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Big data analytics in public safety and personal security. Challenges and potential

 
: Biliri, Evmorfia; Kokkinakos, Panagiotis; Michailitsi, Ariadni; Papaspyros, Dimitris; Tsapelas, John; Mouzakitis, Spiros; Koussouris, Sotirios; Lampathaki, Fenareti; Glickman, Yuri; Kirstein, Fabian

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Jardim-Gonçalves, Ricardo (Ed.) ; Institute of Electrical and Electronics Engineers -IEEE-:
23rd International Conference on Engineering, Technology and Innovaiton, ICE/ITMC 2017. Proceedings : 27-29 June 2017, Madeira Island, Portugal
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5386-0774-9
ISBN: 978-1-5386-0775-6
S.1382-1386
International Conference on Engineering, Technology and Innovation (ICE) <23, 2017, Madeira>
European Commission EC
H2020; 732189; AEGIS
Englisch
Konferenzbeitrag
Fraunhofer FOKUS ()

Abstract
Public safety and personal security organizations need to achieve and maintain high levels of service, while managing the expectations of citizens, the mandates of legislation, and the impacts of new forms of technology, including mobile and IoT communications. In this context, Big and Linked Data analysis is expected to play a key role in the domain of Public Safety and Personal security industries. The paper presents the challenges in achieving efficient and secure big data analysis in this domain, in view of the current state-of-the-art in big and linked data technologies, and proposes a framework that brings together the data, the network & the technologies to create a curated, semantically enhanced, interlinked & multilingual platform for public & personal safety-related big data.

: http://publica.fraunhofer.de/dokumente/N-484516.html