University of Helsinki researchers have demonstrated how smartphone accelerometers can be used to distinguish between different motorized transportation modalities.
The researchers say their method has more than 80 percent accuracy in detecting the most common public transportation types. They note the key is to develop characteristic acceleration and breaking patterns and to use these as a signature to differentiate between vehicular transportation modes.
"Extracting vehicular movement information from smartphone accelerometers is challenging as the placement of the device can vary, users interact with the phone spontaneously, and as the orientation of the phone can change dynamically," says the University of Helsinki's Samuli Hemminki.
The researchers overcame these challenges by developing algorithms for processing and analyzing accelerometer measurements. In addition, the system has low power consumption and works robustly in continuous detection tasks.
"Our work enables fine-grained modeling of human transportation behavior and serves as an important building block for new kinds of mobile applications," says Helsinki researcher Petteri Nurmi. "For example, our methods would be beneficial to an application that provides feedback to encourage drivers towards more ecological driving style or to map deviations in public transportation."
From University of Helsinki
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