Data fusion analysis and synthesis framework for improving disaster situation awareness

Name: Data fusion analysis and synthesis framework for improving disaster situation awareness
Author: Aksit, M., Say, Hanne, Eren, Mehmet Arda, de Camargo, V. V.

İsim	Data fusion analysis and synthesis framework for improving disaster situation awareness
Yazar	Aksit, M., Say, Hanne, Eren, Mehmet Arda, de Camargo, V. V.
Basım Tarihi:	2023-09
Basım Yeri	- MDPI
Konu	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
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	2504-446X
Kayıt Numarası	b00e4ab7-aed8-44f4-8f29-2bdf351e52c3
Tarih	2023-09
Notlar	TÜBİTAK
Örnek Metin	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

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Data fusion analysis and synthesis framework for improving disaster situation awareness

Yazar Aksit, M., Say, Hanne, Eren, Mehmet Arda, de Camargo, V. V.

Basım Tarihi 2023-09

Basım Yeri - MDPI

Konu 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

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 2504-446X

Kayıt Numarası b00e4ab7-aed8-44f4-8f29-2bdf351e52c3

Tarih 2023-09

Notlar TÜBİTAK

Örnek Metin 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