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GRAU EN TECNOLOGIES INDUSTRIALS I ANÀLISI ECONÒMICA (Pla 2018)

Nom

GRAU EN TECNOLOGIES INDUSTRIALS I ANÀLISI ECONÒMICA (Pla 2018)

Sigles

240GTINECO

Activa

Centre

Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB)

Pla d'estudis

2018

Nivell d'estudis

Grau

RSS

Contingut docent

Analysis of the touristic industry in Catalonia and development of a touristic model through neural nets

Treball Final de Grau

Alonso Graña, Javier

Tutor/a - Director/a: Bolea Monte, Yolanda

Data de publicació: 2025

Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB)

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This thesis addresses the challenges posed by tourist overcrowding in Catalonia and proposes solutions based on AI, specifically with Neural Networks (NN). The main objective of the project is to develop a model capable of predicting tourist overcrowding and to provide tools to policymakers to better manage this phenomenon and move towards a more sustainable tourism model. In the theoretical framework, the historical evolution of tourism in Catalonia is described, highlighting how this sector has become an economic pillar since the 1950s. With more than 20 million annual visitors, Catalonia is the most visited region in Spain, but this success has significant impacts. Tourist overcrowding has led to the expulsion of residents from historic centers, an unsustainable increase in housing prices, the loss of local businesses, and the saturation of public infrastructure. At an environmental level, elevated tourist pressure contributes to climate change and water scarcity, especially in coastal and rural areas. The project is based on the use of NNs, a tool from the field of machine learning that allows the modeling of complex relationships between data. These networks are configured to analyze tourism sustainability indicators in three main areas: social, economic, and environmental. By collecting statistical data from official bodies, models are built that are capable of projecting future scenarios on tourism overcrowding and identifying the most critical areas. The work methodology follows a systematic approach: first, the indicators necessary to evaluate tourism pressure are defined; then, a neural network is designed and trained using MATLAB, a software specialized (among other things) in data analysis and prediction. In terms of expected results, the project plans to provide practical tools that help local administrations identify areas with tourism saturation and design appropriate policies in the long run to mitigate the negative effects. However, the limitations of the work are recognized, such as the limited availability of reliable data, especially in the case of unregistered Tourist Use Housing (HUTs), and the difficulties in obtaining considerable amounts of data at the local level.

ENGINYERIA DEL MEDI AMBIENT (Examen final 1r quadrimestre) Restricted access to the UPC academic community

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Data de publicació: 2025

Escola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB)

ENGINYERIA DEL MEDI AMBIENT - 240772

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GRAU EN TECNOLOGIES INDUSTRIALS I ANÀLISI ECONÒMICA (Pla 2018)

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