Privacy-preserving and IoT-capable Crowd Analysis and Detection of Flow Disturbances for Enhancing Public Safety

Hans G. Ziegler

Abstract

This paper describes a solution for monitoring and detection of crowds and analysis of density structures and movement characteristics, to enhance safety of citizens and security of critical infrastructures. The system leverages the Internet of Things concept and heterogenous, energy efficient, networked sensors, with support for wireless communication. Privacy protection, instant deployability and auto configuration are hereby underlying core objectives. The solution, which will be described, comprises two novel distributed crowd analysis algorithms, allowing on the one hand the localisation of critical areas within large crowds and on the other hand the recognition of counter streams, which can cause severe impacts on the crowd flow and movement velocity and which can transform crowding scenarios into threatening situations.

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Paper Citation


in Harvard Style

Ziegler H. (2016). Privacy-preserving and IoT-capable Crowd Analysis and Detection of Flow Disturbances for Enhancing Public Safety . In Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-184-7, pages 55-62. DOI: 10.5220/0005761300550062


in Bibtex Style

@conference{smartgreens16,
author={Hans G. Ziegler},
title={Privacy-preserving and IoT-capable Crowd Analysis and Detection of Flow Disturbances for Enhancing Public Safety},
booktitle={Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2016},
pages={55-62},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005761300550062},
isbn={978-989-758-184-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Privacy-preserving and IoT-capable Crowd Analysis and Detection of Flow Disturbances for Enhancing Public Safety
SN - 978-989-758-184-7
AU - Ziegler H.
PY - 2016
SP - 55
EP - 62
DO - 10.5220/0005761300550062