Privacy-preserving and IoT-capable crowd analysis and detection of flow disturbances for enhancing public safety

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.