A framework for detecting unfolding emergencies using humans as sensors

Abstract The advent of online social networks (OSNs) paired with the ubiquitous proliferation of smartphones have enabled social sensing systems. In the last few years, the aptitude of humans to spontaneously collect and timely share context information has been exploited for emergency detection and...
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Autor*in:	Avvenuti, Marco [verfasserIn] Cimino, Mario G. C. A. [verfasserIn] Cresci, Stefano [verfasserIn] Marchetti, Andrea [verfasserIn] Tesconi, Maurizio [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Twitter Social sensing Social media mining Event detection Crisis informatics Emergency management

Übergeordnetes Werk:	Enthalten in: SpringerPlus - London : Biomed Central, 2012, 5(2016), 1 vom: 19. Jan.
Übergeordnetes Werk:	volume:5 ; year:2016 ; number:1 ; day:19 ; month:01

Links:	Volltext

DOI / URN:	10.1186/s40064-016-1674-y

Katalog-ID:	SPR032775032

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spelling	10.1186/s40064-016-1674-y doi (DE-627)SPR032775032 (SPR)s40064-016-1674-y-e DE-627 ger DE-627 rakwb eng 600 ASE Avvenuti, Marco verfasserin aut A framework for detecting unfolding emergencies using humans as sensors 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The advent of online social networks (OSNs) paired with the ubiquitous proliferation of smartphones have enabled social sensing systems. In the last few years, the aptitude of humans to spontaneously collect and timely share context information has been exploited for emergency detection and crisis management. Apart from event-specific features, these systems share technical approaches and architectural solutions to address the issues with capturing, filtering and extracting meaningful information from data posted to OSNs by networks of human sensors. This paper proposes a conceptual and architectural framework for the design of emergency detection systems based on the “human as a sensor” (HaaS) paradigm. An ontology for the HaaS paradigm in the context of emergency detection is defined. Then, a modular architecture, independent of a specific emergency type, is designed. The proposed architecture is demonstrated by an implemented application for detecting earthquakes via Twitter. Validation and experimental results based on messages posted during earthquakes occurred in Italy are reported. Twitter (dpeaa)DE-He213 Social sensing (dpeaa)DE-He213 Social media mining (dpeaa)DE-He213 Event detection (dpeaa)DE-He213 Crisis informatics (dpeaa)DE-He213 Emergency management (dpeaa)DE-He213 Cimino, Mario G. C. A. verfasserin aut Cresci, Stefano verfasserin aut Marchetti, Andrea verfasserin aut Tesconi, Maurizio verfasserin aut Enthalten in SpringerPlus London : Biomed Central, 2012 5(2016), 1 vom: 19. Jan. (DE-627)718615298 (DE-600)2661116-8 2193-1801 nnns volume:5 year:2016 number:1 day:19 month:01 https://dx.doi.org/10.1186/s40064-016-1674-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2016 1 19 01
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allfieldsGer	10.1186/s40064-016-1674-y doi (DE-627)SPR032775032 (SPR)s40064-016-1674-y-e DE-627 ger DE-627 rakwb eng 600 ASE Avvenuti, Marco verfasserin aut A framework for detecting unfolding emergencies using humans as sensors 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The advent of online social networks (OSNs) paired with the ubiquitous proliferation of smartphones have enabled social sensing systems. In the last few years, the aptitude of humans to spontaneously collect and timely share context information has been exploited for emergency detection and crisis management. Apart from event-specific features, these systems share technical approaches and architectural solutions to address the issues with capturing, filtering and extracting meaningful information from data posted to OSNs by networks of human sensors. This paper proposes a conceptual and architectural framework for the design of emergency detection systems based on the “human as a sensor” (HaaS) paradigm. An ontology for the HaaS paradigm in the context of emergency detection is defined. Then, a modular architecture, independent of a specific emergency type, is designed. The proposed architecture is demonstrated by an implemented application for detecting earthquakes via Twitter. Validation and experimental results based on messages posted during earthquakes occurred in Italy are reported. Twitter (dpeaa)DE-He213 Social sensing (dpeaa)DE-He213 Social media mining (dpeaa)DE-He213 Event detection (dpeaa)DE-He213 Crisis informatics (dpeaa)DE-He213 Emergency management (dpeaa)DE-He213 Cimino, Mario G. C. A. verfasserin aut Cresci, Stefano verfasserin aut Marchetti, Andrea verfasserin aut Tesconi, Maurizio verfasserin aut Enthalten in SpringerPlus London : Biomed Central, 2012 5(2016), 1 vom: 19. Jan. (DE-627)718615298 (DE-600)2661116-8 2193-1801 nnns volume:5 year:2016 number:1 day:19 month:01 https://dx.doi.org/10.1186/s40064-016-1674-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2016 1 19 01
allfieldsSound	10.1186/s40064-016-1674-y doi (DE-627)SPR032775032 (SPR)s40064-016-1674-y-e DE-627 ger DE-627 rakwb eng 600 ASE Avvenuti, Marco verfasserin aut A framework for detecting unfolding emergencies using humans as sensors 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The advent of online social networks (OSNs) paired with the ubiquitous proliferation of smartphones have enabled social sensing systems. In the last few years, the aptitude of humans to spontaneously collect and timely share context information has been exploited for emergency detection and crisis management. Apart from event-specific features, these systems share technical approaches and architectural solutions to address the issues with capturing, filtering and extracting meaningful information from data posted to OSNs by networks of human sensors. This paper proposes a conceptual and architectural framework for the design of emergency detection systems based on the “human as a sensor” (HaaS) paradigm. An ontology for the HaaS paradigm in the context of emergency detection is defined. Then, a modular architecture, independent of a specific emergency type, is designed. The proposed architecture is demonstrated by an implemented application for detecting earthquakes via Twitter. Validation and experimental results based on messages posted during earthquakes occurred in Italy are reported. Twitter (dpeaa)DE-He213 Social sensing (dpeaa)DE-He213 Social media mining (dpeaa)DE-He213 Event detection (dpeaa)DE-He213 Crisis informatics (dpeaa)DE-He213 Emergency management (dpeaa)DE-He213 Cimino, Mario G. C. A. verfasserin aut Cresci, Stefano verfasserin aut Marchetti, Andrea verfasserin aut Tesconi, Maurizio verfasserin aut Enthalten in SpringerPlus London : Biomed Central, 2012 5(2016), 1 vom: 19. Jan. (DE-627)718615298 (DE-600)2661116-8 2193-1801 nnns volume:5 year:2016 number:1 day:19 month:01 https://dx.doi.org/10.1186/s40064-016-1674-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2016 1 19 01
language	English
source	Enthalten in SpringerPlus 5(2016), 1 vom: 19. Jan. volume:5 year:2016 number:1 day:19 month:01
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spellingShingle	Avvenuti, Marco ddc 600 misc Twitter misc Social sensing misc Social media mining misc Event detection misc Crisis informatics misc Emergency management A framework for detecting unfolding emergencies using humans as sensors
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title	A framework for detecting unfolding emergencies using humans as sensors
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title_auth	A framework for detecting unfolding emergencies using humans as sensors
abstract	Abstract The advent of online social networks (OSNs) paired with the ubiquitous proliferation of smartphones have enabled social sensing systems. In the last few years, the aptitude of humans to spontaneously collect and timely share context information has been exploited for emergency detection and crisis management. Apart from event-specific features, these systems share technical approaches and architectural solutions to address the issues with capturing, filtering and extracting meaningful information from data posted to OSNs by networks of human sensors. This paper proposes a conceptual and architectural framework for the design of emergency detection systems based on the “human as a sensor” (HaaS) paradigm. An ontology for the HaaS paradigm in the context of emergency detection is defined. Then, a modular architecture, independent of a specific emergency type, is designed. The proposed architecture is demonstrated by an implemented application for detecting earthquakes via Twitter. Validation and experimental results based on messages posted during earthquakes occurred in Italy are reported.
abstractGer	Abstract The advent of online social networks (OSNs) paired with the ubiquitous proliferation of smartphones have enabled social sensing systems. In the last few years, the aptitude of humans to spontaneously collect and timely share context information has been exploited for emergency detection and crisis management. Apart from event-specific features, these systems share technical approaches and architectural solutions to address the issues with capturing, filtering and extracting meaningful information from data posted to OSNs by networks of human sensors. This paper proposes a conceptual and architectural framework for the design of emergency detection systems based on the “human as a sensor” (HaaS) paradigm. An ontology for the HaaS paradigm in the context of emergency detection is defined. Then, a modular architecture, independent of a specific emergency type, is designed. The proposed architecture is demonstrated by an implemented application for detecting earthquakes via Twitter. Validation and experimental results based on messages posted during earthquakes occurred in Italy are reported.
abstract_unstemmed	Abstract The advent of online social networks (OSNs) paired with the ubiquitous proliferation of smartphones have enabled social sensing systems. In the last few years, the aptitude of humans to spontaneously collect and timely share context information has been exploited for emergency detection and crisis management. Apart from event-specific features, these systems share technical approaches and architectural solutions to address the issues with capturing, filtering and extracting meaningful information from data posted to OSNs by networks of human sensors. This paper proposes a conceptual and architectural framework for the design of emergency detection systems based on the “human as a sensor” (HaaS) paradigm. An ontology for the HaaS paradigm in the context of emergency detection is defined. Then, a modular architecture, independent of a specific emergency type, is designed. The proposed architecture is demonstrated by an implemented application for detecting earthquakes via Twitter. Validation and experimental results based on messages posted during earthquakes occurred in Italy are reported.
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title_short	A framework for detecting unfolding emergencies using humans as sensors
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