Research topics
The Research Topics investigated by the members of the World Alliance on Digitalization for Disaster & Emergency Management, span over a broad range of domains in various disciplines. In the following, examples of research topics are given under the following classifications:
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Disaster and emergency management:
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Awareness, disaster and emergency detection and monitoring: Aims to detect the effects of disasters efficiently and effectively, such as the damages made, conditions of humans and living creatures, etc.
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Demand modeling and generation: Based on the observed damages and the environmental conditions, demand lists are automatically inferred for the necessary resources so that aid operations can be executed efficiently and effectively. Demands for resources can be various, including rescue operations, fire fighters, ambulances, security forces, repair teams, shelters, transport vehicles for evacuation, heating and cooking facilities, food and water, etc.
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Optimization and scheduling : The available resources are optimally assigned to the inferred demands on time. In case of insufficient resources, prioritization, trade-off and/or dynamic selection techniques are applied.
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Performance measurement: The performance indicators of operations are defined formally so that the desired objectives can be specified and measured. Accordingly, ongoing operations can be monitored online and in case of deviations from the desired performance values, corrective actions can be executed.
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Tracking and control: This phase includes both monitoring, evaluation and controlling actions of the ongoing activities as well as coordination among the aid operations.
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Simulation and game playing: To determine the effect of a large set of prospective disaster scenarios, determine the effectiveness and efficiency of the disaster and emergency ecosystem platform, evaluate the necessary quantity of resources and to optimize the locations of logistics centers, simulation environments and techniques must be researched, designed and implemented. Even in times when no disasters are experienced, triggered by the simulated disaster scenarios, the platform must be continuously operational so that it can be optimized using online machine learning techniques.
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​​Computation: Realization of the disaster and emergency management system is not trivial and requires research in various
computer science disciplines: For example:
Event-based computation, Digital twins, Communication networks, Coordination, Platforms and Software Engineering Aspects.
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Sociological disaster research: It is the of the social relations amongst both natural and human-made disasters.
Demand modeling and generation
These research activities aim at automatically generating the demands based on the analysis of disaster and emergency situation analysis.
Examples of research topics are:
Demand modeling for a large set of kinds (rescue, repair, fire fighters, health services, proDtection, evacuation, food distribution, shelter providing, etc.)
Modeling demand and supply processes for each kind
Interpreting (input) data and inferring needs for demands
Disaster and emergency demand ontologies
Stream processing, complex event processing
Gathering data for improved demand generation
Machine learning techniques in improving the effectiveness and efficiency in demand generation
Grouping of demands
Prioritization of demands
Online management of varying disaster and emergency conditions
Techniques for demand management: efficient processing, storing, querying of demands
Extensibility and maintainability of demand management systems
Standardization of demand models and interfaces of demand management systems