Study on mobile device motion detection receives an award for pioneering research that has stood the test of time

A study on mobile device motion detection published ten years ago by computer scientists Petteri Nurmi, Samuli Hemminki and Sasu Tarkoma has received the prestigious SenSys Test of Time Award.

The study entitled Accelerometer-Based Transportation Mode Detection on Smartphones, published ten years ago, has received the SenSys Test of Time Award, which was announced at the ACM SenSys conference in Istanbul in November 2023.

The recognition means that the study, originally published at the SenSys 2013 conference, is considered ground-breaking in its field. It is considered to have contributed to research on embedded computing and telecommunications as well as in the development of further practical applications. According to the grounds for the award, the decision was also influenced by the societal significance of the study, such as its practical impact on people’s lives.

Professor of Computer Science Petteri Nurmi appreciates the award.

“It’s always great to be rewarded for your research but it’s particularly great to hear that your research article continues to be highly valued even after a decade. That’s not an everyday occurrence in this field,” says Nurmi.

Smartphone recognises your mode of transportation

The study looked at how data from smartphone accelerometers can be used to identify whether a person is walking or using a vehicle of some sort. The method was also able to distinguish between different modes of transportation.

When the study was originally published, Nurmi estimated that it would make it possible to model people’s traffic behaviour. This information could then be used as a basis for novel mobile applications, for example, to monitor disruptions to public transport or help motorists drive more economically. This has indeed happened.

“The use of various accelerometers and inertial sensors has become more commonplace and they are now widely used in the analysis of mobility data. Smartphones today also have more advanced features for analysing mobility data,” says Nurmi.

According to Nurmi, the application of data accumulated based on our movement and the related equipment have also diversified in ten years.

“At the time, identification of mobility data with smartphones was still in its infancy. As a smartphone’s position on the user varies, the analysis of mobility data is difficult. We have now moved into an era where there are all kinds of devices that can be used for analysis. There are already so many application areas that it’s difficult to keep up with the development.”

“We have used our methods in smartwatches to compensate the effect of motion on other sensors. For example, heart rate sensors are influenced by motion patterns. Another area where we have used our methods is underwater communications where motion information can be used to detect periods where water is calm and supportive of effective communications,” says Nurmi.

In addition to benefiting the research field in its entirety, the research has also resulted in patenting and given rise to commercialization.


Hemminki, S., Nurmi, P., & Tarkoma, S. (2013). Accelerometer-based transportation mode detection on smartphones. Article 13. Presented at the Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, Roma, Italy. doi:10.1145/2517351.2517367