Practice Report “Smart Disaster Management” — Combining Smart City Data and Citizen Participation to Increase Disaster Resilience

Author:

Wessel Daniel1ORCID,Holtz Julien1,König Florian1ORCID

Affiliation:

1. 9191 Universität zu Lübeck , Lübeck , Germany

Abstract

Abstract Smart cities have a huge potential to increase the everyday efficiency of cities, but also to increase preparation and resilience in case of natural disasters. Especially for disasters which are somewhat predicable like floods, sensor data can be used to provide citizens with up-to-date, personalized and location-specific information (street or even house level resolution). This information allows citizens to better prepare to avert water damage to their property, reduce the needed government support, and — by connecting citizens locally — improve mutual support among neighbors. But how can a smart city application be designed that is both usable and able to function during disaster conditions? Which smart city information can be used? How can the likelihood of mutual, local support be increased? In this practice report, we present the human-centered development process of an app to use Smart City data to better prepare citizens for floods and improve their mutual support during disasters as a case study to answer these questions.

Publisher

Walter de Gruyter GmbH

Subject

Computer Networks and Communications,Human-Computer Interaction,Communication,Business, Management and Accounting (miscellaneous),Information Systems,Social Psychology

Reference59 articles.

1. Inc ACM. ACM Digital Library. https://dl.acm.org, 2020.

2. Aaron Bangor, Philip Kortum, and James Miller. Determining what individual SUS scores mean: Adding an adjective rating scale. Usability Studies, 4(3):114–123, 2009. ISSN 1469493X. 10.1002/14651858.CD012733.pub2.

3. Robert A. Baron, Donn Byrne, and Nyla R. Branscombe. Social Psychology. Pearson Education, Inc., Boston, MA, eleventh edition, 2006.

4. J. Brooke. SUS – A quick and dirty usability scale. In Usability Evaluation in Industry, pages 189–194. Taylor and Francis, London, 1996.

5. Bundesamt für Bevölkerungsschutz (Deutschland). NINA – Die Warn-App des BBK. https://play.google.com/store/apps/details?id=de.materna.bbk.mobile.app&hl=de&gl=US, 2020.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3