Crowd Behavior Modeling: Crowd Source Modeling
Modern societies are vulnerable to a myriad of risks ranging from dangerous diseases to natural hazards to technological disruptions. During the times of emergencies where adverse situations loom large on the society, the crowds behave differently. Crowd behavior modeling or CBM is the practice of stimulating and predicting pedestrian movements within a specified space, using specialist modeling software. Crowds are a very common feature of large cities, not only at mass gatherings but also at regular events like the journey to work.
To address extreme crowding, various computer models for monitoring crowd movement have also been developed in the past decades. It helps to understand, analyze, and estimate how the behavior of the crowds can be molded towards creating informed awareness that can lead to the prevention of disease spreads in the mass levels. Crowd source modeling also plays an indispensable role here as it provides real-time information from participants who answer questions related to a specific topic. They provide current data such as reported cases in a particular area, the facilities to look for, the rates of casualties, and so on.
The ongoing global pandemic COVID19 is one such example where searching for information on infectious disease modeling, on how the disease spreads, what are the risks and how it triggers a diffusion of coping strategies among the masses is of vital importance. It also requires an in-depth understanding of how individuals at a crowd level perceive risks and communicate about the efficacy of protective measures, focusing on learning and distanced social interaction. These are the ways that can be considered as the core mechanisms driving wisdom of the crowds to prevent the spread of this disease. In the current crisis, where it becomes next to impossible to gather data on the spread of this pandemic physically, CBMs prove to be very beneficial.