RAMpaper_V2.pdf (10.92 MB)
Unmanned aerial vehicle-based hazardous materials response: Information-theoretic hazardous source search and reconstruction
Version 2 2020-09-17, 08:42
Version 1 2019-11-27, 09:10
journal contribution
posted on 2020-09-17, 08:42 authored by Michael Hutchinson, Cunjia LiuCunjia Liu, Paul Thomas, Wen-Hua ChenWen-Hua ChenHazardous 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 magazineVolume
27Issue
3Pages
108 - 119Publisher
Institute of Electrical and Electronics EngineersVersion
- 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
2019-09-17Publication date
2019-11-12Copyright date
2020ISSN
1070-9932eISSN
1558-223XPublisher version
Language
- en