Abstract
In the last few years, the Emilia-Romagna region, in Italy, has seen a significant growth in the tourism economy, due to an increasing number of Italian and foreigner visitors. This has highlighted the need of a strong synergy between tourist facilities and local administrations. In this context, Smart City solutions and Machine Learning (ML) can play an important role to analyse the amount of data generated in this sector. This paper presents part of the work done within the ongoing POLIS-EYE project, targeted at the development of a Policy Support System (PSS) and related intelligent services for an optimized management of the Smart City in the specific domain of tourism in this region. Several results obtained from the application of supervised and unsupervised ML techniques show the effectiveness in the prediction of the tourist flow in different scenarios, e.g., towards regional museums and big events. The integration of these results in the PSS architecture will allow a smart management of the territory on behalf of the administration and will be replicable outside the region.
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Notes
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Data have been provided by private Italian companies and cannot be published.
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Acknowledgments
This research was funded by the Fondo di Sviluppo e Coesione (FSC) of Regione Emilia-Romagna within the context of the POR FESR 2014-2020 ASSE 1 AZIONE 1.2.2 (CUP E21F18000200007) project “POLIcy Support systEm for smart citY data governancE (POLIS-EYE)”.
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Bellodi, E., Zese, R., Bertasi, F. (2022). Machine Learning in a Policy Support System for Smart Tourism Management. In: Nicosia, G., et al. Machine Learning, Optimization, and Data Science. LOD 2021. Lecture Notes in Computer Science(), vol 13163. Springer, Cham. https://doi.org/10.1007/978-3-030-95467-3_33
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