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...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9144582/ |
| _version_ | 1818662660905893888 |
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| author | Juan Ramon Santana Luis Sanchez Pablo Sotres Jorge Lanza Tomas Llorente Luis Munoz |
| author_facet | Juan Ramon Santana Luis Sanchez Pablo Sotres Jorge Lanza Tomas Llorente Luis Munoz |
| author_sort | Juan Ramon Santana |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-17T05:04:29Z |
| format | Article |
| id | doaj.art-f5d83b61786d4312b3d991d40b81ee84 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T05:04:29Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f5d83b61786d4312b3d991d40b81ee842022-12-21T22:02:28ZengIEEEIEEE Access2169-35362020-01-01813539413540510.1109/ACCESS.2020.30106099144582A Privacy-Aware Crowd Management System for Smart Cities and Smart BuildingsJuan Ramon Santana0https://orcid.org/0000-0003-1374-2153Luis Sanchez1https://orcid.org/0000-0003-0136-3420Pablo Sotres2https://orcid.org/0000-0002-2881-3594Jorge Lanza3https://orcid.org/0000-0002-9586-1334Tomas Llorente4Luis Munoz5https://orcid.org/0000-0002-7704-1199Network Planning and Mobile Communications Laboratory, Universidad de Cantabria, Santander, SpainNetwork Planning and Mobile Communications Laboratory, Universidad de Cantabria, Santander, SpainNetwork Planning and Mobile Communications Laboratory, Universidad de Cantabria, Santander, SpainNetwork Planning and Mobile Communications Laboratory, Universidad de Cantabria, Santander, SpainNetwork Planning and Mobile Communications Laboratory, Universidad de Cantabria, Santander, SpainNetwork Planning and Mobile Communications Laboratory, Universidad de Cantabria, Santander, SpainCities 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.https://ieeexplore.ieee.org/document/9144582/Smart cityInternet of Thingscrowd managementartificial intelligencepositioning |
| spellingShingle | Juan Ramon Santana Luis Sanchez Pablo Sotres Jorge Lanza Tomas Llorente Luis Munoz A Privacy-Aware Crowd Management System for Smart Cities and Smart Buildings IEEE Access Smart city Internet of Things crowd management artificial intelligence positioning |
| title | 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_short | A Privacy-Aware Crowd Management System for Smart Cities and Smart Buildings |
| title_sort | privacy aware crowd management system for smart cities and smart buildings |
| topic | Smart city Internet of Things crowd management artificial intelligence positioning |
| url | https://ieeexplore.ieee.org/document/9144582/ |
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