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Article type: Research Article
Authors: Bäßmann, Felix N.a; * | Lier, Sarah K.b | Werth, Oliverc | Krage, Astridd | Breitner, Michael H.e
Affiliations: [a] Information Systems Institute, Leibniz University Hannover, Hannover, Germany | [b] Information Systems Institute, Leibniz University Hannover, Hannover, Germany | [c] OFFIS e. V. – Institute for Information Technology, Oldenburg, Germany | [d] ATS Elektronik GmbH, Wunstorf, Germany | [e] Information Systems Institute, Leibniz University Hannover, Hannover, Germany
Correspondence: [*] Corresponding author: Felix N. Bäßmann, Information Systems Institute, Leibniz University Hannover, Königsworther Platz 1, 30167 Hannover, Germany. Tel.: +49 511 762 4996; E-mail: baessmann@iwi.uni-hannover.de.
Abstract: Today, access to real-time information from emergency scenes is still limited for emergency medical services, fire departments, and their professionals, also called first responders. Emergency Response Information Systems (ERISs) have recently been discussed in the literature as a potential solution to this problem. Using the Design Science Research (DSR) paradigm, we present a novel 5G-enabled ERIS (5G-ERIS) design that leverages 5G mobile network technologies to offer diverse real-time information. We provide a user-centered examination of design specifications for a 5G-ERIS based on a smart city digital twin. Based on literature and qualitative expert interviews with several first responders in Germany, we derive how emergency medical services and fire departments can improve their decision-making with this 5G-ERIS. Based on existing 5G application architectures, we structure our identified design specifications into four system layers. Our findings provide an essential knowledge base for the successful development, deployment, and long-term use of 5G-ERISs. We stimulate a broader discussion on the design objectives and specifications of 5G-ERISs in theory and practice.
Keywords: 5G, design science research, ERIS, emergency, digital twin
DOI: 10.3233/IDT-230476
Journal: Intelligent Decision Technologies, vol. 18, no. 2, pp. 1157-1179, 2024
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