Real-Time Detection and Mapping of Crowd Panic Emergencies

Ilias Lazarou, Anastasios Kesidis, Andreas Tsatsaris

2024

Abstract

We present a real-time system that uses machine learning and georeferenced biometric data from wearables and smartphones to detect and map crowd panic emergencies. Our system predicts stress levels, tracks stressed individuals, and introduces the CLOT parameter for better noise filtering and response speed. We also introduce the DEI metric to assess panic severity. The system creates dynamic areas showing the evolving panic situation in real-time. By integrating CLOT and DEI, emergency responders gain insights into crowd behaviour, enabling more effective responses to panic-induced crowd movements. This system enhances public safety by swiftly detecting, mapping, and assessing crowd panic emergencies.

Paper Citation

in Harvard Style

Lazarou I., Kesidis A. and Tsatsaris A. (2024). Real-Time Detection and Mapping of Crowd Panic Emergencies. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP; ISBN 978-989-758-679-8, SciTePress, pages 485-491. DOI: 10.5220/0012372200003660

in Bibtex Style

@conference{visapp24,
author={Ilias Lazarou and Anastasios Kesidis and Andreas Tsatsaris},
title={Real-Time Detection and Mapping of Crowd Panic Emergencies},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP},
year={2024},
pages={485-491},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012372200003660},
isbn={978-989-758-679-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP
TI - Real-Time Detection and Mapping of Crowd Panic Emergencies
SN - 978-989-758-679-8
AU - Lazarou I.
AU - Kesidis A.
AU - Tsatsaris A.
PY - 2024
SP - 485
EP - 491
DO - 10.5220/0012372200003660
PB - SciTePress