Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events
We investigate the utility of DIORAMA-II system which provides enhanced situational awareness within a disaster scene by using real-time visual analytics tools and a collaboration platform between the incident commander and the emergency responders. Our trials were conducted in different geographica...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | International Journal of Telemedicine and Applications |
| Online Access: | http://dx.doi.org/10.1155/2016/9362067 |
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| author | Aura Ganz James M. Schafer Zhuorui Yang Jun Yi Graydon Lord Gregory Ciottone |
| author_facet | Aura Ganz James M. Schafer Zhuorui Yang Jun Yi Graydon Lord Gregory Ciottone |
| author_sort | Aura Ganz |
| collection | DOAJ |
| description | We investigate the utility of DIORAMA-II system which provides enhanced situational awareness within a disaster scene by using real-time visual analytics tools and a collaboration platform between the incident commander and the emergency responders. Our trials were conducted in different geographical areas (feature-rich and featureless regions) and in different lighting conditions (daytime and nighttime). DIORAMA-II obtained considerable time gain in efficiency compared to conventional paper based systems. DIORAMA-II time gain was reflected in reduction of both average triage time per patient (up to 34.3% average triage time reduction per patient) and average transport time per patient (up to 76.3% average transport time reduction per red patient and up to 66.3% average transport time reduction per yellow patient). In addition, DIORAMA-II ensured that no patients were left behind or transported in the incorrect order compared to the conventional method which resulted in patients being left behind and transported in the incorrect order. |
| format | Article |
| id | doaj-art-b4bc9b07311843e8a34f19234db7d351 |
| institution | Kabale University |
| issn | 1687-6415 1687-6423 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Telemedicine and Applications |
| spelling | doaj-art-b4bc9b07311843e8a34f19234db7d3512025-02-03T01:30:14ZengWileyInternational Journal of Telemedicine and Applications1687-64151687-64232016-01-01201610.1155/2016/93620679362067Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty EventsAura Ganz0James M. Schafer1Zhuorui Yang2Jun Yi3Graydon Lord4Gregory Ciottone5Electrical and Computer Engineering Department, University of Massachusetts Amherst, Amherst, MA 01003, USAElectrical and Computer Engineering Department, University of Massachusetts Amherst, Amherst, MA 01003, USAElectrical and Computer Engineering Department, University of Massachusetts Amherst, Amherst, MA 01003, USAElectrical and Computer Engineering Department, University of Massachusetts Amherst, Amherst, MA 01003, USAIntermedix Corporation, 1800 S. Bell Street, Suite 210, Arlington, VA 22202, USADisaster Preparedness Program, Harvard Humanitarian Initiative, Harvard University, Boston, MA 02215, USAWe investigate the utility of DIORAMA-II system which provides enhanced situational awareness within a disaster scene by using real-time visual analytics tools and a collaboration platform between the incident commander and the emergency responders. Our trials were conducted in different geographical areas (feature-rich and featureless regions) and in different lighting conditions (daytime and nighttime). DIORAMA-II obtained considerable time gain in efficiency compared to conventional paper based systems. DIORAMA-II time gain was reflected in reduction of both average triage time per patient (up to 34.3% average triage time reduction per patient) and average transport time per patient (up to 76.3% average transport time reduction per red patient and up to 66.3% average transport time reduction per yellow patient). In addition, DIORAMA-II ensured that no patients were left behind or transported in the incorrect order compared to the conventional method which resulted in patients being left behind and transported in the incorrect order.http://dx.doi.org/10.1155/2016/9362067 |
| spellingShingle | Aura Ganz James M. Schafer Zhuorui Yang Jun Yi Graydon Lord Gregory Ciottone Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events International Journal of Telemedicine and Applications |
| title | Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events |
| title_full | Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events |
| title_fullStr | Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events |
| title_full_unstemmed | Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events |
| title_short | Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events |
| title_sort | evaluation of a scalable information analytics system for enhanced situational awareness in mass casualty events |
| url | http://dx.doi.org/10.1155/2016/9362067 |
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