Urban search and rescue is needed for a variety of emergencies or disasters, including tornadoes, floods, dam failures, technological accidents, and terrorist activities. The efficiency to save people is becoming very important. With the development of the technology, people are trying to find a better way to help people get out of the dangerous places as soon as possible. DIORAMA system has been proposed to help with this problem and turns out very successful on improving efficiency during emergency situation. However, the current DIORAMA system is not perfect for all scenarios, for example, there are some outdoor environments do not support GPS service. Also, the RFID reader is very heavy for responders to carry and the indoor environment is not applicable for DIORAMA system. Besides, there are lack of forensic visualization toolkits that are able to help the incident commander analyze the responders’ behavior and efficiency. In this project, we propose a Localization, Visualization and Evacuation Guidance System in Emergency Situations. The functionalities in this system include localization in outdoor environments using BLE. Besides, for outdoor environments, some forensic visualization toolkit that can help the responder analyze the responders’ behavior with the capability of visualization and representation of data clearly as well as replay the task, detect anomalies and visualize the anomalies clearly is also provided in improving the efficiency and organization in the future task. In addition, the system also includes an indoor localization, navigation guidance and visualization system that provides guidance for people to exit a dangerous building as soon as possible. This system is able to localize the position of evacuees, and construct the exit path that helps reduce the escape time as well as provide a navigation guidance that is able to guide the user to the exit. In addition, an analyst simulation application is provided to simulate the evacuees in a building and evaluate the evacuation time for evacuees given specific path generation algorithm.
Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:masters_theses_2-1356 |
Date | 13 July 2016 |
Creators | Tang, Jingyan |
Publisher | ScholarWorks@UMass Amherst |
Source Sets | University of Massachusetts, Amherst |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Masters Theses |
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