This systematic review provides a comprehensive overview of tsunami evacuation models. The review covers scientific studies from the last decade (2012–2021) and is explicitly focused on models using an agent-based approach. The PRISMA methodology was used to analyze 171 selected papers, resulting in over 53 studies included in the detailed full-text analysis. This review is divided into two main parts: (1) a descriptive analysis of the presented models (focused on the modeling tools, validation, and software platform used, etc.), and (2) model analysis (e.g., model purpose, types of agents, input and output data, and modeled area). Special attention was given to the features of these models specifically associated with an agent-based approach. The results lead to the conclusion that the research domain of agent-based tsunami evacuation models is quite narrow and specialized, with a high degree of variability in the model attributes and properties. At the same time, the application of agent-specific methodologies, protocols, organizational paradigms, or standards is sparse. Supplementary Information The online version contains supplementary material available at 10.1007/s11069-022-05643-x.
Digital twin is a computerized model of a physical device or system. Digital twins open new opportunities for operative decision making. Agent-Based Models (ABM) and simulations are core part of digital twins, especially in case of modelling humans in the spaces they act in. Microscopic simulations at the individual level have to be integrated with realistic models of environments. Here digital twins benefit from Building Information Models (BIM) but importing of BIM files into ABM platforms is not common. This problem is addressed in our paper. Principles of BIM are presented briefly. We suggest enhancing NetLogo modelling platform with BIM as the first step towards the development of digital twins models within NetLogo. The first part of the paper describes BIM formats and 3D visualization, including extraction of 3D model parts from IFC format. Parsing an IFC file using python is proposed, with recalculations of coordinates. It is also shown how the content of IFC can be reused in ABM and how simulations can affect BIM backwards.
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.
The research was motivated by the growing importance of visitor management in protected areas, which can be based on knowledge management, system modelling of processes and phenomena, and a deeper knowledge of the experience of visitors in connection with the concept of psychological carrying capacity. The work builds on previous publications and research by the authors, focused on the optimization of tourism impacts, visitor management and the development of the theory and applicability of the concept of carrying capacity. It emphasizes the overview analysis of the possibilities of using agent-based modelling and visualization of visitor flows in protected areas. The analysis of suitable sources was based on the PRISMA method, which showed the main research directions for the use of the agent-based approach in visitor management. For the practical application of modelling, the NetLogo environment was chosen, in which the visitor flows of the model area were simulated. The visitor attendance was evaluated in relation to the psychological carrying capacity. Subsequently, visitor management measures were implemented in the model, and repeated simulations of visitor attendance, based on monitored flows, were run for a specific location around Oheb Castle (the Železné hory/Iron Mountains, Bohemia). The main result is the innovative use of agent-based modelling in visitor management in the context of visitor experience, visitor satisfaction and psychological carrying capacity. The contribution of the presented research is also the proposal of future research directions for more accurate use of psychological carrying capacity in visitor management.
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