Skip to main content

Couplable Components for Data Processing in Mobile Sensing Campaigns

  • Conference paper
  • First Online:
Ubiquitous Computing and Ambient Intelligence (UCAmI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10586))

Abstract

In mobile sensing, modern phones allow scientists obtain the information about the participants and their surroundings. At times, obtaining raw sensor data from mobile devices demands their collection through sensing campaigns. Often, processing these data requires data processing components in the mobile device. Some of the data processing components pertain to mathematical functions that can be reused to form other functions. These types of functions are usually crafted at a design stage by the programmers. In this work, we present a novel way in which components can be coupled at the design of the sensing campaign, without the need to redeploy the app. That is, scientists can couple two existing data processing components into a new, high-level component. The results of this paper can facilitate code re-use, code maintenance, and flexibility to a mobile sensing campaign.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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

References

  1. Consolvo, S., et al.: Activity sensing in the wild: a field trial of ubifit garden. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM (2008)

    Google Scholar 

  2. Lane, N.D., et al.: Bewell: sensing sleep, physical activities and social interactions to promote wellbeing. Mob. Netw. Appl. 19(3), 345–359 (2014)

    Article  Google Scholar 

  3. Chen, Z., et al.: Unobtrusive sleep monitoring using smartphones. In: 2013 7th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth). IEEE (2013)

    Google Scholar 

  4. Chittaranjan, G., Blom, J., Gatica-Perez, D.: Who’s who with big-five: analyzing and classifying personality traits with smartphones. In: 2011 15th Annual International Symposium on Wearable Computers (ISWC). IEEE (2011)

    Google Scholar 

  5. Mohan, P., Padmanabhan, V.N., Ramjee, R.: Nericell: rich monitoring of road and traffic conditions using mobile smartphones. In: Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems. ACM (2008)

    Google Scholar 

  6. Campbell, A., et al.: NeuroPhone: brain-mobile phone interface using a wireless EEG headset. In: Proceedings of the Second ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds. ACM (2010)

    Google Scholar 

  7. Miluzzo, E., Wang, T., Campbell, A.T.: EyePhone: activating mobile phones with your eyes. In: Proceedings of the Second ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds. ACM (2010)

    Google Scholar 

  8. Hicks, J., et al.: AndWellness: an open mobile system for activity and experience sampling. In: Wireless Health 2010. ACM (2010)

    Google Scholar 

  9. Froehlich, J., et al.: MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones. In: Proceedings of the 5th International Conference on Mobile Systems, Applications and Services. ACM (2007)

    Google Scholar 

  10. Xue, Q.L., et al.: Life-space constriction, development of frailty, and the competing risk of mortality: the Women’s Health and Aging Study I. Am. J. Epidemiol. 167, 240–248 (2008)

    Article  Google Scholar 

  11. Ferreira, D., Kostakos, V., Dey, A.K.: AWARE: mobile context instrumentation framework. Front. ICT 2, 6 (2015)

    Article  Google Scholar 

  12. Castro, L.A., et al.: Behavioral data gathering for assessing functional status and health in older adults using mobile phones. Pers. Ubiquit. Comput. 19(2), 379–391 (2015)

    Article  Google Scholar 

  13. Félix, I.R., Castro, L.A., Rodríguez, L.F., Ruíz, E.C.: Component-based model for on-device pre-processing in mobile phone sensing campaigns. In: García, C., Caballero-Gil, P., Burmester, M., Quesada-Arencibia, A. (eds.) Ubiquitous Computing and Ambient Intelligence. UCAmI 2016. LNCS, vol. 10069. Springer, Cham (2016). doi:10.1007/978-3-319-48746-5_20

    Google Scholar 

Download references

Acknowledgements

This work was partially funded by the Instituto Tecnológico de Sonora through grant #PROFAPI_2016_0041.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Luis A. Castro .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Maya-Zapata, D., Félix, I.R., Castro, L.A., Rodríguez, LF., Domitsu, M. (2017). Couplable Components for Data Processing in Mobile Sensing Campaigns. In: Ochoa, S., Singh, P., Bravo, J. (eds) Ubiquitous Computing and Ambient Intelligence. UCAmI 2017. Lecture Notes in Computer Science(), vol 10586. Springer, Cham. https://doi.org/10.1007/978-3-319-67585-5_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67585-5_31

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67584-8

  • Online ISBN: 978-3-319-67585-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics