Multi-Scale and Multi-Modal Streaming Data Aggregation and Processing for Decision Support during Natural Disasters
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Wright State University / OhioLINK
2018
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=wright1547811329783514 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-wright15478113297835142021-08-03T07:09:26Z Multi-Scale and Multi-Modal Streaming Data Aggregation and Processing for Decision Support during Natural Disasters Kar, Shruti Computer Science multi-modal data natural disasters disaster-related tweets gazetteers relief effort coordination OpenStreetMap geolocate flood mapping DisasterRecord With the surge in digital information systems, there is a data deluge from various sources that can be analyzed and integrated to produce relevant, reliable and actionable information, for better decision making.We employ multi-modal data (i.e., unstructured text, gazetteers, and imagery) for an aggregate level analysis and location-centric demand/request matching in the context of disaster relief. After classifying the Need expressed in a tweet (the WHAT), we leverage OpenStreetMap to geolocate that Need on a computationally accessible map of the local terrain (the WHERE) populated with location features such as hospitals and housing. Further, our novel use of flood mapping based on satellite images of the affected area supports the elimination of candidate resources that are not accessible by road transportation. The resulting map-based visualization of the tool DisasterRecord: Disaster response and relief coordination, serves two levels of users. A community level user (first-responders) can visualize aggregated summary of a selected geographical area and an individual level user can identify current needs and available resources in their geographic proximity. Additionally, our pluggable, modularized pipeline (DisasterRecord) is extensible so that additional functionality can be layered on top of the map. The integration of disaster-related tweets, imagery and pre-existing knowledge-base resources (gazetteers) reduce decision-making latency and enhance resiliency by assisting decision-makers and first responders involved with relief effort coordination. 2018 English text Wright State University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=wright1547811329783514 http://rave.ohiolink.edu/etdc/view?acc_num=wright1547811329783514 unrestricted This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center. |
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NDLTD |
| language |
English |
| sources |
NDLTD |
| topic |
Computer Science multi-modal data natural disasters disaster-related tweets gazetteers relief effort coordination OpenStreetMap geolocate flood mapping DisasterRecord |
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Computer Science multi-modal data natural disasters disaster-related tweets gazetteers relief effort coordination OpenStreetMap geolocate flood mapping DisasterRecord Kar, Shruti Multi-Scale and Multi-Modal Streaming Data Aggregation and Processing for Decision Support during Natural Disasters |
| author |
Kar, Shruti |
| author_facet |
Kar, Shruti |
| author_sort |
Kar, Shruti |
| title |
Multi-Scale and Multi-Modal Streaming Data Aggregation and Processing for Decision Support during Natural Disasters |
| title_short |
Multi-Scale and Multi-Modal Streaming Data Aggregation and Processing for Decision Support during Natural Disasters |
| title_full |
Multi-Scale and Multi-Modal Streaming Data Aggregation and Processing for Decision Support during Natural Disasters |
| title_fullStr |
Multi-Scale and Multi-Modal Streaming Data Aggregation and Processing for Decision Support during Natural Disasters |
| title_full_unstemmed |
Multi-Scale and Multi-Modal Streaming Data Aggregation and Processing for Decision Support during Natural Disasters |
| title_sort |
multi-scale and multi-modal streaming data aggregation and processing for decision support during natural disasters |
| publisher |
Wright State University / OhioLINK |
| publishDate |
2018 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=wright1547811329783514 |
| work_keys_str_mv |
AT karshruti multiscaleandmultimodalstreamingdataaggregationandprocessingfordecisionsupportduringnaturaldisasters |
| _version_ |
1719455098862567424 |