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Efstratios Kontopoulos, Panagiotis Mitzias, Jürgen Moßgraber, Philipp Hertweck, Hylke van der Schaaf, Désirée Hilbring, et al. (2018). Ontology-based Representation of Crisis Management Procedures for Climate Events. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1064–1073). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: One of the most critical challenges faced by authorities during the management of a climate-related crisis is the overwhelming flow of heterogeneous information coming from humans and deployed sensors (e.g. cameras, temperature measurements, etc.), which has to be processed in order to filter meaningful items and provide crisis decision support. Towards addressing this challenge, ontologies can provide a semantically unified representation of the domain, along with superior capabilities in querying and information retrieval. Nevertheless, the recently proposed ontologies only cover subsets of the relevant concepts. This paper proposes a more “all-around” lightweight ontology for climate crisis management, which greatly facilitates decision support and merges several pertinent aspects: representation of a crisis, climate parameters that may cause climate crises, sensor analysis, crisis incidents and related impacts, first responder unit allocations. The ontology could constitute the backbone of the decision support systems for crisis management.
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Jürgen Moßgraber, Désirée Hilbring, Hylke van der Schaaf, Philipp Hertweck, Efstratios Kontopoulos, Panagiotis Mitzias, et al. (2018). The sensor to decision chain in crisis management. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 754–763). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In every disaster and crisis, incident time is the enemy, and getting accurate information about the scope, extent, and impact of the disaster is critical to creating and orchestrating an effective disaster response and recovery effort. Decision Support Systems for disaster and crisis situations need to solve the problem of facilitating the broad variety of sensors available today. This includes the research domain of the Internet of Things and data coming from social media. All this data needs to be aggregated and fused, the semantics of the data needs to be understood and the results must be presented to the decision makers in an accessible way. Furthermore, the interaction and integration with risk and crisis management systems are necessary for a better analysis of the situation and faster reaction times. This paper provides an insight into the sensor to decision chain and proposes solutions and technologies for each step.
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Philipp Hertweck, Tobias Hellmund, Hylke van der Schaaf, Jürgen Moßgraber, & Jan-Wilhelm Blume. (2019). Management of Sensor Data with Open Standards. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: In an emergency, getting up-to-date information about the current situation is crucial to orchestrate an efficient response. Due to its objectivity, preciseness and comparability, time-series data offer broad possibilities to manage emergency incidents. Since the Internet of Things (IoT) is rapidly growing with an estimated number of 30 billion sensors in 2020, it offers excellent potential to collect time-series data for improving situational awareness. The IoT brings several challenges: caused by a splintered sensor manufacturer landscape, data comes in various structures, incompatible protocols and unclear semantics. To tackle these challenges a well-defined interface, from where uniform data can be queried, is necessary. The Open Geospatial Consortium (OGC) has recognized this demand and developed the SensorThings API standard, an open, unified way to interconnect devices throughout the IoT, which is implemented by the FRaunhofer-Opensource-SensorThings-Server (FROST). This paper presents the standard, its implementation and the application to the domain of crisis management.
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Tobias Hellmund, Jürgen Moßgraber, Manfred Schenk, Philipp Hertweck, Hylke van der Schaaf, & Hans Springer. (2021). The Design and Implementation of ZEUS: Novel Support in Managing Large-Scale Evacuations. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 1003–1014). Blacksburg, VA (USA): Virginia Tech.
Abstract: This paper introduces ZEUS, a novel software tool for the management of large-scale evacuations. The tasks ZEUS supports were derived from two Standard Operating Procedures, developed on demand of the German federal states. To this date, the authors are not aware of another software tool that gives technical support to the management and control of large-scale evacuations as ZEUS does. It comprises functionalities to (pre-)plan a large-scale evacuation, as well as functions for the management of the flow of evacuees during an evacuation situation. This paper describes how the requirements of ZEUS were derived from the two named planning frameworks and how use-cases were developed to meet the requirements; these use-cases were conceptualized as different steps of a workflow. In an evaluation, the paper gives credit how ZEUS can provide technical support for the evaluation of large-scale evacuations. ZEUS will undergo a two-staged review process: first, a controlled theoretical scenario is tested and, upon successful completion, a practical test on a large scale will be executed.
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