2025: Crisis Management Days Conference Proceedings
Security and protection (national security, corporate and information security, disaster risk reduction)

A compact, AI-powered System for Rapid Decontamination During CBRNE Incidents

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  • Manousos Logiakis,
  • Prodromos Boutis,
  • Iliana Vasilopoulou,
  • Katerina Valouma,
  • Anastasios Dimou,
  • Spyridon Kintzios,
  • Eleftherios Ouzounoglou,
  • Stefanos Vrochidis
Manousos Logiakis
VANOS S.A.
Prodromos Boutis
Centre for Research and Technology Hellas (CERTH)
Iliana Vasilopoulou
VANOS S.A.
Katerina Valouma
Institute of Communications and Computer Systems (ICCS)
Anastasios Dimou
Centre for Research and Technology Hellas (CERTH)
Spyridon Kintzios
Centre for Research and Technology Hellas (CERTH)
Eleftherios Ouzounoglou
Institute of Communications and Computer Systems (ICCS)
Stefanos Vrochidis
Centre for Research and Technology Hellas (CERTH)

Published 2025-11-16

Keywords

  • Mass Decontamination,
  • Body pose estimation,
  • CBRNE incident,
  • Emergency Response,
  • Crisis Management

How to Cite

Logiakis, M., Boutis, P., Vasilopoulou, I., Valouma, K., Dimou, A., Kintzios, S., … Vrochidis, S. (2025). A compact, AI-powered System for Rapid Decontamination During CBRNE Incidents. Crisis Management Days. Retrieved from https://ojs.vvg.hr/index.php/DKU/article/view/750

Copyright (c) 2025 Manousos Logiakis, Prodromos Boutis, Iliana Vasilopoulou, Katerina Valouma, Anastasios Dimou, Spyridon Kintzios, Eleftherios Ouzounoglou, Stefanos Vrochidis

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Abstract

Effective decontamination is critical in emergency response, yet traditional systems require extensive infrastructure, specialized personnel and significant logistical support, limiting their practicality in urgent scenarios. This Work-in-Progress (WiP) paper presents: i) the Fast Deployable Mass Decontamination system (FDMD), a novel decontamination tunnel designed for rapid deployment, operational flexibility and ease of use in various emergency response environments, and ii) the DECON Body Pose Estimation Tool (DBPET), a camera-based AI-driven image-analysis system that tracks body posture in real-time, integrated with the FDMD to ensure optimal decontamination coverage. Utilizing integrated speakers, the DBPET provides automated, step-by-step instructions to guide individuals and minimize body posture error based on international standards. Additionally, its multilingual support enhances accessibility, enabling clear communication in high-stress environments. FDMD incorporates three interchangeable sets of sprinklers, supporting both wet and dry decontamination methods based on the nature of the contamination. The system features a lightweight, modular structure that enables quick assembly with minimal training requirements, while minimizing its storage in a large suitcase. This paper examines the decontamination process and systems and outlines the FDMD’s and DBPET’s design, key technological components, initial experimental validation efforts and expected impact and benefits. Preliminary assessments focus on deployment speed, body posture efficiency and operational scalability. Future work will expand on performance testing, field trials and integration with other technological tools under development (e.g. Digital Triage Tag) and within emergency response frameworks. By addressing current decontamination challenges, FDMD integrated with the DBPET aim to provide an efficient, cost-effective, rapidly deployable and adaptable solution for first responders (FRs), experts and non-experts managing CBRNE incidents.

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