Overview of data-driven hazard detection research at WSU's disaster resilience analytics center for enhancing community resilience

Loading...
Thumbnail Image
Authors
Dutta, Atri
Issue Date
2022-07-06
Type
Conference paper
Language
en_US
Keywords
Hazard detection , Artificial intelligence , Sensor networks
Research Projects
Organizational Units
Journal Issue
Alternative Title
Abstract

Early detection of hazards as well as the identification of geographical regions affected by a disaster play a substantial role in timely intervention and planning of disaster relief operations. We provide an overview of the current research efforts at Disaster Resilience Analytics Center for technologies that can facilitate early detection of hazard through collection and analysis of data by remote sensors, as well as identification of hazardous situations through analysis of social media data. The availability of these technologies can help reduce the risk of disasters, thereby improving the resilience of communities.

Description
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Citation
Dutta, A. (2022). Overview of data-driven hazard detection research at WSU's disaster resilience analytics center for enhancing community resilience Data-driven Resilience Research 2022, Leipzig, Germany.
Publisher
CEUR-WS
License
Journal
Volume
Issue
PubMed ID
DOI
ISSN
1613-0073
EISSN