Affiliation:
1. Fraunhofer IOSB, Institute of Optronics, System Technologies and Image Exploitation, Karlsruhe, Germany
2. Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece
Abstract
Understanding the current situation is critical in every natural disaster or crisis. Therefore, there is a need for accurate and up-to-date information about the scope, extent and impact of a disaster. The basis for this information is data that is available through a variety of sensors. Decision Support Systems (DSSs) support decision makers in disaster management, response, and recovery by providing early warnings, insights into the current situation and recommendations for mitigation actions. For this purpose, raw sensor data needs to be collected, analyzed, integrated, and its semantics need to be automatically understood by the system. This series of processes forms a generic sensor to decision chain. In this paper, we present solutions and technologies to integrate those steps seamlessly, also demonstrating how each step of the pipeline can be visualized.
Reference38 articles.
1. W3C SPARQL Working Group. (2012) SPARQL 1.1 overview. W3C recommendation.
2. Angaramo, F., & Rossi, C. (2018) Online clustering and classification for real-time event detection in Twitter. In Proceedings of the 15th ISCRAM Conference, Rochester, NY. Academic Press.
3. SoKNOS – Using Semantic Technologies in Disaster Management Software
4. bAWARE. (2018a) The beAWARE Crisis Management Ontology v1.0. Retrieved from http://w3id.org/beaware_ontology
5. BBC. (2017) Hottest June day since summer of 1976 in heatwave. Retrieved from https://www.bbc.com/news/uk-40353118