An Integrated Fusion Engine for Early Threat Detection Demonstrated in Public-Space Trials

Henri Bouma (Corresponding Author), Maria Luisa Villani, Arthur van Rooijen, Pauli Räsänen, Johannes Peltola, Sirra Toivonen, Antonio De Nicola, Massimiliano Guarneri, Cristiano Stifini, Luigi De Dominicis

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Counter terrorism is a huge challenge for public spaces. Therefore, it is essential to support early detection of threats, such as weapons or explosives. An integrated fusion engine was developed for the management of a plurality of sensors to detect threats without disrupting the flow of commuters. The system improves security of soft targets (such as airports, undergrounds and railway stations) by providing security operators with real-time information of the threat combined with image and position data of each person passing the monitored area. This paper describes the results of the fusion engine in a public-space trial in a metro station in Rome. The system consists of 2D-video tracking, person re-identification, 3D-video tracking, and command and control (C&C) formulating two co-existing data pipelines: one for visualization on smart glasses and another for hand-over to another sensor. Over multiple days, 586 commuters participated in the trial. The results of the trial show overall accuracy scores of 97.4% and 97.6% for the visualization and hand-over pipelines, respectively, and each component reached high accuracy values (2D Video = 98.0%, Re-identification = 100.0%, 3D Video = 99.7% and C&C = 99.5%).

Original languageEnglish
Article number440
JournalSensors
Volume23
Issue number1
DOIs
Publication statusPublished - 31 Dec 2022
MoE publication typeA1 Journal article-refereed

Keywords

  • counter terrorism
  • forensics
  • re-identification
  • surveillance
  • threat detection
  • Explosive Agents
  • Terrorism
  • Humans

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