Skip to main content

Energy-Efficient GPS Usage in Location-Based Applications

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 701)

Abstract

GPS is one of the most used services in any location-based app in our smartphone, and almost a quarter of all Android apps available in the Google Play store are using this GPS. There are many apps which require monitoring your locations in a continuous fashion because of the application’s nature, and those kinds of apps consume the highest power from the smartphones. Because of the high-power draining nature of this GPS, we hesitate to take part in different crowd-sourced applications which are very much important for the smart city realization as maximum of these applications use GPS in real time or in a very frequent manner for the realization of participatory sensing in a smart city scenario. To resolve this, we have introduced an energy-efficient context-aware approach which utilizes user’s mobility information from the user’s context and as well smartphone’s sensing values from the inbuilt accelerometer, magnetometer, and gyroscope of the smartphone to provide us a very close estimation of the present location of the user without using continuous GPS. It is an energy-efficient solution without sacrificing the accuracy compared to energy saving which will boost the crowd to take part in the smartphone-based crowd-sourced applications that depend on participatory sensing for the smart city environment.

Keywords

  • Energy efficient
  • GPS
  • Location estimation
  • Sensor fusion
  • Smart city

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-981-10-7563-6_36
  • Chapter length: 9 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   299.00
Price excludes VAT (USA)
  • ISBN: 978-981-10-7563-6
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   379.99
Price excludes VAT (USA)
Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. Abdesslem, F.B., Phillips, A., Henderson T.: Less is more: energy-efficient mobile sensing with senseless. In Proceedings of the 1st ACM workshop on Networking, Systems, and Applications for Mobile Handhelds (2009)

    Google Scholar 

  2. Singhal, T., Harit, A., Vishwakarma, D.N.: Kalman filter implementation on an accelerometer sensor data for three state estimation of a dynamic system. Int. J. Res. Eng. Technol. (2012)

    Google Scholar 

  3. Muthohar, M.F., Nugraha, I.G.D., Choi, D.: Exploring significant motion sensor for energy-efficient continuous motion and location sampling in mobile sensing application. Int. J. Technol. 38–49 (2016)

    CrossRef  Google Scholar 

  4. Kjærgaard, M.B., Langdal, J., Godsk, T., Toftkjær, T.: Entracked: energy-efficient robust position tracking for mobile devices. In: Proceedings of the 7th International Conference on Mobile Systems, Applications, and Services. ACM. New York. USA (2009) 221–234

    Google Scholar 

  5. Paek, J., Kim, J., Govindan, R.: Energy-efficient rate-adaptive GPS-based positioning for smartphones. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services. ACM. New York. USA (2010) 299–314

    Google Scholar 

  6. Dutta, J., Gazi, F., Roy, S., Chowdhury, C.: AirSense: opportunistic crowd-sensing based air quality monitoring system for smart city. In: Proceedings of IEEE Sensors. Orlando, FL, USA (2016) https://doi.org/10.1109/icsens.2016.7808730

  7. Dutta, J., Chowdhury, C., Roy, S., Middya, A.I., Gazi, F.: Towards smart city: sensing air quality in city based on opportunistic crowd-sensing. In: Proceedings of the 18th International Conference on Distributed Computing and Networking. Hyderabad, India. ACM. (2017) https://doi.org/10.1145/3007748.3018286

  8. Dutta, J., Roy, S.: IoT-fog-cloud based architecture for smart city: prototype of a smart building. In: Proceedings of 7th International Conference on Cloud Computing, Data Science & Engineering. Noida, India, pp. 237–242 (2017). https://doi.org/10.1109/confluence.2017.7943156

  9. Liu, J., et al.: CO-GPS: energy efficient GPS sensing with cloud offloading. IEEE Trans. Mob. Comput. 15(6), 1348–1361 (2016). https://doi.org/10.1109/TMC.2015.2446461

    CrossRef  Google Scholar 

  10. Taylor, I. M., Labrador, M. A.: Improving the energy consumption in mobile phones by filtering noisy GPS fixes with modified Kalman filters. IEEE Wireless Communications and Networking Conference, Cancun, Quintana Roo, Mexico 2006–2011. (2011). https://doi.org/10.1109/wcnc.2011.5779437

  11. Khaleghi, B., El-Ghazal, A., Hilal, A. R., Toonstra, J., Miners, W. B., Basir O. A.: Opportunistic calibration of smartphone orientation in a vehicle. In: IEEE 16th International Symposium on a World of Wireless, Mobile and Multimedia Networks. Boston, MA, USA (2015). https://doi.org/10.1109/wowmom.2015.7158210

  12. Abyarjoo, F. et al.: Implementing a sensor fusion algorithm for 3D orientation detection with inertial/magnetic sensors. Innovations and Advances in Computing, Informatics, Systems Sciences, Networking and Engineering. Springer. Cham pp. 305–310 (2015)

    Google Scholar 

Download references

Acknowledgements

The research work of the first author is funded by “Visvesvaraya PhD Scheme, Ministry of Communications & IT, Government of India”.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joy Dutta .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Dutta, J., Pramanick, P., Roy, S. (2018). Energy-Efficient GPS Usage in Location-Based Applications. In: Satapathy, S., Tavares, J., Bhateja, V., Mohanty, J. (eds) Information and Decision Sciences. Advances in Intelligent Systems and Computing, vol 701. Springer, Singapore. https://doi.org/10.1007/978-981-10-7563-6_36

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7563-6_36

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7562-9

  • Online ISBN: 978-981-10-7563-6

  • eBook Packages: EngineeringEngineering (R0)