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Instant Learning For Crisis Response

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dc.contributor.author Suydam, Martin
dc.creator Suydam, Martin
dc.date 2008-06-19
dc.date.accessioned 2008-08-07T19:38:15Z
dc.date.available NO_RESTRICTION en
dc.date.available 2008-08-07T19:38:15Z
dc.date.issued 2008-08-07T19:38:15Z
dc.identifier.uri https://hdl.handle.net/1920/3217
dc.description.abstract Important to effective use of graphic portrayals of data and information is the science of communicating effectively with symbols. In general, today’s practice of icon design is more art than true science. While attractiveness of symbols has merit, there exists a real discipline void in connecting human sensory (may be more than visual) and cognitive processes to easy-to-comprehend symbols. The primary objective of this project is to develop a scientific methodology and the tools necessary for effective icon design, evaluation, selection, and implementation. This project is considered as a foundation stage upon which future research will be based. The purpose was to establish the methodology for creation of icons for required and essential messages in emergency management visual displays. The use of the latest technology developments in Computer-Aided Facility Management (CAFM) was used as a platform for demonstration and evaluation. It is likely that solutions for navigation within facility structures will likely require use of CAFM to be effective. While demonstration of CAFM application produced useful results, the process methodology developed for icon creation, evaluation, and use is more important than any initial group of icon products created. Future work will involve the proof of scientific icon identification and recognition theory in the context of Emergency Management needs. That challenge is distilled to the following questions: “Is it possible and practicable to develop icons producing consistent messages with little, or, better yet, no, learning? If these icon messages can effectively and efficiently be created, can they be easily transmitted, received, and effectively/reliably acted upon”. This project involves development/adaptation of many enabling-technology innovations in Computer-Aided Facility Management (CAFM) that would permit wireless deployment of spatial data technology for data access and navigation within facility structures. While robust, enabling-communications, both wireless and web-based, was considered essential environment for successful satisfying Emergency Management responder needs, mechanisms to ensure reduction in communication burden were considered essential. The communication burden is considered both in terms of the load placed on the communication transport system and the human reception and cognitive decoding aspects. These aspects can be measured in terms of file sizes required and speeds and accuracy of human response. A major development component to minimizing the communication burden was accomplished by exploiting Scalable Vector Graphics (SVG) technology for CAFM implementation where rendering of equivalent graphics can be reduced in size by a factor of 1,000. Integration and demonstration CAFM-SVG was viewed as a major challenge and was accomplished.
dc.language.iso en_US en
dc.subject Icon en_US
dc.subject SVG Icon en_US
dc.subject Icon Design Guidelines en_US
dc.subject Instant Learning en_US
dc.subject CAFM en_US
dc.subject Emergency Management en_US
dc.title Instant Learning For Crisis Response en
dc.type Project en
thesis.degree.name Engineer Degree en
thesis.degree.level Master's en
thesis.degree.discipline Engineer Degree en
thesis.degree.grantor George Mason University en


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