A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
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 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.
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 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.
A privacy-aware crowd management system for smart cities and smart buildings
Santana Martínez, Juan Ramón (author) / Sánchez González, Luis (author) / Sotres García, Pablo (author) / Lanza Calderón, Jorge (author) / Llorente Cabello, Tomás (author) / Muñoz Gutiérrez, Luis (author) / Universidad de Cantabria
2020-07-20
doi:10.1109/ACCESS.2020.3010609
IEEE Access, 2020, 8, 135394-135405
Article (Journal)
Electronic Resource
English
DDC:
720
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