. Therefore, the choice of the simulation approach should be considered depending on the aimed goal. In this work, we used the Julich Pedestrian Simulator (JuPedSim) [19] an open framework for simulating and analyzing pedestrians' motion at a microscopic level. It allows the modeling of events (e.g., doors that open or close), the transmission of knowledge among the agents, and the measurement of the simulation in terms of density, velocity, _etc._ In terms, of adopted model, JuPedSim makes available two options: the Generalized Centrifugal Force Model (GCFM) and the Gompertz model. GCFM is a spatially continuous force-based model to simulate pedestrian dynamics, which includes an elliptical volume exclusion of pedestrians [20]. The Gompertz model is based on a continuous physical force and it may simulate social as well as physical forces in a continuous way [19]. The second approach is much more expensive in terms of processing requirements. We extended the JuPedSim simulator to integrate a module to easily provide the topography of an event to the simulator and to calculate other parameters from the simulation able to indicate dangerous situations. In particular, we looked for the estimation of the crowd pressure, as defined by [PERSON] _et al._[10]. Crowd pressure depends in local density and local speed and it takes into account the main differences among fluid dynamics and human behavior. For instance, people instead of filling all the available area tends to overcrowd some areas while leaving empty others areas. Crowd pressure is an aspect to consider also when dealing with real-time crowd monitoring. SmartCrowd aimed to automatically detect dangerous situation (e.g., too high crowd pressure) as well as recognize groups within a crowd. Real-time crowd monitoring is usually performed using vision-based techniques. In fact, cameras provide a reliable and constant flow of video that may be analyzed by security agents or by computer-vision approaches that can assist security agents. Vision-based monitoring has several advantages such the independence (_i.e._, it does not rely on the collaboration of the crowd) and the real-time feedback.