Abstract
Given their ubiquity and sensing capabilities, current smartphones have been used to explore different real-life tracking and monitoring scenarios. Particularly, in the domain of Intelligent Transportation Systems (ITS), the exact orientation of the smartphone must be known to gain full advantage of the data provided by its internal accelerometers. From here, rich contextual information could be inferred. Nonetheless, in real-life scenarios, smartphones are freely placed within vehicles, so a reorientation strategy needs to be applied. The usage of several algorithms to reorient acceleration readings has been mentioned for ITS applications, but very little evaluation of their efficacy has been performed. In this work, we study the effectiveness of four algorithms for vertical reorientation, and two for triaxial reorientation of acceleration readings. Results suggest that all methods for the vertical case are equivalent, however, in the case where triaxial reorientation is needed, current strategies are far from acceptable results. We expect these findings could promote further research to alleviate these issues.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
An azimuth is a horizontal angle measured from a north base line.
- 3.
The equations used in our experiments are summarized in http://accelerometer.xyz/reorientations/equations.pdf.
- 4.
As \(Z_i=(z_i-\overline{z})/s_z\), where \(z_i\) represents the \(i^{th}\) datapoint in the time series of axis Z, \(\overline{z}\) is the mean, and \(s_z\) is the standard deviation on the same axis.
- 5.
Some of the series are not visible because their values are very similar, and only one line is displayed.
- 6.
In their article, the authors use a different convention for axes. Their X axis corresponds to our Y, and vice versa.
References
Figo, D., Diniz, P.C., Ferreira, D.R., Cardoso, J.M.P.: Preprocessing techniques for context recognition from accelerometer data. Pers. Ubiquit. Comput. 14(7), 645–662 (2010)
Engelbrecht, J., Booysen, M.J., van Rooyen, G.-J., Bruwer, F.J.: Survey of smartphone-based sensing in vehicles for intelligent transportation system applications. IET Intell. Transp. Syst. 9(10), 924–935 (2015)
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 - SenSys 2008, pp. 323–336. ACM Press (2008)
Astarita, V., Caruso, M.V., Danieli, G., Festa, D.C., Giofrè, V.P., Iuele, T., Vaiana, R.: A mobile application for road surface quality control: UNIquALroad. Procedia Soc. Behav. Sci. 54, 1135–1144 (2012)
Jain, M., Singh, A.P., Bali, S., Kaul, S.: Speed-breaker early warning system. In: Proceedings of the 6th USENIX/ACM Workshop on Networked Systems for Developing Regions (2012)
Tundo, M.D., Lemaire, E., Baddour, N.: Correcting smartphone orientation for accelerometer-based analysis. In: 2013 IEEE International Symposium on Medical Measurements and Applications (MeMeA), pp. 58–62. IEEE, May 2013
Promwongsa, N., Chaisatsilp, P., Supakwong, S.: Automatic accelerometer reorientation for driving event detection using smartphone. In: 13th ITS Asia Pacific Forum, Auckland, New Zealand (2014)
Eriksson, J., Girod, L., Hull, B., Newton, R., Madden, S., Balakrishnan, H.: The pothole patrol: using a mobile sensor network for road surface monitoring. In: Proceeding of the 6th International Conference on Mobile Systems, Applications, and Services - MobiSys 2008, pp. 29–39. ACM Press (2008)
Fazeen, M., Gozick, B., Dantu, R., Bhukhiya, M., González, M.C.: Safe driving using mobile phones. IEEE Trans. Intell. Trans. Syst. 13(3), 1462–1468 (2012)
Douangphachanh, V., Oneyama, H.: A study on the use of smartphones for road roughness condition estimation. In: Proceedings of the Eastern Asia Society for Transportation Studies (10), 1551–1564 (2013)
González, L.C., Martínez, F., Carlos, M.R.: Identifying roadway surface disruptions based on accelerometer patterns. Latin Am. Trans. IEEE (Revista IEEE America Latina) 12(3), 455–461 (2014)
Goldstein, H., Poole, C.P., Safko, J.L.: Classical Mechanics, 3rd edn. Addison Wesley, Boston (2001)
Kuipers, J.B.: Quaternions and Rotation Sequences: A Primer with Applications to Orbits, Aerospace and Virtual Reality. Princeton University Press, Princeton (1999)
Ozyagcilar, T.: Implementing a Tilt-Compensated eCompass using Accelerometer and Magnetometer Sensors. Freescale Semiconductor (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Carlos, M.R., González, L.C., Martínez, F., Cornejo, R. (2016). Evaluating Reorientation Strategies for Accelerometer Data from Smartphones for ITS Applications. In: García, C., Caballero-Gil, P., Burmester, M., Quesada-Arencibia, A. (eds) Ubiquitous Computing and Ambient Intelligence. IWAAL AmIHEALTH UCAmI 2016 2016 2016. Lecture Notes in Computer Science(), vol 10070. Springer, Cham. https://doi.org/10.1007/978-3-319-48799-1_45
Download citation
DOI: https://doi.org/10.1007/978-3-319-48799-1_45
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-48798-4
Online ISBN: 978-3-319-48799-1
eBook Packages: Computer ScienceComputer Science (R0)