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- W2562679285 abstract "Technical advancements allow for the development of crowd monitoring and management support systems to ensure the safety of pedestrians during large-scale events. This way, pedestrian behaviour can be monitored during events, and potential dangerous situations can be identified in a timely manner. A real-time prototype Crowd Monitoring Dashboard has been developed for a large nautical event in Amsterdam in 2015. Three main functions of such a system have been identified: the real-time data collection, the traffic engineering functions and the visualization. This paper focuses on three state estimation algorithms in the second component - the traffic engineering functions. These algorithms are presented and cross compared in terms of performance, data usage and practical applications, based on the empirical data collected from this large-scale event. The outcome can shed useful light on the feasibility of the data sources and estimation methods for future real-time applications on crowd monitoring and management for large-scale events." @default.
- W2562679285 created "2017-01-06" @default.
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- W2562679285 date "2016-11-01" @default.
- W2562679285 modified "2023-09-29" @default.
- W2562679285 title "Comparison of three algorithms for real-time pedestrian state estimation - supporting a monitoring dashboard for large-scale events" @default.
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- W2562679285 doi "https://doi.org/10.1109/itsc.2016.7795974" @default.
- W2562679285 hasPublicationYear "2016" @default.
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