Author
Aksit, M., Say, Hanne, Eren, Mehmet Arda, de Camargo, V. V.
Publication Date
2023-09
Publication Place
-
MDPI
Subject
Automated synthesis for data fusion, Disaster situation awareness, Domain model of data sources for earthquake detection, Model-based framework for determining optimal data fusion, Quality of data fusion, UAVs and data sources
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
2504-446X
Record ID
b00e4ab7-aed8-44f4-8f29-2bdf351e52c3
Date
2023-09
Notes
TÜBİTAK
Sample Text
To carry out required aid operations efficiently and effectively after an occurrence of a disaster such as an earthquake, emergency control centers must determine the effect of disasters precisely and and in a timely manner. Different kinds of data-gathering techniques can be used to collect data from disaster areas, such as sensors, cameras, and unmanned aerial vehicles (UAVs). Furthermore, data-fusion techniques can be adopted to combine the data gathered from different sources to enhance the situation awareness. Recent research and development activities on advanced air mobility (AAM) and related unmanned aerial systems (UASs) provide new opportunities. Unfortunately, designing these systems for disaster situation analysis is a challenging task due to the topological complexity of urban areas, and multiplicity and variability of the available data sources. Although there are a considerable number of research publications on data fusion, almost none of them deal with estimating the optimal set of heterogeneous data sources that provide the best effectiveness and efficiency value in determining the effect of disasters. Moreover, existing publications are generally problem- and system-specific. This article proposes a model-based novel analysis and synthesis framework to determine the optimal data fusion set among possibly many alternatives, before expensive implementation and installation activities are carried out.
DOI
10.3390/drones7090565
Cilt
7
