Abstract
Building fires fortunately rarely occur however they may cause the tragic loss of properties and lives. While we all watch the news and see the damage caused by fire on buildings and on rural vegetation, very little research has been undertaken on the rate a fire consumes a building’s structure. This re-search began when the question was asked “If a building is ablaze, how long does it take before the structure is severely damaged”. This project is an implementation of Big Data Analysis for Emergency Management through the use of statistical computing tool R and its data visualisation features to ana-lyse historical data set provided by a NSW Government Public Safety Agency that responds to struc-tural fire incidents. The main goal of this project is to determine the optimum fire services’ response time on property losses due to urban fires in Australia. More precisely, the results of this study will aid the decision making of Fire Service Agencies by determining the correlation between the damage level and the Emergency services response time. This project has implications for Fire Services not only in NSW but nationally and internationally as there is a research gap in the analysis of (Australian) fire data.
Recommended Citation
Smith, Stephen; Pang, Vincent; Liu, Kurt; Kavakli-Thorne, Manolya; Edwards, Andrew; Orgun, Mehmet; and Host, Richard, "ADOPTION OF DATA-DRIVEN DECISION MAKING IN FIRE EMERGENCY MANAGEMENT" (2016). Research Papers. 116.
https://aisel.aisnet.org/ecis2016_rp/116