Architecture-Oriented Agent-Based Simulations and Machine Learning Solution: The Case of Tsunami Emergency Analysis for Local Decision Makers

• Published in: Information (Basel) 2023-03, Vol.14 (3), p.172
• Main Authors: Čech, Pavel, Mattoš, Martin, Anderková, Viera, Babič, František, Alhasnawi, Bilal Naji, Bureš, Vladimír, Kořínek, Milan, Štekerová, Kamila, Husáková, Martina, Zanker, Marek, Manneela, Sunanda, Triantafyllou, Ioanna
• Format: Article
• Language: English
• Subjects: agent-based evacuation simulation; Agent-based models; Architecture; Australia; Big Data; Data mining; Data processing; Decision analysis; Decision making; decision support; Emergency communications systems; Emergency response; Emergency warning programs; Evacuation of civilians; Evacuations & rescues; Information technology; Infrastructure; Machine learning; Planning; Seismology; Simulation; Simulation methods; Software; Standardization; tsunami; tsunami warning system; tsunami warning system architecture; Tsunami warning systems; Tsunamis; Warning systems
• ISSN: 2078-2489; 2078-2489
• DOI: 10.3390/info14030172

Tsunamis are a perilous natural phenomenon endangering growing coastal populations and tourists in many seaside resorts. Failures in responding to recent tsunami events stresses the importance of further research in building a robust tsunami warning system, especially in the “last mile” component. The lack of detail, unification and standardisation in information processing and decision support hampers wider implementation of reusable information technology solutions among local authorities and officials. In this paper, the architecture of a tsunami emergency solution is introduced. The aim of the research is to present a tsunami emergency solution for local authorities and officials responsible for preparing tsunami response and evacuation plans. The solution is based on a combination of machine learning techniques and agent-based modelling, enabling analysis of both real and simulated datasets. The solution is designed and developed based on the principles of enterprise architecture development. The data exploration follows the practices for data mining and big data analyses. The architecture of the solution is depicted using the standardised notation and includes components that can be exploited by responsible local authorities to test various tsunami impact scenarios and prepare plans for appropriate response measures.