Crowd monitoring refers to the sensing and analysis of multiple people simultaneously within a shared environment, encompassing tasks such as crowd counting, density estimation, pedestrian flow tracking, and group behavior recognition using wireless signals like WiFi CSI or RSSI. It matters for the field because it extends human sensing beyond individual-level detection to population-scale situational awareness, enabling critical applications in public safety, transportation management, and smart infrastructure. Key variants include static crowd density estimation, dynamic crowd flow analysis, and agent-based simulation approaches that integrate data assimilation techniques to model and predict collective pedestrian movement in complex environments.
Source Papers
- A survey of recent advances in CNN-based single image crowd counting and density estimation ↗ — A survey of recent advances in CNN-based single image crowd
- Data collection methods for studying pedestrian behaviour: A systematic review ↗ — Data collection methods for studying pedestrian behaviour: A
- Recent trends in crowd analysis: A review ↗ — Recent trends in crowd analysis: A review