基于机器学习、物联网和大数据的灾前管理:调查和未来方向

Yehya Bouzeraa, Nardjas Bouchemal, Nada Zendaoui
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引用次数: 0

摘要

近年来,由于气候变化,世界各地经历了火灾、洪水、台风等严重的自然灾害。由于灾害难以应对和停止,研究人员将重点放在灾前管理阶段以减少损失。灾前管理是灾害管理周期的第一阶段,它使用从不同资源收集的可用数据来发现和预测灾害情况,以便给救援队更多的时间来准备和做出决定。随着现代技术和设备的发展,在此基础上提出了许多系统和方法,以提高灾害管理和预警系统的有效性和性能。本文旨在概述过去几年的研究,重点关注灾前管理的新技术(物联网,机器学习,大数据)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pre-disaster Management based Machine Learning, IoT and Big Data: Survey and future direction
Due to climate changes, the world has experienced in recent years violent natural disasters such as fires, floods and typhoons. Since Disasters are difficult to cope with and stop, researchers have focused on the pre-disaster management phase to reduce damage. Pre-disaster management is the first phase in a disaster management cycle, it uses available data collected from different resources, to detect and predict disaster cases in order to give rescue teams more time to prepare and make decisions.With development of modern technologies and equipment many systems and approaches were proposed based on this development to improve the effectiveness and performance of disaster management and early warning systems. This paper aims to provide an overview of last years studies, focusing on new technologies (IoT, Machine learning, Big Data) for pre-disaster management.
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