A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence
<p>The development of a system that monitors social media continuously for general landslide-related content using a landslide classification model to identify and retain the most relevant information is described and validated. The system harvests photographs in real-time from these data and...
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| مؤلفون آخرون: | , , , , , |
| منشور في: |
2022
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| الموضوعات: | |
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إضافة وسم
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| _version_ | 1864513518604124160 |
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| author | Catherine V.L. Pennington (18426939) |
| author2 | Rémy Bossu (9090281) Ferda Ofli (8983517) Muhammad Imran (282621) Umair Qazi (8983514) Julien Roch (9090278) Vanessa J. Banks (18426942) |
| author2_role | author author author author author author |
| author_facet | Catherine V.L. Pennington (18426939) Rémy Bossu (9090281) Ferda Ofli (8983517) Muhammad Imran (282621) Umair Qazi (8983514) Julien Roch (9090278) Vanessa J. Banks (18426942) |
| author_role | author |
| dc.creator.none.fl_str_mv | Catherine V.L. Pennington (18426939) Rémy Bossu (9090281) Ferda Ofli (8983517) Muhammad Imran (282621) Umair Qazi (8983514) Julien Roch (9090278) Vanessa J. Banks (18426942) |
| dc.date.none.fl_str_mv | 2022-07-01T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.ijdrr.2022.103089 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/A_near-real-time_global_landslide_incident_reporting_tool_demonstrator_using_social_media_and_artificial_intelligence/25671762 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Built environment and design Building Earth sciences Geology Engineering Civil engineering 6 max) Landslides Triggered-landslides Image-labelling Artificial intelligence Database |
| dc.title.none.fl_str_mv | A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p>The development of a system that monitors social media continuously for general landslide-related content using a landslide classification model to identify and retain the most relevant information is described and validated. The system harvests photographs in real-time from these data and tags each image as landslide or not-landslide. A training model was developed with input from computer scientists, geologists (landslide specialists) and social media specialists to establish a large image dataset that has then been applied to the live Twitter data stream. The preliminary model was developed by training a convolutional neural network on the dataset. Quantitative verification of the system's performance during a real-world deployment shows that the system can detect landslide reports with Precision = 76%. The demonstrator model is currently running live https://landslide-aidr.qcri.org/service.php; the next stage of development will incorporate stakeholder and user feedback.</p><h2>Other Information</h2> <p> Published in: International Journal of Disaster Risk Reduction<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ijdrr.2022.103089" target="_blank">https://dx.doi.org/10.1016/j.ijdrr.2022.103089</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_f837343b16826077eb3d9388b5e11889 |
| identifier_str_mv | 10.1016/j.ijdrr.2022.103089 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/25671762 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligenceCatherine V.L. Pennington (18426939)Rémy Bossu (9090281)Ferda Ofli (8983517)Muhammad Imran (282621)Umair Qazi (8983514)Julien Roch (9090278)Vanessa J. Banks (18426942)Built environment and designBuildingEarth sciencesGeologyEngineeringCivil engineering6 max)LandslidesTriggered-landslidesImage-labellingArtificial intelligenceDatabase<p>The development of a system that monitors social media continuously for general landslide-related content using a landslide classification model to identify and retain the most relevant information is described and validated. The system harvests photographs in real-time from these data and tags each image as landslide or not-landslide. A training model was developed with input from computer scientists, geologists (landslide specialists) and social media specialists to establish a large image dataset that has then been applied to the live Twitter data stream. The preliminary model was developed by training a convolutional neural network on the dataset. Quantitative verification of the system's performance during a real-world deployment shows that the system can detect landslide reports with Precision = 76%. The demonstrator model is currently running live https://landslide-aidr.qcri.org/service.php; the next stage of development will incorporate stakeholder and user feedback.</p><h2>Other Information</h2> <p> Published in: International Journal of Disaster Risk Reduction<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.ijdrr.2022.103089" target="_blank">https://dx.doi.org/10.1016/j.ijdrr.2022.103089</a></p>2022-07-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.ijdrr.2022.103089https://figshare.com/articles/journal_contribution/A_near-real-time_global_landslide_incident_reporting_tool_demonstrator_using_social_media_and_artificial_intelligence/25671762CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/256717622022-07-01T00:00:00Z |
| spellingShingle | A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence Catherine V.L. Pennington (18426939) Built environment and design Building Earth sciences Geology Engineering Civil engineering 6 max) Landslides Triggered-landslides Image-labelling Artificial intelligence Database |
| status_str | publishedVersion |
| title | A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence |
| title_full | A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence |
| title_fullStr | A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence |
| title_full_unstemmed | A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence |
| title_short | A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence |
| title_sort | A near-real-time global landslide incident reporting tool demonstrator using social media and artificial intelligence |
| topic | Built environment and design Building Earth sciences Geology Engineering Civil engineering 6 max) Landslides Triggered-landslides Image-labelling Artificial intelligence Database |