Plataforma para visualização geo-temporal de apinhamento turístico
April 16, 2025 · Declared Dead · 🏛 arXiv.org
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Authors
Rodrigo Simões, Fernando Brito e Abreu, Adriano Lopes
arXiv ID
2504.13952
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Tourist crowding degrades the visitor experience and negatively impacts the environment and the local population, potentially making tourism in popular destinations unsustainable. This motivated us to develop, within the framework of the European RESETTING project related to the digital transformation of tourism, a platform to visualize this crowding, exploring historical data, detecting patterns and trends and predicting future events. The ultimate goal is to support short- and medium-term decision-making to mitigate the phenomenon. To this end, the platform takes into account the carrying capacity of the target sites when calculating crowding density. The integration of data from different sources is achieved with an extensible, connector-based architecture. Three scenarios for using the platform are described, relating to major annual crowding events. Two of them, in the municipality of Lisbon, are based on data from a mobile network provided by the LxDataLab initiative. The third, in Melbourne, Australia, using public data from a network of movement sensors called the Pedestrian Counting System. An experiment to evaluate the usability of the proposed platform using NASA-TLX is also described. -- -- O apinhamento turístico degrada a experiência dos visitantes e impacta negativamente o ambiente e a população local, podendo tornar insustentável o turismo em destinos populares. Isto motivou-nos a desenvolver, no âmbito do projeto europeu RESETTING relacionado com a transformação digital do turismo, uma plataforma para visualizar este apinhamento, explorando dados históricos, detetando padrões e tendências e prevendo eventos futuros. O objetivo final é apoiar a tomada de decisão, a curto e médio prazo, para mitigar o fenómeno. Para tal, a plataforma considera a capacidade de carga dos locais alvo no cálculo da densidade de apinhamento. A integração de dados de diversas fontes é conseguida com uma arquitetura extensível, à base de conetores. São descritos três cenários de utilização da plataforma, relativos a eventos anuais de grande apinhamento. Dois deles, no município de Lisboa, baseados em dados de uma rede móvel disponibilizados pela iniciativa LxDataLab. O terceiro, em Melbourne na Austrália, utilizando dados públicos de uma rede de sensores de movimento designada de Pedestrian Counting System. É ainda descrita uma experiência de avaliação da usabilidade da plataforma proposta, usando o NASA-TLX.
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