Researchers from France and Spain have developed a theoretical model to forecast the movements of confined, densely packed crowds. The study, published in Nature, analyzed high-resolution video footage of the Chupinazo opening ceremony of the San Fermín Festival in Pamplona, Spain, and revealed a change in behavior akin to a phase change when the crowd density passed a critical threshold. The model could help predict potentially life-threatening crowd behavior in confined environments and potentially form the basis for a crowd management protocol.
Forecast for 6 months: Within the next 6 months, we expect to see increased adoption of crowd management protocols in high-risk events, such as music festivals and sporting events, as event organizers and authorities become aware of the potential benefits of using crowd modeling to prevent crushing incidents.
Forecast for 1 year: Within the next year, we anticipate the development of more advanced crowd modeling tools and technologies, including the integration of machine learning algorithms and real-time data analytics, which will enable more accurate predictions and more effective crowd management strategies.
Forecast for 5 years: Within the next 5 years, we expect to see widespread adoption of crowd modeling in various industries, including entertainment, sports, and transportation, leading to significant reductions in crowd-related incidents and improved public safety.
Forecast for 10 years: Within the next 10 years, we anticipate the development of even more sophisticated crowd modeling technologies, including the use of artificial intelligence and the Internet of Things (IoT), which will enable real-time monitoring and prediction of crowd behavior, leading to even greater improvements in public safety and reduced risk of crowd-related incidents.
