Home > Learning Hub > Learning Module #1

Learning Module—Crowd Management During Events

Discover how AI and data can improve crowd management during large events in this video-based learning module. Based on the AiMTT use case on crowd management, the series takes you step by step through the complete process, covering topics such as data sharing, crowd simulation, forecasting, monitoring and evaluation.

This learning module consists of 19 videos, organised into four chapters. Use the links in the table below to watch individual videos. Videos without a link will be added soon.

#TitlePresenter
1.1Introduction: SAIL AmsterdamRoland Geraerts, uCrowds
1.2Introduction: Crowd ManagementWinnie Daamen, TU Delft
1.3Introduction: Data SharingKevin Otjes, Analyze
1.4Introduction: ScenariosRoland Geraerts, uCrowds
2.1Working With StakeholdersKevin Otjes, Analyze
2.2Level-of-Service ConceptWinnie Daamen, TU Delft
2.3VisualisationKevin Otjes, Analyze
2.4Data Architecture for Data SharingKevin Otjes, Analyze
2.5.1Crowd SimulationRoland Geraerts, uCrowds
2.5.2Crowd Simulation: TheoryRoland Geraerts, uCrowds
2.5.3Crowd Simulation: Working With…Roland Geraerts, uCrowds
2.5.4Crowd Simulation: Using LLMsRoland Geraerts ,uCrowds
3.1MonitoringWinnie Daamen, TU Delft
3.2AlertingKevin Otjes, Analyze
3.3.1Crowd ForecastingTheivaprakasham Hari, TU Delft
3.3.2Time Series Forecasting: IntroductionTheivaprakasham Hari, TU Delft
3.3.3Time Series Forecasting: AdvancedTheivaprakasham Hari, TU Delft
3.4Evaluation During the EventKevin Otjes, Analyze
4Evaluation of Crowd ManagementWinnie Daamen, TU Delft