Skip to main content
Log in

A context-aware mobile application framework using audio watermarking

  • Regular Paper
  • Published:
Multimedia Systems Aims and scope Submit manuscript

Abstract

In this paper, we propose a proximity-based indoor positioning system which is capable of monitoring mobile device user’s indoor locations where the commonly used GPS signal is unavailable or weak. The designed system is aimed to be integrated into a context-aware communications system to prevent transmission of irrelevant content to all users but easing delivery of the location-based information. Similar to the beacon technology that assigns a code to each targeted position in an indoor location, our system labels the locations with audio watermark codes where user’s mobile device monitors and receives the watermarked audio. The proposed encoder performs code-division multiplexing that allows insertion of several location indexes into the same audio file. Watermark embedded through spread spectrum improves robustness to noise and guarantees a satisfactory performance even though the mobile device has a low band microphone. The designed decoder installs synchronization between the mobile device and the watermarked audio emitter in real time, and extracts the embedded watermark code words assigned to specific indoor locations. This invokes the context-aware content delivery module and the delivery is initiated. Position displacements of the mobile users are estimated by the time-of-flight technique and the users moving within the coverage range of the emitters are continuously monitored. Decoding is achieved in real time that enables the mobile users to reach to content delivered from different emitters within their coverage range. Performance tests demonstrate that the developed system enables to estimate the user position within the 7-m distance from the emitter while keeping inaudibility. We reached 2-m spatial resolution in discrimination of different emitters. The proposed framework can be considered as a promising alternative to latest technologies, i.e., Wi-Fi-based fingerprinting systems or beacons.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Yeh, S.P., Talwar, S., Wu, G., Himayat, N., Johnsson, K.: Capacity and coverage enhancement in heterogeneous networks. IEEE Wirel. Commun. 18(3), 32–38 (2011)

    Article  Google Scholar 

  2. Bejuri W., Yaakob W.M., Mohamad M.M., Sapri M.: Ubiquitous positioning: a taxonomy for location determination on mobile navigation system. CoRR, abs/1103.5035 (2011)

  3. Song Z., Jiang G., Huang C.: A survey on indoor positioning technologies. In: Proc. ICTMF Second International Conference, Singapore, 164, 198–206 (2011)

  4. Wendong X., Wei N., Yue K.T.: Integrated Wi-Fi fingreprinting and inertial sensing for indoor positioning. In: Proc. International Conference on Indoor Positioning and Indoor Navigation, Guimarães, Portugal, pp. 1–6 (2011)

  5. Luoh, L.: ZigBee-based intelligent indoor positioning system. Soft Comput. 18(3), 443–456 (2014)

    Article  Google Scholar 

  6. Kaemarungsia, K., Krishnamurthy, P.: Analysis of WLAN’s received signal strength indication for indoor location fingerprinting. Pervasive Mobile Comput. 8, 292–316 (2012)

    Article  Google Scholar 

  7. Li L., Shen G., Zhao C., Moscibroda T., Lin J.H., Zhao F.: Experiencing and handling the diversity in data density and environmental locality in an indoor positioning service. The 20th Annual International Conference on Mobile Computing and Networking (MobiCom2014), Hawaii, USA, pp. 459–470 (2014)

  8. Zhu L., Yang A., Wu D., and Liu L.: Survey of indoor positioning technologies and systems, international conference on life system modeling and simulation, LSMS 2014, and International Conference on intelligent computing for sustainable energy and environment, ICSEE 2014, Shanghai, China, pp. 400–409 (2014)

  9. Yang, Q., Pan, S.J., Zheng, V.W.: Estimating location using Wi-Fi. IEEE Intell. Syst. 23(1), 8–13 (2008)

    Article  Google Scholar 

  10. Chintalapudi K., Iyer A.P., Padmanabhan V. N.: Indoor localization without the pain. In Proc. MOBICOM, Chicago USA, pp. 173–184 (2010)

  11. Dardari, D., Closas, P., Djuri´c, P.M.: Indoor tracking: theory, methods, and technologies. IEEE Trans. Veh. Technol. 64(4), 1263–1278 (2015)

    Article  Google Scholar 

  12. Martin P., Ho B. J., Grupen N., Munoz S., Srivastava M.: Demo abstract: an iBeacon primer for indoor localization. BuildSys ‘14 Proceedings of the 1st ACM Conference on embedded systems for energy-efficient buildings, pp. 190–191 (2014)

  13. Song Z., Jiang G., Huang C.: A survey on indoor positioning technologies. Second International Conference, ICTMF 2011, Singapore, pp. 198–206 (2011)

  14. Deak, G., Curran, K., Condell, J.: A survey of active and passive indoor localization systems. Comput. Commun. 35(16), 1939–1954 (2012)

    Article  Google Scholar 

  15. Filonenko V., Cullen C., Carswell J.: Investigating ultrasonic positioning on mobile phones, International Conference on indoor positioning and indoor navigation (IPIN), Zürich, Switzerland (2010)

  16. Höflinger F., Hoppe J., Zhang R., Ens A., Reindl L., Berg J.W., Schindelhauer C.: Acoustic indoor-localization system for smart phones, 11th International Multi-Conference on systems, signals & devices (SSD), Barcelona, Spain, pp. 1–4 (2014)

  17. Yaslan Y., Gunsel B.: An integrated online audio watermark decoding scheme for broadcast monitoring. Multimed Tools Appl. 40(1), (2008)

    Article  Google Scholar 

  18. Nakashima Y., Tachibana R., Nishimura M., Babaguchi N.: Estimation of recording location using audio watermarking. In Proc. the 8th Workshop on multimedia and security, New York USA, pp 108–113 (2006)

  19. Sertatil, C., Altinkaya, M.A., Raoof, K.: A novel acoustic indoor localization system employing CDMA. Digit Signal Process 22, 506–517 (2012)

    Article  Google Scholar 

  20. Kaneto R., Nakashima Y., Babaguchi N.: Real-time user position estimation in indoor environments using digital watermarking for audio signals. In Proc. of the 20th International Conference on Pattern Recognition (ICPR 2010), Istanbul Turkey, pp 97–100 (2010)

  21. Lopes, C., Haghighat, A., Mandal, A., Givargis, T., Baldi, P.: Localization of off-the-shelf mobile devices using audible sound: architectures, protocols and performance assessment. ACM SIGMOBILE Mob. Comput. Commun. Rev. 10(2), 38–50 (2006)

    Article  Google Scholar 

  22. Liu, K., Liu, X., Li, X.: Guoguo: enabling fine-grained smartphone localization via acoustic anchors. IEEE Trans. Mob. Comput. 15(5), 1144–1156 (2016)

    Article  Google Scholar 

  23. Moutinho, J.N., Araujo, R.E., Freitas, D.: Indoor localization with audible sound-towards practical implementation. Pervasive Mobile Comput. (Elsevier) 29, 1–16 (2016)

    Article  Google Scholar 

  24. Donoho D.L., Johnstone I.M.: Threshold selection for wavelet shrinkage of noisy data. In Proc. of 16th Annual Conf. of the IEEE engineering in medicine and biology society pp. 24–25 (1994)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yusuf Yaslan.

Additional information

Communicated by Q. Tian.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yaslan, Y., Gunsel, B. A context-aware mobile application framework using audio watermarking. Multimedia Systems 26, 323–337 (2020). https://doi.org/10.1007/s00530-019-00646-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00530-019-00646-4

Keywords

Navigation