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Increasing disaster victim survival rate: SaveMyLife Mobile Application development
International Journal of Disaster Risk Reduction ( IF 5 ) Pub Date : 2021-05-06 , DOI: 10.1016/j.ijdrr.2021.102290
Mohammed Ali Berawi , Pekka Leviäkangas , Sutan Akbar Onggar Siahaan , Alya Hafidza , Mustika Sari , Perdana Miraj , Ruki Harwahyu , Gunawan Saroji

Natural disasters have harmful effects on human lives and the economy, as well as physical damage to the environment. Previous research has discussed technological and social perspectives to cope with disaster events, but limited evidence was found on the communication between victims and rescuers and mobile applications' impact as the means of communication between the users. This research aims to improve search and rescue team response time and increase the victim survival rate by taking into account the victim prioritization and technology utilization through mobile disaster applications. This research considers Indonesia as the case study due to its high risk of natural disaster occurrences. A mixed-method approach using the questionnaire survey and in-depth interview was conducted. A fuzzy inference system and a supervised machine learning approach were also utilized to achieve the research objectives. The research identified four components that should be considered to improve the survival rate of victims. The proposed combination model shows that the prediction produces a significant accuracy and can be used to prioritize victims. This research's output also suggests a mobile application development that guides victims to safety points and connects them to the rescuers. The mobile application can be used from pre-disaster and emergency response phases.



中文翻译:

提高灾难受害者的生存率:SaveMyLife移动应用程序开发

自然灾害对人类生命和经济产生有害影响,并对环境造成物理破坏。先前的研究已经讨论了应对灾难事件的技术和社会观点,但是在受害者和救援人员之间的通信以及作为用户之间的通信手段的移动应用程序的影响方面,发现的证据有限。这项研究旨在通过考虑受害者优先级和通过移动灾难应用程序对技术的利用来改善搜索和救援团队的响应时间,并提高受害者生存率。由于印度尼西亚发生自然灾害的风险很高,因此本研究将其视为案例研究。采用问卷调查和深度访谈的混合方法。模糊推理系统和有监督的机器学习方法也被用来达到研究目的。该研究确定了应考虑提高受害者生存率的四个组成部分。所提出的组合模型表明,该预测产生了显着的准确性,可用于对受害者进行优先排序。这项研究的结果还提出了一种移动应用程序开发,可将受害者引导到安全点并将他们连接到救援人员。可以在灾难前和紧急响应阶段使用该移动应用程序。所提出的组合模型表明,该预测产生了显着的准确性,可用于对受害者进行优先排序。这项研究的结果还提出了一种移动应用程序开发,可将受害者引导到安全点并将他们连接到救援人员。可以在灾难前和紧急响应阶段使用该移动应用程序。所提出的组合模型表明,该预测产生了显着的准确性,可用于对受害者进行优先排序。这项研究的结果还提出了一种移动应用程序开发,可将受害者引导到安全点并将他们连接到救援人员。可以在灾难前和紧急响应阶段使用该移动应用程序。

更新日期:2021-05-08
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