Skip to main content

Points of Interest in Smart Cities and Visitor Behavior

  • Conference paper
  • First Online:
Intelligent Transport Systems (INTSYS 2023)

Abstract

Smart cities leverage technology and data to enhance the quality of urban life, including the management of points of interest (POIs) and visitor experiences. This paper explores the relationship between POIs and visitor behavior in smart cities, examining the impact of technology-driven solutions on understanding, analyzing, and optimizing visitor experiences. It highlights the importance of data-driven approaches in identifying and managing POIs, enhancing visitor satisfaction, and driving economic growth. The paper reviews existing literature, discusses key concepts, and presents case studies to illustrate the role of POIs in smart cities and their influence on visitor behavior. Our major contribution is a data driven approach to extract useful information from real data to municipality decisions and understand the problem. It concludes with recommendations for future research and practical implications for city planners, policymakers, and tourism authorities.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 79.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Travel & Tourism Economic Impact | World Travel & Tourism Council (WTTC). https://wttc.org/research/economic-impact. Accessed 22 May 2023

  2. LCG. TravelBI by Turismo de Portugal. https://travelbi.turismodeportugal.pt/. Accessed 22 May 2023

  3. Mariani, M., Baggio, R., Fuchs, M., Höepken, W.: Business intelligence and big data in hospitality and tourism: a systematic literature review. Int. J. Contemp. Hosp. Manag. 30(12), 3514–3554 (2018). https://doi.org/10.1108/IJCHM-07-2017-0461

    Article  Google Scholar 

  4. Supak, S., Brothers, G., Bohnenstiehl, D., Devine, H.: Geospatial analytics for federally managed tourism destinations and their demand markets. J. Destin. Mark. Manag. 4(3), 173–186 (2015). https://doi.org/10.1016/j.jdmm.2015.05.002

    Article  Google Scholar 

  5. Mesquitela, J., Elvas, L.B., Ferreira, J.C., Nunes, L.: Data analytics process over road accidents data—a case study of Lisbon city. ISPRS Int. J. Geo-Inf. 11(2), Article no. 2 (2022). https://doi.org/10.3390/ijgi11020143

  6. Elvas, L.B., Gonçalves, S.P., Ferreira, J.C., Madureira, A.: Data fusion and visualization towards city disaster management: Lisbon case study. EAI Endorsed Trans. Smart Cities 6(18), e3–e3 (2022). https://doi.org/10.4108/eetsc.v6i18.1374

    Article  Google Scholar 

  7. Elvas, L.B., Mataloto, B.M., Martins, A.L., Ferreira, J.C.: Disaster management in smart cities. Smart Cities 4(2), Article no. 2 (2021). https://doi.org/10.3390/smartcities4020042

  8. Elvas, L.B., Marreiros, C.F., Dinis, J.M., Pereira, M.C., Martins, A.L., Ferreira, J.C.: Data-driven approach for incident management in a smart city. Appl. Sci. 10(22), Article no. 22 (2020). https://doi.org/10.3390/app10228281

  9. Gil, E., Ahn, Y., Kwon, Y.: Tourist attraction and points of interest (POIs) using search engine data: case of Seoul. Sustainability 12(17), Article no. 17 (2020). https://doi.org/10.3390/su12177060

  10. Spangenberg, T.: Standardization, modeling and implementation of points of interest – a touristic perspective. Int. J. U- E- Serv. Sci. Technol. 6, 59–70 (2013). https://doi.org/10.14257/ijunesst.2013.6.6.07

    Article  Google Scholar 

  11. Zeng, W., Fu, C.-W., Müller Arisona, S., Schubiger, S., Burkhard, R., Ma, K.-L.: Visualizing the relationship between human mobility and points of interest. IEEE Trans. Intell. Transp. Syst. 18(8), 2271–2284 (2017). https://doi.org/10.1109/TITS.2016.2639320

  12. Zhang, Y.: User mobility from the view of cellular data networks. In: IEEE Conference on Computer Communications, IEEE INFOCOM 2014, pp. 1348–1356 (2014). https://doi.org/10.1109/INFOCOM.2014.6848068

  13. Wu, T., Rustamov, R.M., Goodall, C.: Distributed learning of human mobility patterns from cellular network data. In: 2017 51st Annual Conference on Information Sciences and Systems (CISS), pp. 1–6 (2017). https://doi.org/10.1109/CISS.2017.7926085

  14. Shafiee, S., Ghatari, A.R.: Big data in tourism industry. In: 2016 10th International Conference on e-Commerce in Developing Countries: with focus on e-Tourism (ECDC), pp. 1–7 (2016). https://doi.org/10.1109/ECDC.2016.7492979

  15. Suakanto, S., Andreswari, R., Albasori, E.P.: SEMPIR: sequence multiple point of interest recommender system for overland tourism. In: 2021 International Conference on ICT for Smart Society (ICISS), pp. 1–7 (2021). https://doi.org/10.1109/ICISS53185.2021.9533194

  16. Ajantha, D., Vijay, J., Sridhar, R.: A user-location vector based approach for personalised tourism and travel recommendation. In: 2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), pp. 440–446 (2017). https://doi.org/10.1109/ICBDACI.2017.8070880

  17. Giglio, S., Bertacchini, F., Bilotta, E., Pantano, P.: Machine learning and points of interest: typical tourist Italian cities. Curr. Issues Tour. 23(13), 1646–1658 (2020). https://doi.org/10.1080/13683500.2019.1637827

    Article  Google Scholar 

  18. Wirth, R., Hipp, J.: CRISP-DM: towards a standard process model for data mining. In: Proceedings of the 4th International Conference on the Practical Applications of Knowledge Discovery and Data Mining (2000)

    Google Scholar 

  19. Prophet. http://facebook.github.io/prophet/. Accessed 22 May 2023

  20. Current Local Time in Lisbon, Portugal (Lisboa). Consultado em 10 de abril de 20223. Disponível em https://www.timeanddate.com/worldclock/portugal/lisbon

  21. Vodafone Portugal alvo de ciberataque. Press Release, 8 de fevereiro de 2022. Consultado em 03 de maio de 2023 (2022). Disponível em https://www.vodafone.pt/press-releases/2022/2/vodafone-portugal-alvo-de-ciberataque.html

  22. 10 things to do and see in Lisbon. Visit Portugal. Consultado em 01 de abril de 2023. Disponível em https://www.visitportugal.com/en/destinos/lisboa-regiao/73773

  23. Visit Lisboa. Turismo de Lisboa. Consultado em 01 de abril de 2023. Disponível em https://www.visitlisboa.com/pt-pt

  24. O que visitar em Lisboa. O Guia da Cidade. Consultado em 01 de abril de 2023. Disponível em https://www.guiadacidade.pt/pt/discover-pois-lisboa-11

  25. Indicadores TOP 100 - Registos de Património + Vistos. Direção Geral do Património Cultural. Consultado em 01 de abril de 2023. Disponível em http://www.monumentos.gov.pt/site/APP_PagesUser/SIPATop100.aspx?it=1

  26. Lisbon Portugal Guide. LisbonLisboaPortugal.com. Consultado em 01 de abril de 2023. Disponível em https://lisbonlisboaportugal.com/index.html

  27. Lisbon Travel Guide. Civitatis Lisbon. Consultado em 01 de abril de 2023. Disponível em https://www.lisbon.net/

  28. Past Weather in Lisbon, Portugal. Consultado em 12 de março de 2023. Disponível em https://www.timeanddate.com/weather/portugal/lisbon/historic?month=12&year=2021

  29. Europa sem fronteiras: O Espaço Schengen. Publicação da Comissão Europeia – Migração e Assuntos Internos. Consultado em 13 de abril de 2023 em (2019). https://doi.org/10.2837/71557, https://home-affairs.ec.europa.eu/system/files_en?file=2020-09

Download references

Acknowledgment

We thank the Lisbon City Council for providing us with the data necessary for this study, namely Mr. António Costa (Lisbon City Council), Mrs. Helena Martins (Lisbon City Council) and Mrs. Paula Melicias (Lisbon City Council). We also thank IPMA for providing us with the data necessary to complement our study.

Funding

This work was supported by EEA Grants Blue Growth Programme (Call #5). Project PT-INNOVATION-0069 – Fish2Fork. This research also received funding from ERAMUS+ project NEMM with grant 101083048.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joao Carlos Ferreira .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Elvas, L.B., Nunes, M., Francisco, B., Gonçalves, F., Martins, A.L., Ferreira, J.C. (2024). Points of Interest in Smart Cities and Visitor Behavior. In: Martins, A.L., Ferreira, J.C., Kocian, A., Tokkozhina, U., Helgheim, B.I., Bråthen, S. (eds) Intelligent Transport Systems. INTSYS 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 540. Springer, Cham. https://doi.org/10.1007/978-3-031-49379-9_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-49379-9_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-49378-2

  • Online ISBN: 978-3-031-49379-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics