This article is published in the Case Study category.

Big Data and Weather: The Impact on Touristic Destinations

Crowd Analytics and Weather Data: scatter chart showing the correlation between the number of visitors from January to March 2018 and the temperature, during weekdays (1) and weekends (2).

Over the entire winter, the data analysis, from January to March 2018, showed that the temperature had an impact on the decision to have a walk on the touristic bridge. The results prove that people’s behaviour is different from weekends and weekdays, considering additional factors like work and free time as drivers in the decision-making process. On top of that, warmer temperatures seem to invite people on Seoullo Bridge, increasing the crowd of 50% on average (55% over weekends, 45% over weekdays).

Based on these results, predictions could be built in order to provide tourism businesses such as festival organisers with detailed weather/crowd predictions.

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PrOFT – Profit Optimization for Tourists Destination

As part of EUROSTARSPrOFT project, correlations are being made between Crowd Analytics and other external sources of data (such as weather data, BLE, NFC, biometrics data…), allowing to develop a prediction engine for the tourism industry. Also, PrOFT’s partners are heading to the stage of finding out how weather affects customers’ and tourists’ buying patterns. The first version of an analysis platform is expected to be released by July 2018.

 

Led by the Korean R&D SME, KNL Information Systems, PrOFT’s consortium is composed of four other partners: DFRC (R&D SME), HES-SO Valais/Wallis – Institute of Tourism of University of Applied Sciences Western Switzerland (University), SWU / SMIACF Sookmyung Women’s University Industry Academic Cooperation Foundation (University) and Unisem Co., Ltd (Large Company).

Interested in knowing more about PrOFT? Contact us.

DFRC

Data team

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