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Export Reference (APA) 
Mestre Santos, T., Marinheiro, R. N. & Brito e Abreu, F. (2024). Wireless Crowd Detection for Smart Overtourism Mitigation. In Elena Kornyshova, Rébecca Deneckère, Eric Gressier-Soudan, John Murray, Sjaak Brinkkemper (Ed.), Smart Life and Smart Life Engineering: Current State and Future Vision. (pp. 1-21).: Springer Nature.
Export Reference (IEEE) 
T. M. Santos et al.,  "Wireless Crowd Detection for Smart Overtourism Mitigation", in Smart Life and Smart Life Engineering: Current State and Future Vision, Elena Kornyshova, Rébecca Deneckère, Eric Gressier-Soudan, John Murray, Sjaak Brinkkemper, Ed., Springer Nature, 2024, pp. 1-21
Export BibTeX 
@incollection{santos2024_1716153265853,
	author = "Mestre Santos, T. and Marinheiro, R. N. and Brito e Abreu, F.",
	title = "Wireless Crowd Detection for Smart Overtourism Mitigation",
	chapter = "",
	booktitle = "Smart Life and Smart Life Engineering: Current State and Future Vision",
	year = "2024",
	volume = "",
	series = "Lecture Notes in Business Information Processing",
	edition = "",
	pages = "1-1",
	publisher = "Springer Nature",
	address = "",
	url = "https://www.springer.com/series/7911"
}
Export RIS 
TY  - CHAP
TI  - Wireless Crowd Detection for Smart Overtourism Mitigation
T2  - Smart Life and Smart Life Engineering: Current State and Future Vision
AU  - Mestre Santos, T.
AU  - Marinheiro, R. N.
AU  - Brito e Abreu, F.
PY  - 2024
SP  - 1-21
SN  - 1865-1348
UR  - https://www.springer.com/series/7911
AB  - Overtourism occurs when the number of tourists exceeds the carrying capacity of a destination, leading to negative impacts on the environment, culture, and quality of life for residents. By monitoring overtourism, destination managers can identify areas of concern and implement measures to mitigate the negative impacts of tourism while promoting smarter tourism practices. This can help ensure that tourism benefits both visitors and residents while preserving the natural and cultural resources that make these destinations so appealing.

This chapter describes a low-cost approach to monitoring overtourism based on mobile devices’ wireless activity. A flexible architecture was designed for a smart tourism toolkit to be used by small and medium-sized enterprises (SMEs) in crowding management solutions, to build better tourism services, improve efficiency and sustainability, and reduce the overwhelming feeling of pressure in critical hotspots.

The crowding sensors count the number of surrounding mobile devices, by detecting trace elements of wireless technologies, overcoming MAC address randomization. They run detection programs for several technologies, and fingerprinting analysis results are only stored locally in an anonymized database, without infringing privacy rights. After that edge computing, sensors communicate the crowding information to a cloud server, by using a variety of uplink techniques to mitigate local connectivity limitations, something that has been often disregarded in alternative approaches.

Field validation of sensors has been performed on Iscte’s campus before their planned use in other locations, such as the Pena Palace in Sintra. Preliminary results show that these sensors can be deployed in multiple scenarios and provide a diversity of spatiotemporal crowding data and analysis in order to promote smart engineering techniques to be used for tourism overcrowding management.
ER  -