The traveler stress monitoring system developed under EU Horizon 2020 project

Bon Voyage  is expected to give municipalities actionable data they can use to come up with new transportation-related services. CEA Tech institute Leti is a member of the project consortium.

The researchers used existing technologies to build the Mobility Observer, an application that can very accurately determine the type of transportation a person is using. "We took advantage of the most energy-efficient commercial sensors on the market—the accelerometers, magnetometers, and, in some cases, GPS and Wi-Fi, already used in smartphones—to extract signatures characteristic of different types of transportation," said a researcher. "The data goes into a learning algorithm that gradually builds an accurate model capable of distinguishing between a train, subway, and tramway or—in the future—between a traditional and electric vehicle." The researchers also developed a second application that processes signals (like heart rate and electrodermal activity) from biological sensors. The tool combines data fusion and signal processing technologies to generate indicators of users' stress levels. A laboratory prototype was validated for transportation applications.

Together, the applications could give municipalities the kind of real-time data they need to gain valuable insights into user habits and come up with more advanced, better-targeted transportation services.