Enabling disaster early warning via a configurable data collection framework and real-time analytics

Young Woo Kwon; Seungwon Yang; Haeyong Chung

doi:10.1145/2814940.2815014

Enabling disaster early warning via a configurable data collection framework and real-time analytics

Young Woo Kwon
, Seungwon Yang
, Haeyong Chung

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The detection and prediction of natural catastrophes or manmade disasters before they occur has recently shone the light on several relatively new technologies. Due to the significant development of mobile hardware and software technologies, a smartphone has become an important device for detecting and warning about such disasters. Specifically, disasterrelated data can be collected from diverse sources including smartphones' sensors and social networks, and then the collected data are further analyzed to detect disasters and alert people about them. These collective data enable a user to have access to a variety of essential information related to disaster events. Using the example of a communicable disease outbreak, such information helps to identify and detect the ground zero of a disaster, as well as make sense of the means of transmission, progress, and patterns of the disaster. In this paper, we discuss a novel approach for analyzing and interacting with collective sensor data in a visual, real-time, and scalable fashion, offering diverse perspectives and data management components.

Original language	English
Title of host publication	HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction
Publisher	Association for Computing Machinery, Inc
Pages	337-340
Number of pages	4
ISBN (Electronic)	9781450335270
DOIs	https://doi.org/10.1145/2814940.2815014
State	Published - 21 Oct 2015
Event	3rd International Conference on Human-Agent Interaction, HAI 2015 - Daegu, Korea, Republic of Duration: 21 Oct 2015 → 24 Oct 2015

Publication series

Name	HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction

Conference

Conference	3rd International Conference on Human-Agent Interaction, HAI 2015
Country/Territory	Korea, Republic of
City	Daegu
Period	21/10/15 → 24/10/15

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Crisis informatics
Disaster
Early warning
Mobile devices
Ontology
Visual analytics

Access to Document

10.1145/2814940.2815014

Cite this

Kwon, Y. W., Yang, S., & Chung, H. (2015). Enabling disaster early warning via a configurable data collection framework and real-time analytics. In HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction (pp. 337-340). (HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction). Association for Computing Machinery, Inc. https://doi.org/10.1145/2814940.2815014

Kwon, Young Woo ; Yang, Seungwon ; Chung, Haeyong. / Enabling disaster early warning via a configurable data collection framework and real-time analytics. HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction. Association for Computing Machinery, Inc, 2015. pp. 337-340 (HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction).

@inproceedings{82aaafda08bd478ba55f1aa7b8658184,

title = "Enabling disaster early warning via a configurable data collection framework and real-time analytics",

abstract = "The detection and prediction of natural catastrophes or manmade disasters before they occur has recently shone the light on several relatively new technologies. Due to the significant development of mobile hardware and software technologies, a smartphone has become an important device for detecting and warning about such disasters. Specifically, disasterrelated data can be collected from diverse sources including smartphones' sensors and social networks, and then the collected data are further analyzed to detect disasters and alert people about them. These collective data enable a user to have access to a variety of essential information related to disaster events. Using the example of a communicable disease outbreak, such information helps to identify and detect the ground zero of a disaster, as well as make sense of the means of transmission, progress, and patterns of the disaster. In this paper, we discuss a novel approach for analyzing and interacting with collective sensor data in a visual, real-time, and scalable fashion, offering diverse perspectives and data management components.",

keywords = "Crisis informatics, Disaster, Early warning, Mobile devices, Ontology, Visual analytics",

author = "Kwon, \{Young Woo\} and Seungwon Yang and Haeyong Chung",

note = "Publisher Copyright: {\textcopyright} 2015 ACM.; 3rd International Conference on Human-Agent Interaction, HAI 2015 ; Conference date: 21-10-2015 Through 24-10-2015",

year = "2015",

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doi = "10.1145/2814940.2815014",

language = "English",

series = "HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction",

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}

Kwon, YW, Yang, S & Chung, H 2015, Enabling disaster early warning via a configurable data collection framework and real-time analytics. in HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction. HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction, Association for Computing Machinery, Inc, pp. 337-340, 3rd International Conference on Human-Agent Interaction, HAI 2015, Daegu, Korea, Republic of, 21/10/15. https://doi.org/10.1145/2814940.2815014

Enabling disaster early warning via a configurable data collection framework and real-time analytics. / Kwon, Young Woo; Yang, Seungwon; Chung, Haeyong.
HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction. Association for Computing Machinery, Inc, 2015. p. 337-340 (HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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N2 - The detection and prediction of natural catastrophes or manmade disasters before they occur has recently shone the light on several relatively new technologies. Due to the significant development of mobile hardware and software technologies, a smartphone has become an important device for detecting and warning about such disasters. Specifically, disasterrelated data can be collected from diverse sources including smartphones' sensors and social networks, and then the collected data are further analyzed to detect disasters and alert people about them. These collective data enable a user to have access to a variety of essential information related to disaster events. Using the example of a communicable disease outbreak, such information helps to identify and detect the ground zero of a disaster, as well as make sense of the means of transmission, progress, and patterns of the disaster. In this paper, we discuss a novel approach for analyzing and interacting with collective sensor data in a visual, real-time, and scalable fashion, offering diverse perspectives and data management components.

AB - The detection and prediction of natural catastrophes or manmade disasters before they occur has recently shone the light on several relatively new technologies. Due to the significant development of mobile hardware and software technologies, a smartphone has become an important device for detecting and warning about such disasters. Specifically, disasterrelated data can be collected from diverse sources including smartphones' sensors and social networks, and then the collected data are further analyzed to detect disasters and alert people about them. These collective data enable a user to have access to a variety of essential information related to disaster events. Using the example of a communicable disease outbreak, such information helps to identify and detect the ground zero of a disaster, as well as make sense of the means of transmission, progress, and patterns of the disaster. In this paper, we discuss a novel approach for analyzing and interacting with collective sensor data in a visual, real-time, and scalable fashion, offering diverse perspectives and data management components.

KW - Crisis informatics

KW - Disaster

KW - Early warning

KW - Mobile devices

KW - Ontology

KW - Visual analytics

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Kwon YW, Yang S, Chung H. Enabling disaster early warning via a configurable data collection framework and real-time analytics. In HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction. Association for Computing Machinery, Inc. 2015. p. 337-340. (HAI 2015 - Proceedings of the 3rd International Conference on Human-Agent Interaction). doi: 10.1145/2814940.2815014

Enabling disaster early warning via a configurable data collection framework and real-time analytics

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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