KIRAS Security Research

Kooperative Projekte > Call 2019

AIFER – Artificial Intelligence for Emergency Response

The FFG KIRAS project AIFER focuses on the automated analysis and fusion of heteroge-neous mass data (EO image data, geo-social media data, geo-referenced news articles, Google Trends, etc.) using artificial intelligence (AI) as well as the transparent fusion of the derived information and their provision for civil protection.

Disaster events and major damage situations caused by floods, forest fires, extreme snow conditions or storms pose major challenges for civil protection in terms of (1) avail-ability of near real-time and large-scale information for disaster assessment and management, (2) analysis of the data in near real time, and (3) fusion of derived in-formation products for intuitive, transparent and focused decision support. The follow-ing problems arise from this:

P1: Lack of automated AI-based algorithms for analysis of innovative data sources to support situation awareness and assessment.

P2: Lack of availability of reliable AI methods for the fusion of information layers from the analysis of remote sensing and internet data in disaster management.

P3: Largely neglected consideration of legal, sociological and ethical framework con-ditions with regard to the data and AI methods used.

P4: Frequently non-demand-oriented research, which often does not generate usable results for end users.

P5: Insufficient consideration of the integration of project developments into existing, proven processes of disaster management.

The AIFER project addresses all of the above-mentioned problems to ensure civil securi-ty and better information availability during a natural disaster. Solutions:

S1: Research into explainable AI algorithms that automatically extract information from earth observation data (e.g. satellite data, aerial and drone images) and internet data (e.g. geo-social media, georeferenced news articles, Google Trends).

S2: Development of an AI-based algorithm for the fusion of information based on the analyses of earth observation and internet data.

S3: Legal, sociological and ethical issues are dealt with in detail, and examined and reflected with the help of an Ethical Board.

S4: End-user needs are collected and investigated in a structured way and integrated into technical research activities.

S5: Validation and integrability of the results are achieved through the strong involve-ment of end users and practical testing in a TRL4 test environment.

AIFER primarily addresses the disaster scenario of flooding with the analysis of two his-torical (“cold”) and a real-time (“warm”) use cases. The transferability to other disaster scenarios (forest fires, storms, extreme snowfall) will be validated.

ProjektleiterIn / Name und Institut/Unternehmen
Assoz.-Prof. Dr. Bernd Resch, Universität Salzburg, Fachbereich Geoinformatik – Z_GIS

Auflistung der weiteren Projekt- bzw. KooperationspartnerInnen

Österreichische Konsortialpartner
Universität Salzburg, Fachbereich Geoinformatik – Z_GIS
Institut für empirische Sozialforschung GmbH
Johanniter Österreich Ausbildung und Forschung gemeinnützige GmbH
Österreichisches Rotes Kreuz – Landesverband Salzburg
Spatial Services GmbH

Deutsche Konsortialpartner
Deutsches Zentrum für Luft- und Raumfahrt (DLR)
Universität Kassel
Bundesanstalt Technisches Hilfswerk (THW)
Bayerisches Rotes Kreuz
Disy Informationssysteme GmbH

Assoziierte Partner
Ärzte ohne Grenzen (MSF)
Rotes Kreuz Tirol
Rotes Kreuz Wien

Name / Institut oder Unternehmen

Universität Salzburg, Fachbereich Geoinformatik – Z_GIS

Kontakt
Assoz.-Prof. Dr. Bernd Resch
Universität Salzburg, Fachbereich Geoinformatik – Z_GIS
Schillerstraße 30
A-5020 Salzburg
Tel: +43-662-8044-7551
Fax: +43-662-8044-7560
E-mail: bernd.resch@sbg.ac.at
Website: zgis.at 
Projekt-Website: https://giscience.zgis.at/aifer