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.
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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.
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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
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