Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Crowdsourcing in early warning systems

: Meissen, Ulrich

Volltext urn:nbn:de:0011-n-3221021 (444 KByte PDF)
MD5 Fingerprint: 25b6c87ca50ad65fec35a32d838b44e9
Erstellt am: 16.1.2015

Ames, D.P. ; International Environmental Modelling and Software Society -IEMSS-:
Bold Vision for Environmental Modelling. 7th International Congress on Environmental Modelling and Software 2014. Proceedings. Vol.1 : June 15-19, San Diego, California, USA
San Diego/Calif., 2014
ISBN: 978-88-9035-744-2
International Congress on Environmental Modelling and Software <7, 2014, San Diego/Calif.>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer FOKUS ()
crowdsourcing; disaster management; early warning; mobile alert systems; Architectures

The use of mobile devices as an effective and targeted way for alerting the public in cases of disasters has become an important part of future infrastructures for early warning and disaster management. In contrast to classical alert approaches such as TV, Radio and sirens that are offering solely a one-directional communication the use of smart phones opens new potentials such as feedback mechanisms that support more precise warnings and adapted response actions. In this context crowdsourcing techniques show a high potential as an effective measure to meliorate the data basis for predictions and augment warnings. This paper discusses the application of crowdsourcing in Early Warning Systems (EWS) with the main focus on elaborating a general architecture that provides a reference structure and implementation scheme for crowdsourcing in this domain. Based on a comprehension of existing crowdsourcing approaches typical components are identified and mapped to monitoring subsystems of early warning systems. As a result the paper presents an integrated architecture and discusses the three main structural variants of applying crowdsourcing in early warning systems along the example of a prototypical extension of two existing large-scale hydro-meteorological warning systems.