Rapid damage assessment using social media images by combining human and machine intelligence

Muhammad Imran*, Firoj Alam, Umair Qazi, Steve Peterson, Ferda Ofli

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Citations (Scopus)

Abstract

Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings. This work analyzes the usefulness of social media imagery content to perform rapid damage assessment during a real-world disaster. An automatic image processing system, which was activated in collaboration with a volunteer response organization, processed ~280K images to understand the extent of damage caused by the disaster. The system achieved an accuracy of 76% computed based on the feedback received from the domain experts who analyzed ~29K system-processed images during the disaster. An extensive error analysis reveals several insights and challenges faced by the system, which are vital for the research community to advance this line of research.

Original languageEnglish
Title of host publicationISCRAM 2020 - Proceedings
Subtitle of host publication17th International Conference on Information Systems for Crisis Response and Management
EditorsAmanda Lee Hughes, Fiona McNeill, Christopher W. Zobel
PublisherInformation Systems for Crisis Response and Management, ISCRAM
Pages761-773
Number of pages13
ISBN (Electronic)9781949373271
Publication statusPublished - 2020
Event17th Annual International Conference on Information Systems for Crisis Response and Management, ISCRAM 2020 - Blacksburg, United States
Duration: 23 May 2021 → …

Publication series

NameProceedings of the International ISCRAM Conference
Volume2020-May
ISSN (Electronic)2411-3387

Conference

Conference17th Annual International Conference on Information Systems for Crisis Response and Management, ISCRAM 2020
Country/TerritoryUnited States
CityBlacksburg
Period23/05/21 → …

Keywords

  • Artificial Intelligence
  • Damage Assessment
  • Image Processing
  • Social Media

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