Analysing and shaping civil security

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The aim of civil security research is to make fire and disaster protection and civil defence more efficient. For example, using artificial intelligence (AI) to analyse images during disaster relief operations in order to check the navigability of bridges and roads. The department also analyses data from cities and municipalities in order to carry out automated hazard analyses for demand planning and creates risk assessments, e.g. accessibility maps (travel time isochrones) or similar.

Research also focuses on the application of empirical social research methods in order to understand the behaviour of crisis teams, groups of people or companies in the event of a disaster. Processes and training methods are analysed in order to improve the ability to react in emergency situations. The department's portfolio in the field of civil security research also includes the design of information services based on the Internet of Things (IoT), which serve to better manage disaster situations.

Our expertise

Our competences Your challenges
  • Investigation of important issues in civil protection using empirical social research methods
  • Use of market intelligence processes to make markets in civil defence and civil protection transparent
  • Use of forecasting methods to predict events
  • Training of generative AI for use in authorities and organisations with security tasks
  • AI for image analysis in disaster response (Geo-AI), change detection, data analysis for hazard analysis, empirical social research on behaviour in the event of a disaster
  • How do I create a good basis for hazard defence planning based on geodata?
  • Where can I find an overview of command and control systems for the BOS market?
  • What innovations will this market offer in the coming years?

 

References

Organisation

»Risk and Location Analyses« Department

The department develops data-based solutions for greater civil security, more resilient supply chains and sustainable location decisions. With a strong understanding of the market and industry, research focuses on data-centred spatial and risk research. The experts rely on AI-supported remote sensing, geoinformation and empirical social research to analyse and locate complex economic relationships.