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


Abstract: 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.

 Autoría: Santana J.R., Sanchez L., Sotres P., Lanza J., Llorente T., Munoz L.,

 Fuente: IEEE Access, 2020, 8, 135394-135405

Editorial: Institute of Electrical and Electronics Engineers Inc.

 Fecha de publicación: 20/07/2020

Nº de páginas: 12

Tipo de publicación: Artículo de Revista

DOI: 10.1109/ACCESS.2020.3010609

ISSN: 2169-3536

Proyecto español: RTI2018-093475-A-I00

Proyecto europeo: info:eu-repo/grantAgreement/EC/H2020/761708/EU/Federated CPS Digital Innovation Hubs for the Smart Anything Everywhere Initiative/FED4SAE/

Url de la publicación: https://doi.org/10.1109/ACCESS.2020.3010609