Page 49 - Smart tourism: A path to more secure and resilient destinations

• Ability to model scenarios based on historical data to consolidate new tourist segments through
better promotion and adequacy of supply.

4.4.4.2 Visitor behaviour and mobility

4�4�4�2�1 Description
Tourism mobility flow analysis to study the seasonal behaviour of segments of the population,
making it possible to analyse the estimated activity in different geographical areas and points of
interest, and to extract behavioural patterns to establish preventive measures to ensure the safety
of the areas and visitors.

4�4�4�2�1 Main characteristics

• Monitoring of anonymized data from
mobile devices and Wi-Fi sensors that allow
obtaining information about places with
more traffic, time spent at points of interest,
peak/valley hours, and so on.

• Travel prediction and simulation of inflow
scenarios based on historical storage.

• Generation of reports to compare results and evaluate seasonality and tourism behaviour at
different intervals (e.g., month, year).

4.4.4.3 Economic impact observatory

4�4�4�3�1 Description

Analysis and monitoring of the consumption
activity of tourists visiting the destination with
anonymized data from the transactions made
by visitors through their debit/credit cards at
the different merchants operating within the
destination.

4�4�4�3�2 Main characteristics
• Cross-analysis of information with data from other systems and services of the destination,
allowing for a much richer and high value-added global vision.

• Estimation of activity by geographic area, origin of visitor, spending, merchant category codes
or average spending, segmenting tourist spending.

Smart tourism: A path to more secure and resilient destinations 39