Human-Computer Cloud for Smart Cities: Tourist Itinerary Planning Case Study

  • Alexander Smirnov
  • Andrew Ponomarev
  • Nikolay TeslyaEmail author
  • Nikolay Shilov
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 303)


The development of smart cities provides a lot of data and services that can be utilized to improve the tourists’ experience during the trip. Information technologies affect directly the development of tourism industry. Tourists and cities’ inhabitants take an active part in the production of tourism products, as well as in sharing their knowledge and experience. To help them in this activity and provide an interface to communicate with other people and computer resources the human-computer cloud concept has been viewed. The paper proposes a workflow that uses computer and human processing units for tourist’s itinerary planning. The workflow integrates data analysis from various sources with computer and human-based calculation of itineraries in the cloud system. The case is implemented based on the smart destination services of St. Petersburg, Russia.


Cloud Human Computer GIS Smartness Itinerary Big data 



The research is funded by the Russian Science Foundation (Project # 16-11-10253).


  1. 1.
  2. 2.
    Buhalis, D.: ETourism: Information Technology for Strategic Tourism Management. Financial Times Prentice Hall, Harlow (2003)Google Scholar
  3. 3.
    Gretzel, U., Reino, S., Kopera, S., Koo, C.: Smart tourism challenges. J. Tour. 16, 41–47 (2015)Google Scholar
  4. 4.
    Khan, Z., Anjum, A., Soomro, K., Tahir, M.A.: Towards cloud based big data analytics for smart future cities. J. Cloud Comput. 4, 1–11 (2015)CrossRefGoogle Scholar
  5. 5.
    Smirnov, A., Ponomarev, A.: Crowd computing framework for geoinformation tasks. In: Popovich, V., Claramunt, C., Schrenk, M., Korolenko, K., Gensel, J. (eds.) Information Fusion and Geographic Information Systems (IF&GIS’ 2015). LNGC. Springer, Cham (2015). doi: 10.1007/978-3-319-16667-4_7 Google Scholar
  6. 6.
    Adla, A., Nachet, B., Ould-Mahraz, A.: Multi-agents model for web-based collaborative decision support systems. In: CEUR Workshop Proceedings, pp. 294–299 (2012)Google Scholar
  7. 7.
    Gowri, S., Vigneshwari, S., Sathiyavathi, R., Kalai Lakshmi, T.R.: A framework for group decision support system using cloud database for broadcasting earthquake occurrences. In: Proceedings of the International Congress on Information and Communication Technology, pp. 611–615 (2016)Google Scholar
  8. 8.
    Sun, X., Cai, C., Shen, X.: A new cloud model based human-machine cooperative path planning method. J. Intell. Robot. Syst. 79, 3–19 (2015)CrossRefGoogle Scholar
  9. 9.
    Distefano, S., Merlino, G., Puliafito, A.: SAaaS: a framework for volunteer-based sensing clouds. Parallel Cloud Comput. 1(2), 21–33 (2012). Google Scholar
  10. 10.
    Merlino, G., Arkoulis, S., Distefano, S., Papagianni, C., Puliafito, A., Papavassiliou, S.: Mobile crowdsensing as a service: a platform for applications on top of sensing Clouds. Future Gener. Comput. Syst. 56, 623–639 (2016)CrossRefGoogle Scholar
  11. 11.
    Formisano, C., Pavia, D., Gurgen, L., Yonezawa, T., Galache, J.A., Doguchi, K., Matranga, I.: The advantages of IoT and cloud applied to smart cities. In: 2015 3rd International Conference on Future Internet of Things and Cloud, pp. 325–332. IEEE (2015)Google Scholar
  12. 12.
    Dustdar, S., Bhattacharya, K.: The social compute unit. IEEE Internet Comput. 15, 64–69 (2011)CrossRefGoogle Scholar
  13. 13.
    Sengupta, B., Jain, A., Bhattacharya, K., Truong, H.-L., Dustar, S.: Collective problem solving using social compute units. Int. J. Coop. Inf. Syst. 22, 1–21 (2013)CrossRefGoogle Scholar
  14. 14.
    Mavridis, N., Bourlai, T., Ognibene, D.: The human-robot cloud: situated collective intelligence on demand. In: 2012 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER), pp. 360–365. IEEE (2012)Google Scholar
  15. 15.
    Mavridis, N., Konstantopoulos, S., Vetsikas, I., Heldal, I., Karampiperis, P., Mathiason, G., Thill, S., Stathis, K., Karkaletsis, V.: CLIC: A Framework for Distributed, On-Demand, Human-Machine Cognitive Systems. arXiv:1312.2242 (2013)
  16. 16.
    Mavridis, N., Pierris, G., Benabdelkader, C., Krstikj, A., Karaiskos, C.: Smart buildings and the human-machine cloud. In: 2015 IEEE 8th GCC Conference and Exhibition, GCCCE 2015, pp. 1–6. IEEE (2015)Google Scholar
  17. 17.
    Smirnov, A., Ponomarev, A., Levashova, T., Teslya, N.: Human-computer cloud for decision support in tourism: approach and architecture. In: Balandin, S., Tyutina, T. (eds.) Proceedings of the FRUCT 19. pp. 226–235, Jyvaskyla, Finland (2016)Google Scholar
  18. 18.
    Scekic, O., Truong, H.-L., Dustdar, S.: Incentives and rewarding in social computing. Commun. ACM 56, 72 (2013)CrossRefGoogle Scholar
  19. 19.
    Little, G., Chilton, L.B., Goldman, M., Miller, R.C.: Exploring iterative and parallel human computation processes. In: Proceedings of the ACM SIGKDD Workshop on Human Computation - HCOMP 2010, p. 68. ACM Press, New York (2010)Google Scholar
  20. 20.
    Gretzel, U., Werthner, H., Koo, C., Lamsfus, C.: Conceptual foundations for understanding smart tourism ecosystems. Comput. Hum. Behav. 50, 558–563 (2015)CrossRefGoogle Scholar
  21. 21.
    Castelein, W., Grus, L., Crompvoe, J., Bregt, A.: A characterization of volunteered geographic information. In: 13th AGILE International Conference on Geographic Information Science, pp. 1–10 (2010)Google Scholar
  22. 22.
    Mashhadi, A., Quattrone, G., Capra, L.: The impact of society on volunteered geographic information: the case of OpenStreetMap. In: Jokar Arsanjani, J., Zipf, A., Mooney, P., Helbich, M. (eds.) OpenStreetMap in GIScience. LNGC, pp. 125–141. Springer International Publishing, Cham (2015). doi: 10.1007/978-3-319-14280-7_7 Google Scholar
  23. 23.
    Coleman, D.J., Georgiadou, Y., Labonte, J., Observation, E., Canada, N.R.: Volunteered geographic information: the nature and motivation of produsers. Int. J. Spat. Data Infrastruct. Res. 4, 332–358 (2009)Google Scholar
  24. 24.
    Seigerroth, U., Kaidalova, J., Shilov, N., Kaczmarek, T.: Semantic web technologies in business and IT alignment: multi-model algorithm of ontology matching. In: Fifth International Conference on Advances in Future Internet, pp. 50–56 (2013)Google Scholar
  25. 25.
    World’s Leading Cultural City Destination 2016 – World Travel Awards.
  26. 26.
    St. Petersburg Public Transport Portal.
  27. 27.
    Smirnov, A., Kashevnik, A., Shilov, N., Teslya, N., Shabaev, A.: Mobile application for guiding tourist activities: tourist assistant - TAIS. In: Conference of Open Innovation Association, FRUCT, pp. 95–100. IEEE Computer Society (2014)Google Scholar
  28. 28.
    Smirnov, A., Kashevnik, A., Ponomarev, A., Shilov, N., Teslya, N.: Proactive recommendation system for m-tourism application. In: Johansson, B., Andersson, B., Holmberg, N. (eds.) BIR 2014. LNBIP, vol. 194, pp. 113–127. Springer, Cham (2014). doi: 10.1007/978-3-319-11370-8_9 Google Scholar
  29. 29.
    Smirnov, A., Teslya, N., Shilov, N., Kashevnik, A.: Context-based trip planning in infomobility system for public transport. In: Abraham, A., Kovalev, S., Tarassov, V., Snášel, V. (eds.) IITI 2016. AISC, vol. 450, pp. 361–371. Springer, Cham (2016). doi: 10.1007/978-3-319-33609-1_33 Google Scholar
  30. 30.
    Google: GTFS Static Overview.

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Alexander Smirnov
    • 1
  • Andrew Ponomarev
    • 1
  • Nikolay Teslya
    • 1
    Email author
  • Nikolay Shilov
    • 1
  1. 1.SPIIRASSt. PetersburgRussia

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