Safer on the roads thanks to intelligent driving assistance.

We have actively contributed to the research on early detection of motion sickness through sensor measurements and their rates of change, and have been able to optimize this prediction problem. The accuracy of the process was significantly improved and the product was finally marketable.

Our know-how comes into play especially in this less conventional classification problem with more than two categories. We have been instrumental in ensuring that the vehicle’s on-board computer provides the driver with reliable information as to whether everything is in order, whether the driver is in a state of transition to motion sickness, or whether a break is necessary.

Here, machine learning pipelines were combined with nested binary classification models to address this problem. Our approach is based on best practices and latest research in the field, so the data could be analyzed quickly and effectively to train the best possible predictive model.

Thanks to our extensive experience and know-how, we have been able to significantly improve the accuracy and reliability of the forecast, thus making an important contribution to road safety. We are strongly positioned to bring this expertise to other industries to solve similar challenges and develop innovative solutions.


Discover how businesses and academia have already benefited from our AI applications: