Skip to main content
SpringerLink
Log in

Mobile Crowdsourcing and Inertial Sensing

  • Chapter
  • First Online:
Wireless Indoor Localization

  • 939 Accesses

Abstract

This chapter presents the preliminary background on mobile crowdsourcing and inertial sensing, which together have opened the new possibilities for wireless indoor localization, after more than a decade of development. In particular, we first introduce the basic concept of mobile crowdsourcing. Then we study how to measure human mobility using smartphone-based inertial sensing, including what types of sensors we can use and what mobility information we can acquire.

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

Access this chapter

Log in via an institution
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
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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.

    http://www.wikipedia.org

References

  1. Afzal, M., Renaudin, V., Lachapelle, G.: Assessment of indoor magnetic field anomalies using multiple magnetometers. In: Proceedings of ION International Technical Meeting of the Satellite Division of the Institute of Navigation (GNSS) (2001)

    Google Scholar 

  2. Agarwal, Y., Hall, M.: ProtectMyPrivacy: detecting and mitigating privacy leaks on iOS devices using crowdsourcing. In: ACM International Conference on Mobile Systems, Applications, and Services (MobiSys) (2013)

    Google Scholar 

  3. Angermann, M., Robertson, P.: FootSLAM: pedestrian simultaneous localization and mapping without exteroceptive sensors hitchhiking on human perception and cognition. Proc. IEEE 100(Special Centennial Issue), 1840–1848 (2012)

    Google Scholar 

  4. Azizyan, M., Constandache, I., Roy Choudhury, R.: SurroundSense: mobile phone localization via ambience fingerprinting. In: ACM International Conference on Mobile Computing and Networking (MobiCom) (2009)

    Google Scholar 

  5. Bao, L., Intille, S.: Activity recognition from user-annotated acceleration data. In: Pervasive Computing. Lecture Notes in Computer Science, vol. 3001, pp. 1–17. Springer, Berlin/Heidelberg (2004)

    Google Scholar 

  6. Barralon, P., Vuillerme, N., Noury, N.: Walk detection with a kinematic sensor: frequency and wavelet comparison. In: Proceedings of IEEE International Conference of Engineering in Medicine and Biology Society (EMBS) (2006)

    Google Scholar 

  7. Bertram, J.E., Ruina, A.: Multiple walking speed–frequency relations are predicted by constrained optimization. Elsevier J. Theor. Biol. 209(4), 445–453 (2001)

    Article  Google Scholar 

  8. Brajdic, A., Harle, R.: Walk detection and step counting on unconstrained smartphones. In: Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp) (2013)

    Google Scholar 

  9. Cho, D.K., Mun, M., Lee, U., Kaiser, W., Gerla, M.: AutoGait: a mobile platform that accurately estimates the distance walked. In: Proceedings of IEEE International Conference on Pervasive Computing and Communications (PerCom) (2010)

    Google Scholar 

  10. Choffnes, D.R., Bustamante, F.E., Ge, Z.: Crowdsourcing service-level network event monitoring. ACM SIGCOMM Comput. Commun. Rev. 40(4) (2010)

    Google Scholar 

  11. Constandache, I., Bao, X., Azizyan, M., Choudhury, R.R.: Did you see bob?: human localization using mobile phones. In: Proceedings of the Sixteenth Annual International Conference on Mobile computing and networking, pp. 149–160. ACM, New York (2010)

    Google Scholar 

  12. Constandache, I., Choudhury, R., Rhee, I.: Towards mobile phone localization without war-driving. In: Proceedings of IEEE International Conference on Computer Communications (INFOCOM) (2010)

    Google Scholar 

  13. Doan, A., Franklin, M.J., Kossmann, D., Kraska, T.: Crowdsourcing applications and platforms: a data management perspective. Proc. VLDB Endow. 4(12), 1508–1509 (2011)

    Google Scholar 

  14. Franklin, M.J., Kossmann, D., Kraska, T., Ramesh, S., Xin, R.: Crowddb: answering queries with crowdsourcing. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data, pp. 61–72. ACM, New York (2011)

    Google Scholar 

  15. Gao, H., Barbier, G., Goolsby, R.: Harnessing the crowdsourcing power of social media for disaster relief. IEEE Intell. Syst. 26(3), 10–14 (2011)

    Article  Google Scholar 

  16. Gao, R., Zhao, M., Ye, T., Ye, F., Wang, Y., Bian, K., Wang, T., Li, X.: Jigsaw: indoor floor plan reconstruction via mobile crowdsensing. In: ACM International Conference on Mobile Computing and Networking (MobiCom) (2014)

    Google Scholar 

  17. Goyal, P., Ribeiro, V., Saran, H., Kumar, A.: Strap-down pedestrian dead-reckoning system. In: Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN) (2011)

    Google Scholar 

  18. Gusenbauer, D., Isert, C., Krosche, J.: Self-contained indoor positioning on off-the-shelf mobile devices. In: Proceedings of International Conference on Indoor Positioning and Indoor Navigation (IPIN) (2010)

    Google Scholar 

  19. Harle, R.: A Survey of indoor inertial positioning systems for pedestrians. IEEE Commun. Surv. Tutorials 15(3), 1281–1293 (2013)

    Article  Google Scholar 

  20. Hemminki, S., Nurmi, P., Tarkoma, S.: Accelerometer-based transportation mode detection on smartphones. In: Proceedings of ACM Conference on Embedded Networked Sensor Systems (SenSys) (2013)

    Google Scholar 

  21. Hoque, M.A., Siekkinen, M., Nurminen, J.K.: Using crowd-sourced viewing statistics to save energy in wireless video streaming. In: ACM International Conference on Mobile Computing and Networking (MobiCom). ACM, New York (2013)

    Google Scholar 

  22. Howe, J.: The rise of crowdsourcing. Wired Mag. 14(6), 1–4 (2006)

    Google Scholar 

  23. Iso, T., Yamazaki, K.: Gait analyzer based on a cell phone with a single three-axis accelerometer. In: Proceedings of ACM Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) (2006)

    Google Scholar 

  24. Jiang, Y., Xiang, Y., Pan, X., Li, K., Lv, Q., Dick, R.P., Shang, L., Hannigan, M.: Hallway based automatic indoor floorplan construction using room fingerprints. In: Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp) (2013)

    Google Scholar 

  25. Jimenez, A., Seco, F., Prieto, C., Guevara, J.: A comparison of pedestrian dead-reckoning algorithms using a low-cost MEMS IMU. In: Proceedings of IEEE International Symposium on Intelligent Signal Processing (WISP) (2009)

    Google Scholar 

  26. Jun, J., Gu, Y., Cheng, L., Lu, B., Sun, J., Zhu, T., Niu, J.: Social-loc: improving indoor localization with social sensing. In: Proceedings of ACM Conference on Embedded Networked Sensor Systems (SenSys) (2013)

    Google Scholar 

  27. Kittur, A., Chi, E.H., Suh, B.: Crowdsourcing user studies with mechanical turk. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 453–456. ACM, New York (2008)

    Google Scholar 

  28. Kobayashi, T., Hasida, K., Otsu, N.: Rotation invariant feature extraction from 3-D acceleration signals. In: Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP) (2011)

    Google Scholar 

  29. Korpela, E., Werthimer, D., Anderson, D., Cobb, J., Leboisky, M.: SETI@home-massively distributed computing for SETI. Comput. Sci. Eng. 3(1), 78–83 (2001)

    Article  Google Scholar 

  30. Koukoumidis, E., Peh, L.S., Martonosi, M.R.: Signalguru: leveraging mobile phones for collaborative traffic signal schedule advisory. In: Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services, pp. 127–140. ACM, New York (2011)

    Google Scholar 

  31. Ladetto, Q.: On foot navigation: continuous step calibration using both complementary recursive prediction and adaptive kalman filtering. In: Proceedings of ION GPS (2000)

    Google Scholar 

  32. Li, F., Zhao, C., Ding, G., Gong, J., Liu, C., Zhao, F.: A reliable and accurate indoor localization method using phone inertial sensors. In: Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp) (2012)

    Google Scholar 

  33. Mannini, A., Sabatini, A.: A hidden Markov model-based technique for Gait segmentation using a foot-mounted gyroscope. In: Proceedings of IEEE International Conference of Engineering in Medicine and Biology Society (EMBS) (2011)

    Google Scholar 

  34. Margaria, R., Margaria, R.: Biomechanics and Energetics of Muscular Exercise. Clarendon Press, Oxford (1976)

    Google Scholar 

  35. Marschollek, M., Goevercin, M., Wolf, K.H., Song, B., Gietzelt, M., Haux, R., Steinhagen-Thiessen, E.: A performance comparison of accelerometry-based step detection algorithms on a large, non-laboratory sample of healthy and mobility-impaired persons. In: Proceedings of IEEE International Conference of Engineering in Medicine and Biology Society (EMBS) (2008)

    Google Scholar 

  36. Miluzzo, E., Lane, N.D., Fodor, K., Peterson, R., Lu, H., Musolesi, M., Eisenman, S.B., Zheng, X., Campbell, A.T.: Sensing meets mobile social networks: the design, implementation and evaluation of the cenceMe application. In: Proceedings of ACM Conference on Embedded Networked Sensor Systems (SenSys) (2008)

    Google Scholar 

  37. Park, J.g., Patel, A., Curtis, D., Teller, S., Ledlie, J.: Online pose classification and walking speed estimation using handheld devices. In: Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp) (2012)

    Google Scholar 

  38. Purohit, A., Sun, Z., Pan, S., Zhang, P.: SugarTrail: indoor navigation in retail environments without surveys and maps. In: Proceedings of IEEE Communications Society Conference on Sensor Mesh and Ad Hoc Communications and Networks (SECON) (2013)

    Google Scholar 

  39. Rai, A., Chintalapudi, K.K., Padmanabhan, V.N., Sen, R.: Zee: zero-effort crowdsourcing for indoor localization. In: Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom) (2012)

    Google Scholar 

  40. Randell, C., Djiallis, C., Muller, H.: Personal position measurement using dead reckoning. In: Proceedings of IEEE International Symposium on Wearable Computers (ISWC) (2003)

    Google Scholar 

  41. Ravi, N., Dandekar, N., Mysore, P., Littman, M.L.: Activity recognition from accelerometer data. In: Proceedings of AAAI Conference on Innovative Applications of Artificial Intelligence (IAAI) (2005)

    Google Scholar 

  42. Rong, L., Zhiguo, D., Jianzhong, Z., Ming, L.: Identification of individual walking patterns using gait acceleration. In: Proceedings of International Conference on Bioinformatics and Biomedical Engineering (ICBBE) (2007)

    Google Scholar 

  43. Roy, N., Wang, H., Roy Choudhury, R.: I am a smartphone and i can tell my user’s walking direction. In: Proceedings of the 12th Annual International Conference on Mobile Systems, Applications, and Services, pp. 329–342. ACM, New York (2014)

    Google Scholar 

  44. Sen, S., Lee, J., Kim, K.H., Congdon, P.: Back to the basics: avoiding multipath to revive inbuilding WiFi localization. In: Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys) (2013)

    Google Scholar 

  45. Shen, G., Chen, Z., Zhang, P., Moscibroda, T., Zhang, Y.: Walkie-Markie: indoor pathway mapping made easy. In: Proceedings of USENIX Conference on Networked Systems Design and Implementation (NSDI) (2013)

    Google Scholar 

  46. Siirtola, P., Roning, J.: Recognizing human activities user-independently on smartphones based on accelerometer data. Int. J. Interact. Multimed. Artif. Intell. 1(5), 38–45 (2012)

    Google Scholar 

  47. Simoens, P., Xiao, Y., Pillai, P., Chen, Z., Ha, K., Satyanarayanan, M.: Scalable crowd-sourcing of video from mobile devices. In: ACM International Conference on Mobile Systems, Applications, and Services (MobiSys) (2013)

    Google Scholar 

  48. Sun, W., Liu, J., Wu, C., Yang, Z., Zhang, X., Liu, Y.: MoLoc: on distinguishing fingerprint twins. In: Proceedings of IEEE International Conference on Distributed Computing Systems (ICDCS) (2013)

    Google Scholar 

  49. Sun, Z., Pan, S., Su, Y.C., Zhang, P.: Headio: zero-configured heading acquisition for indoor mobile devices through multimodal context sensing. In: Proceedings of ACM International Conference on Ubiquitous Computing (UbiComp) (2013)

    Google Scholar 

  50. Sun, Z., Pan, S., Su, Y.C., Zhang, P.: Headio: zero-configured heading acquisition for indoor mobile devices through multimodal context sensing. In: Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 33–42. ACM, New York (2013)

    Google Scholar 

  51. von Ahn, L., Maurer, B., McMillen, C., Abraham, D., Blum, M.: reCAPTCHA: human-based character recognition via web security measures. Science 321(5895), 1465–1468 (2008)

    Google Scholar 

  52. Wang, H., Sen, S., Elgohary, A., Farid, M., Youssef, M., Choudhury, R.R.: No need to war-drive: unsupervised indoor localization. In: Proceedings of ACM International Conference on Mobile Systems, Applications, and Services (MobiSys) (2012)

    Google Scholar 

  53. Wang, J.H., Ding, J.J., Chen, Y., Chen, H.H.: Real time accelerometer-based gait recognition using adaptive windowed wavelet transforms. In: Proceedings of IEEE Asia Pacific Conference on Circuits and Systems (APCCAS) (2012)

    Google Scholar 

  54. Wang, H., Wang, Z., Shen, G., Li, F., Han, S., Zhao, F.: WheelLoc: enabling continuous location service on mobile phone for outdoor scenarios. In: Proceedings of IEEE International Conference on Computer Communications (INFOCOM) (2013)

    Google Scholar 

  55. Wang, Y., Liu, X., Wei, H., Forman, G., Chen, C., Zhu, Y.: CrowdAtlas: self-updating maps for cloud and personal use. In: ACM International Conference on Mobile Systems, Applications, and Services (MobiSys) (2013)

    Google Scholar 

  56. Weinberg, H.: Using the ADXL202 in pedometer and personal navigation applications. Analog Devices AN-602 Application Note (2002)

    Google Scholar 

  57. Wikipedia: http://en.wikipedia.org/wiki/Accelerometer (2014)

  58. Wikipedia: http://en.wikipedia.org/wiki/Gyroscope (2014)

  59. Wikipedia: http://en.wikipedia.org/wiki/Magnetometer (2014)

  60. Wu, C., Yang, Z., Liu, Y., Xi, W.: WILL: wireless indoor localization without site survey. IEEE Trans. Parallel Distrib. Syst. 24(4), 839–848 (2013)

    Article  Google Scholar 

  61. Wu, C., Yang, Z., Zhao, Y., Liu, Y.: Footprints elicit the truth: improving global positioning accuracy via local mobility. In: Proceedings of IEEE International Conference on Computer Communications (INFOCOM) (2013)

    Google Scholar 

  62. Yan, B., Chen, G.: Appjoy: personalized mobile application discovery. In: Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services, pp. 113–126. ACM, New York (2011)

    Google Scholar 

  63. Yang, D., Xue, G., Fang, X., Tang, J.: Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing. In: ACM International Conference on Mobile Computing and Networking (MobiCom) (2012)

    Google Scholar 

  64. Yang, Z., Wu, C., Liu, Y.: Locating in fingerprint space: wireless indoor localization with little human intervention. In: Proceedings of ACM International Conference on Mobile Computing and Networking (MobiCom) (2012)

    Google Scholar 

  65. Youssef, M., Yosef, M., El-Derini, M.: GAC: energy-efficient hybrid GPS-accelerometer-compass GSM localization. In: Proceedings of IEEE Global Telecommunications Conference (GLOBECOM) (2010)

    Google Scholar 

  66. Zatsiorsky, V.M.: Kinematics of Human Motion. Human Kinetics, Champaign/Leeds (1998)

    Google Scholar 

  67. Zhang, X., Yang, Z., Sun, W., Liu, Y., Tang, S., Xing, K., Mao, X.: Incentives for mobile crowd sensing: a survey. IEEE Commun. Surv. Tutorials 18(1), 54–67 (2016)

    Article  Google Scholar 

  68. Zhao, Y., Zhang, Y., Yu, T., Liu, T., Wang, X., Tian, X., Liu, X.: Citydrive: a map-generating and speed-optimizing driving system. In: IEEE International Conference on Computer Communications (INFOCOM) (2014)

    Google Scholar 

  69. Zhou, P., Zheng, Y., Li, M.: How long to wait?: predicting bus arrival time with mobile phone based participatory sensing. In: ACM International Conference on Mobile Systems, Applications, and Services (MobiSys), pp. 379–392 (2012)

    Google Scholar 

  70. Zhu, X., Li, Q., Chen, G.: APT: accurate outdoor pedestrian tracking with smartphones. In: Proceedings of IEEE International Conference on Computer Communications (INFOCOM) (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Maryland, College Park, Maryland, USA

    Chenshu Wu

  2. School of Software, Tsinghua University, Beijing, China

    Zheng Yang & Yunhao Liu

Authors
  1. Chenshu Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zheng Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yunhao Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Wu, C., Yang, Z., Liu, Y. (2018). Mobile Crowdsourcing and Inertial Sensing. In: Wireless Indoor Localization. Springer, Singapore. https://doi.org/10.1007/978-981-13-0356-2_2

Download citation

  • DOI: https://doi.org/10.1007/978-981-13-0356-2_2

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0355-5

  • Online ISBN: 978-981-13-0356-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation