Skip to main content

Collecting Human Habit Datasets for Smart Spaces Through Gamification and Crowdsourcing

  • Conference paper
  • First Online:
Games and Learning Alliance (GALA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9599))

Included in the following conference series:

  • 2245 Accesses

Abstract

A lot of research in the last years has focused on smart spaces, covering aspects related to ambient intelligence, activity monitoring and mining, etc. All these efforts require datasets to be used for experimental purposes and as benchmarks for novel techniques. Such datasets are today difficult to obtain as, on the one hand, building smart facilities is expensive, requiring considerable costs for maintenance and extension, and, on the other hand, freely available datasets are scarce, not continuously updated and contain a limited set of sensors, thus not allowing the evaluation of algorithms that require the availability of specific categories of sensors. To this aim, we have built a prototype smart virtual environment producing sensor logs on the basis of activities performed by users as if they were really acting in a physical smart space.

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Notes

  1. 1.

    https://wsucasas.wordpress.com.

  2. 2.

    https://unity3d.com/.

  3. 3.

    http://smarthome.ailab.wsu.edu/.

References

  1. Bauckhage, C., Drachen, A., Sifa, R.: Clustering game behavior data. IEEE Trans. on Comput. Intell. AI Game 7(3), 266–278 (2015)

    Article  Google Scholar 

  2. Caruso, M., Ilban, C., Leotta, F., Mecella, M., Vassos, S.: Synthesizing daily life logs through gaming and simulation. In: Proceedings of 2013 ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication, UbiComp 2013 Adjunct, pp. 451–460. ACM, New York (2013)

    Google Scholar 

  3. Cook, D., Crandall, A., Thomas, B., Krishnan, N.: Casas: a smart home in a box. Computer 46(7), 62–69 (2013)

    Article  Google Scholar 

  4. Ester, M., Kriegel, H.-P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: KDD, vol. 96, no. 34, pp. 226–231 (1996)

    Google Scholar 

  5. Helal, A., Mendez-Vazquez, A., Hossain, S.: Specification and synthesis of sensory datasets in pervasive spaces. In: IEEE Symposium on Computers and Communications, pp. 920–925 (2009)

    Google Scholar 

  6. Kamar, E., Horvitz, E.: Incentives for truthful reporting in crowdsourcing. In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, vol. 3, pp. 1329–1330. International Foundation for Autonomous Agents and Multiagent Systems (2012)

    Google Scholar 

  7. Merico, D., Bisiani, R.: An agent-based data-generation tool for situation-aware systems. In: 7th International Conference on Intelligent Environments (2011)

    Google Scholar 

  8. Reinhardt, A., Baumann, P., Burgstahler, D., Hollick, M., Chonov, H., Werner, M., Steinmetz, R.: On the accuracy of appliance identification based on distributed load metering data. In: Proceedings of the 2nd IFIP Conference on Sustainable Internet and ICT for Sustainability (SustainIT), pp. 1–9 (2012)

    Google Scholar 

  9. Tazari, M.-R., Furfari, F., Fides-Valero, Á., Hanke, S., Höftberger, O., Kehagias, D., Mosmondor, M., Wichert, R., Wolf, P.: The universAAL reference model for AAL. In: Handbook of Ambient Assisted Living, vol. 11, pp. 610–625 (2012)

    Google Scholar 

  10. Von Ahn, L.: Games with a purpose. Computer 39(6), 92–94 (2006)

    Article  Google Scholar 

  11. Winkler, W.E.: Overview of Record Linkage, Current Research Directions. Statistical Research Division, US Census Bureau, Washington, D.C. (2006)

    Google Scholar 

  12. Metz, C.E.: Basic principles of ROC analysis. In: Seminars in Nuclear Medicine, vol. 8, pp. 283–298. Elsevier (1978)

    Google Scholar 

Download references

Acknowledgements

This work has been partly supported by the EU project VOICE (621137), the Italian cluster SM&ST - Social Museum and Smart Tourism, and the Italian project NEPTIS.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Francesco Leotta .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Cucari, G., Leotta, F., Mecella, M., Vassos, S. (2016). Collecting Human Habit Datasets for Smart Spaces Through Gamification and Crowdsourcing. In: De Gloria, A., Veltkamp, R. (eds) Games and Learning Alliance. GALA 2015. Lecture Notes in Computer Science(), vol 9599. Springer, Cham. https://doi.org/10.1007/978-3-319-40216-1_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-40216-1_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40215-4

  • Online ISBN: 978-3-319-40216-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics