dc.contributor.author | López Novoa, Unai | |
dc.contributor.author | Aguilera, Unai | |
dc.contributor.author | Emaldi, Mikel | |
dc.contributor.author | López de Ipiña, Diego | |
dc.contributor.author | Pérez-de-Albeniz, Iker | |
dc.contributor.author | Valerdi, David | |
dc.contributor.author | Iturricha, Ibai | |
dc.contributor.author | Arza, Eneko | |
dc.date.accessioned | 2024-02-08T11:35:32Z | |
dc.date.available | 2024-02-08T11:35:32Z | |
dc.date.issued | 2017-02-17 | |
dc.identifier.citation | Personal and Ubiquitous Computing 21 : 507-519 (2017) | |
dc.identifier.issn | 1617-4909 | |
dc.identifier.uri | http://hdl.handle.net/10810/65664 | |
dc.description.abstract | The increase in the number of large-scale events held indoors (i.e., conferences and business events) opens new opportunities for crowd monitoring and access controlling as a way to prevent risks and provide further information about the event’s development. In addition, the availability of already connectable devices among attendees allows to perform non-intrusive positioning during the event, without the need of specific tracking devices. We present an algorithm for overcrowding detection based on passive Wi-Fi requests capture and a platform for event monitoring that integrates this algorithm. The platform offers access control management, attendees monitoring and the analysis and visualization of the captured information, using a scalable software architecture. In this paper, we evaluate the algorithm in two ways: First, we test its accuracy with data captured in a real event, and then we analyze the scalability of the code in a multi-core Apache Spark-based environment. The experiments show that the algorithm provides accurate results with the captured data, and that the code scales properly. | es_ES |
dc.description.sponsorship | This work has been partially supported by the Basque Country Government under the Gaitek funding program (IG-2014/00172) and the Spanish Ministry of Economy and Competitiveness (grant number TIN2013-47152-C3-3-R) | |
dc.language.iso | eng | es_ES |
dc.publisher | Springer | |
dc.relation | info:eu-repo/grantAgreement/MINECO/TIN2013-47152-C3-3-R | |
dc.rights | info:eu-repo/semantics/restrictedAccess | es_ES |
dc.subject | overcrowding detection | es_ES |
dc.subject | indoor location | es_ES |
dc.subject | scalable data processing | es_ES |
dc.title | Overcrowding detection in indoor events using scalable technologies | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | © 2017, Springer-Verlag London | |
dc.relation.publisherversion | https://link.springer.com/article/10.1007/s00779-017-1012-6 | |
dc.identifier.doi | 10.1007/s00779-017-1012-6 | |
dc.departamentoes | Lenguajes y sistemas informáticos | es_ES |
dc.departamentoeu | Hizkuntza eta sistema informatikoak | es_ES |