A privacy-aware crowd management system for smart cities and smart buildings

Cities are growing at a dizzying pace and they require improved methods to manage crowded areas. Crowd management stands for the decisions and actions taken to supervise and control densely populated spaces and it involves multiple challenges, from recognition and assessment to application of action...

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Detalles Bibliográficos
Autores: Santana Martínez, Juan Ramón|||0000-0003-1374-2153, Sánchez González, Luis|||0000-0003-0136-3420, Sotres García, Pablo|||0000-0002-2881-3594, Lanza Calderón, Jorge|||0000-0002-9586-1334, Llorente Cabello, Tomás, Muñoz Gutiérrez, Luis|||0000-0002-7704-1199
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universidad de Cantabria (UC)
Repositorio:UCrea Repositorio Abierto de la Universidad de Cantabria
Idioma:inglés
OAI Identifier:oai:repositorio.unican.es:10902/19211
Acceso en línea:http://hdl.handle.net/10902/19211
Access Level:acceso abierto
Palabra clave:Smart city
Internet of Things
Crowd management
Artificial intelligence
Positioning
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network_acronym_str ES
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spelling A privacy-aware crowd management system for smart cities and smart buildingsSantana Martínez, Juan Ramón|||0000-0003-1374-2153Sánchez González, Luis|||0000-0003-0136-3420Sotres García, Pablo|||0000-0002-2881-3594Lanza Calderón, Jorge|||0000-0002-9586-1334Llorente Cabello, TomásMuñoz Gutiérrez, Luis|||0000-0002-7704-1199Smart cityInternet of ThingsCrowd managementArtificial intelligencePositioningCities are growing at a dizzying pace and they require improved methods to manage crowded areas. Crowd management stands for the decisions and actions taken to supervise and control densely populated spaces and it involves multiple challenges, from recognition and assessment to application of actions tailored to the current situation. To that end, Wi-Fi-based monitoring systems have emerged as a cost-effective solution for the former one. The key challenge that they impose is the requirement to handle large datasets and provide results in near real-time basis. However, traditional big data and event processing approaches have important shortcomings while dealing with crowd management information. In this paper, we describe a novel system architecture for real-time crowd recognition for smart cities and smart buildings that can be easily replicated. The described system proposes a privacy-aware platform that enables the application of artificial intelligence mechanisms to assess crowds' behavior in buildings employing sensed Wi-Fi traces. Furthermore, the present paper shows the implementation of the system in two buildings, an airport and a market, as well as the results of applying a set of classification algorithms to provide crowd management information.This work was supported in part by the Spanish Government (MINECO) by means of the Project Future Internet Enabled Resilient CitiEs (FIERCE) under Grant RTI2018-093475-A-I00, and in part by the European Union’s Horizon 2020 Programme through the European project Federated CPS Digital Innovation Hubs for the Smart Anything Everywhere Initiative (FED4SAE) under Grant 761708.Institute of Electrical and Electronics Engineers Inc.Universidad de Cantabria20202020-07-20journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articlehttp://hdl.handle.net/10902/19211IEEE Access, 2020, 8, 135394-135405reponame:UCrea Repositorio Abierto de la Universidad de Cantabriainstname:Universidad de Cantabria (UC)InglésengEuropean Commission http://dx.doi.org/10.13039/501100000780 Horizon 2020 Framework Programme 761708open accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:repositorio.unican.es:10902/192112026-06-02T12:39:31Z
dc.title.none.fl_str_mv A privacy-aware crowd management system for smart cities and smart buildings
title A privacy-aware crowd management system for smart cities and smart buildings
spellingShingle A privacy-aware crowd management system for smart cities and smart buildings
Santana Martínez, Juan Ramón|||0000-0003-1374-2153
Smart city
Internet of Things
Crowd management
Artificial intelligence
Positioning
title_short A privacy-aware crowd management system for smart cities and smart buildings
title_full A privacy-aware crowd management system for smart cities and smart buildings
title_fullStr A privacy-aware crowd management system for smart cities and smart buildings
title_full_unstemmed A privacy-aware crowd management system for smart cities and smart buildings
title_sort A privacy-aware crowd management system for smart cities and smart buildings
dc.creator.none.fl_str_mv Santana Martínez, Juan Ramón|||0000-0003-1374-2153
Sánchez González, Luis|||0000-0003-0136-3420
Sotres García, Pablo|||0000-0002-2881-3594
Lanza Calderón, Jorge|||0000-0002-9586-1334
Llorente Cabello, Tomás
Muñoz Gutiérrez, Luis|||0000-0002-7704-1199
author Santana Martínez, Juan Ramón|||0000-0003-1374-2153
author_facet Santana Martínez, Juan Ramón|||0000-0003-1374-2153
Sánchez González, Luis|||0000-0003-0136-3420
Sotres García, Pablo|||0000-0002-2881-3594
Lanza Calderón, Jorge|||0000-0002-9586-1334
Llorente Cabello, Tomás
Muñoz Gutiérrez, Luis|||0000-0002-7704-1199
author_role author
author2 Sánchez González, Luis|||0000-0003-0136-3420
Sotres García, Pablo|||0000-0002-2881-3594
Lanza Calderón, Jorge|||0000-0002-9586-1334
Llorente Cabello, Tomás
Muñoz Gutiérrez, Luis|||0000-0002-7704-1199
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidad de Cantabria
dc.subject.none.fl_str_mv Smart city
Internet of Things
Crowd management
Artificial intelligence
Positioning
topic Smart city
Internet of Things
Crowd management
Artificial intelligence
Positioning
description Cities are growing at a dizzying pace and they require improved methods to manage crowded areas. Crowd management stands for the decisions and actions taken to supervise and control densely populated spaces and it involves multiple challenges, from recognition and assessment to application of actions tailored to the current situation. To that end, Wi-Fi-based monitoring systems have emerged as a cost-effective solution for the former one. The key challenge that they impose is the requirement to handle large datasets and provide results in near real-time basis. However, traditional big data and event processing approaches have important shortcomings while dealing with crowd management information. In this paper, we describe a novel system architecture for real-time crowd recognition for smart cities and smart buildings that can be easily replicated. The described system proposes a privacy-aware platform that enables the application of artificial intelligence mechanisms to assess crowds' behavior in buildings employing sensed Wi-Fi traces. Furthermore, the present paper shows the implementation of the system in two buildings, an airport and a market, as well as the results of applying a set of classification algorithms to provide crowd management information.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-07-20
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10902/19211
url http://hdl.handle.net/10902/19211
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv European Commission http://dx.doi.org/10.13039/501100000780 Horizon 2020 Framework Programme 761708
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
publisher.none.fl_str_mv Institute of Electrical and Electronics Engineers Inc.
dc.source.none.fl_str_mv IEEE Access, 2020, 8, 135394-135405
reponame:UCrea Repositorio Abierto de la Universidad de Cantabria
instname:Universidad de Cantabria (UC)
instname_str Universidad de Cantabria (UC)
reponame_str UCrea Repositorio Abierto de la Universidad de Cantabria
collection UCrea Repositorio Abierto de la Universidad de Cantabria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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