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Parameter Study on the Use of Artificial Intelligence to Optimize Response to Unattended Bags to Increase Airport Security

Milbredt, Olaf and Popa, Andrei and Draeger, Christina (2023) Parameter Study on the Use of Artificial Intelligence to Optimize Response to Unattended Bags to Increase Airport Security. In: Communications in Computer and Information Science, 1911, pp. 405-414. Springer. 22nd Asia Simulation Conference, 2023-10-25 - 2023-10-26, Langkawi Island, Malaysia. doi: 10.1007/978-981-99-7240-1_32. ISBN 978-303032422-3. ISSN 1865-0929.

Full text not available from this repository.

Abstract

As a vulnerable transportation hub, the airport can become the target of an attack at any time. Airport security, therefore, touches a fundamental aspect of our society: moving without fear. The attackers' methods become increasingly sophisticated. It is therefore essential to react quickly and adequately through unforeseen events. Every piece of unattended baggage --- a commonly occurring incident --- potentially poses a threat. The digitalization of airports has been advanced over the last decade. This circumstance opens the possibility to a broader use of Artificial Intelligence. AI is already being successfully used in individual areas of an airport. These range from intelligent video surveillance through border control to monitoring high-security areas. In this work, an exemplary environment was examined depicting the actions necessary to neutralize an unattended piece of baggage (\eg a suitcase). The AI method Reinforcement Learning, especially the Deep Q-Network method, was used to train an agent to solve the challenge of choosing an optimal sequence of actions. This special method gives rise to a set of parameters, namely learning rate, batch size and the number of iterations. By means of a parameter study, a set of parameters was searched for enabling the agent to adequately solve the challenge.

Item URL in elib:https://elib.dlr.de/198562/
Document Type:Conference or Workshop Item (Speech)
Title:Parameter Study on the Use of Artificial Intelligence to Optimize Response to Unattended Bags to Increase Airport Security
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Milbredt, OlafUNSPECIFIEDhttps://orcid.org/0000-0001-7388-7026UNSPECIFIED
Popa, AndreiUNSPECIFIEDhttps://orcid.org/0000-0003-0085-2054UNSPECIFIED
Draeger, ChristinaDLRUNSPECIFIEDUNSPECIFIED
Date:October 2023
Journal or Publication Title:Communications in Computer and Information Science
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:No
Volume:1911
DOI:10.1007/978-981-99-7240-1_32
Page Range:pp. 405-414
Editors:
EditorsEmailEditor's ORCID iDORCID Put Code
Hassan, FazilahUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Sunar, NoorhazirahUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Publisher:Springer
Series Name:Methods and Applications for Modeling and Simulation of Complex Systems
ISSN:1865-0929
ISBN:978-303032422-3
Status:Published
Keywords:Airport Security, Artificial Intelligence, Reinforcement Learning
Event Title:22nd Asia Simulation Conference
Event Location:Langkawi Island, Malaysia
Event Type:international Conference
Event Start Date:25 October 2023
Event End Date:26 October 2023
Organizer:Malaysian Simulation Society
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Air Transportation and Impact
DLR - Research area:Aeronautics
DLR - Program:L AI - Air Transportation and Impact
DLR - Research theme (Project):L - Air Transport Operations and Impact Assessment
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems > Information Gathering and Modelling, BS
Institute of Transportation Systems > Design and Evaluation of Mobility Solutions, BS
Deposited By: Milbredt, Dr. Olaf
Deposited On:10 Nov 2023 13:38
Last Modified:24 Apr 2024 20:59

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