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Unmanned aerial vehicle-based hazardous materials response: Information-theoretic hazardous source search and reconstruction

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journal contribution
posted on 17.09.2020, 08:42 by Michael Hutchinson, Cunjia Liu, Paul Thomas, Wen-Hua Chen
Hazardous materials (HAZMAT) released into the atmosphere pose both an immediate and chronic risk to human health. Characteristic examples include the Sarin gas terrorist attacks in Japan (1995), the infamous chemical accidents of Bhopal, India (1984) and Seveso, Italy (1976), such nuclear disasters as Fukushima (2012), and the recent use of chemical weapons and nerve agents in Syria (2013-2018). A prompt and accurate prediction of the whereabouts of the HAZMAT and a forecast of its dispersion and deposition are important to enable responders to undertake appropriate mitigation strategies and extract people from affected regions. Hazard predictions, however, require accurate knowledge of the release parameters (the so-called source term), as well as the local meteorological information. In many situations, this information is unknown or highly uncertain. HAZMAT sensor readings will indicate the presence of HAZMAT, and this must be turned rapidly into a warning to ensure the safety of personnel in the vicinity. This currently requires either a static network of pre-deployed sensors, which can be costly and necessitates substantial planning, or the manual collection of sensor measurements, e.g., using handheld devices and HAZMAT suits, which can be time-consuming and places personnel at risk.

Funding

UK Ministry of Defence and the UK Home Office via the Defence and Security Accelerator under project number ACC500113

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

IEEE Robotics and Automation magazine

Volume

27

Issue

3

Pages

108 - 119

Publisher

Institute of Electrical and Electronics Engineers

Version

AM (Accepted Manuscript)

Publisher statement

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Acceptance date

17/09/2019

Publication date

2019-11-12

Copyright date

2020

ISSN

1070-9932

eISSN

1558-223X

Language

en

Depositor

Dr Cunjia Liu

Exports