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http://hdl.handle.net/10071/35870| Author(s): | Santos, T. Marinheiro, R. N. Brito e Abreu, F. |
| Editor: | Kornyshova, Elena Deneckère, Rébecca Brinkkemper, Sjaak |
| Date: | 2025 |
| Title: | Wireless crowd detection for smart overtourism mitigation |
| Book title/volume: | Smart life and smart life engineering: Current state and future vision |
| Pages: | 237 - 258 |
| Reference: | Santos, T., Marinheiro, R. N., & Brito e Abreu, F. (2025). Wireless crowd detection for smart overtourism mitigation. In E. Kornyshova, R. Deneckère, & S. Brinkkemper (Eds.), Smart life and smart life engineering: Current state and future vision (pp. 237-258). Springer. https://doi.org/10.1007/978-3-031-75887-4_11 |
| ISBN: | 978-3-031-75887-4 |
| DOI (Digital Object Identifier): | 10.1007/978-3-031-75887-4_11 |
| Keywords: | Crowding sensor Edge computing Fingerprinting MAC address randomization Overtourism Smart tourism toolkit Wi-Fi detection |
| Abstract: | 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. |
| Peerreviewed: | yes |
| Access type: | Open Access |
| Appears in Collections: | ISTAR-CLI - Capítulos de livros internacionais IT-CLI - Capítulos de livros internacionais |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| bookPart_98420.pdf | 4,53 MB | Adobe PDF | View/Open |
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