Smart resilience through IoT-enabled natural disaster management: A COVID-19 response in São Paulo state

IF 2.1 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Alessandro S. Santos, Icaro Goncales, Angelina Silva, Rodrigo Neves, Igor Teixeira, Eder Barbosa, Vagner Gava, Olga Yoshida
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Abstract

Natural disaster management approach establishes stages of prevention, preparation, response, and recovery. With the Internet of Things (IoT), Bigdata, Business Intelligence, and other Information Communication Technologies, data can be gathered to support decisions in stages of the response to natural disaster events. In biological natural disasters, the ICTs can also support efforts to promote social distancing, public health, and economic monitoring to face the threads. São Paulo state used IoT in scenarios to face COVID-19, such as monitoring vehicular interurban mobility, social distancing, and economic activity. Frameworks, strategies, data views, and use cases are presented to support the decision-making process to face this biological natural disaster. The data-driven approach supports several purposes, including the communication of social distancing indices, economic recovery, the progression of contagion, and deaths. It also played a pivotal role in fostering transparency initiatives for society and supporting the crisis committee by facilitating situational analyses, and this approach became standard practice for pandemic response. Studies and innovative visualisation perspectives have produced positive outcomes, guiding the decision-making process through data analysis. Noteworthy use cases were interurban traffic fence monitoring; mapping of virus spreading; tracking the economic impact concerning recovery plans; and, evaluating the effectiveness of public policies.

Abstract Image

通过支持物联网的自然灾害管理实现智能复原力:圣保罗州的 COVID-19 应对措施
自然灾害管理方法分为预防、准备、应对和恢复几个阶段。利用物联网(IoT)、大数据、商业智能和其他信息通信技术,可以收集数据,为应对自然灾害事件各阶段的决策提供支持。在生物自然灾害中,信息和通信技术还可以支持促进社会隔离、公共卫生和经济监测等工作,以应对自然灾害。圣保罗州在应对 COVID-19 的场景中使用了物联网,如监测城市间的车辆流动、社会隔离和经济活动。介绍了框架、战略、数据视图和用例,以支持应对这一生物自然灾害的决策过程。数据驱动方法支持多个目的,包括社会疏远指数、经济恢复、传染进展和死亡人数的交流。它还在促进社会透明度倡议方面发挥了关键作用,并通过促进形势分析为危机委员会提供支持,这种方法已成为应对大流行病的标准做法。研究和创新的可视化视角产生了积极的成果,通过数据分析指导了决策过程。值得一提的使用案例有:城际交通围栏监测;病毒传播地图;跟踪恢复计划对经济的影响;以及评估公共政策的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IET Smart Cities
IET Smart Cities Social Sciences-Urban Studies
CiteScore
7.70
自引率
3.20%
发文量
25
审稿时长
21 weeks
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