Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

FIWARE-compatible Smart Data Models for Satellite Imagery and Flood Risk Assessment to Enhance Data Management

Ioannis-Omiros Kouloglou
* ,
Gerasimos Antzoulatos
* ORCID logo ,
Georgios Vosinakis
* ORCID logo ,
Francesca Lombardo
,
Alberto Abella
,
Marios Bakratsas
,
Anastasia Moumtzidou
ORCID logo ,
Evangelos Maltezos
,
Ilias Gialampoukidis
ORCID logo ,
Eleftherios Ouzounoglou
ORCID logo ,
Stefanos Vrochidis
ORCID logo ,
Angelos Amditis
ORCID logo ,
Ioannis Kompatsiaris
ORCID logo ,
Michele Ferri
Version 1 : Received: 24 November 2023 / Approved: 24 November 2023 / Online: 24 November 2023 (15:08:26 CET)

A peer-reviewed article of this Preprint also exists.

Kouloglou, I.-O.; Antzoulatos, G.; Vosinakis, G.; Lombardo, F.; Abella, A.; Bakratsas, M.; Moumtzidou, A.; Maltezos, E.; Gialampoukidis, I.; Ouzounoglou, E.; et al. FIWARE-Compatible Smart Data Models for Satellite Imagery and Flood Risk Assessment to Enhance Data Management. Information 2024, 15, 257, doi:10.3390/info15050257. Kouloglou, I.-O.; Antzoulatos, G.; Vosinakis, G.; Lombardo, F.; Abella, A.; Bakratsas, M.; Moumtzidou, A.; Maltezos, E.; Gialampoukidis, I.; Ouzounoglou, E.; et al. FIWARE-Compatible Smart Data Models for Satellite Imagery and Flood Risk Assessment to Enhance Data Management. Information 2024, 15, 257, doi:10.3390/info15050257.

Abstract

The increasing rate of adoption of innovative technological achievements along with the penetration of the Next Generation Internet (NGI) technologies and Artificial Intelligence (AI) in the water sector, are leading to a shift to a Water-Smart Society. New challenges have emerged in terms of data interoperability, sharing, and trustworthiness due to the rapidly increasing volume of heterogeneous data generated by multiple technologies. Hence, there is a need for efficient harmonisation and smart modeling of the data to foster advanced AI analytical processes which will lead to efficient water data management. The main objective of this work is to propose two Smart Data Models focusing on the modeling of the Satellite Imaginary data and the Flood Risk Assessment processes. The utilisation of those models reinforces the fusion and homogenisation of diverse information and data facilitating the adoption of AI technologies for flood mapping and monitoring. Furthermore, a holistic framework has been developed and evaluated via qualitative and quantitative performance indicators revealing the efficacy of the proposed models concerning the usage of the models in real cases. The framework is based on the well-known and compatible technologies on NGSI-LD standards which are customised and applicable easily to support the water data management processes effectively.

Keywords

Smart Data Models; Remote sensing; Satellite Imagery; Flood Monitoring and Mapping; Flood Risk Assessment; Data Sharing; Interoperability; Water Data Management

Subject

Computer Science and Mathematics, Other

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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