F. Taia Alaoui

French National Centre for Scientific Research | CNRS · GRICAD center of Grenoble

This work presents a novel transportation mode detection algorithm that handles the recognition of kick-scooters. In 2015, 10 minutes of data from a kick-scooter were considered in a transportation mode detection study, yielding a 56% F1-score. Since then, kick-scooters were not given much attention. Yet, kick-scooters are now very present in the u...

Kick-scooters detection in sensor-based transportation mode classification methods. Abstract: In this work we present a novel classification model that can detect kick-scooters from inertial and pressure sensors. The detection is performed with kick-scooters being trained with other activities and transportation modes including still, walking, biki...

This paper presents a novel urban transportation mode detection (TMD) method based on inertial and barometric data. To the best of our knowledge, this is the first time that a 3-axis accelerometer, a 3-axis gyroscope, and a barometer are combined for TMD purposes. One contribution was to build and share an optimized TMD dataset in terms of duration...

La navigation inertielle grâce aux capteurs intégrés dans les smartphones permet d’assurer une géolocalisation continue même en absence de signal GNSS. Ces capteurs bas coût délivrent néanmoins des mesures bruitées qui engendrent une dérive de la trajectoire. La technique PDR qui est une technique de navigation inertielle par détection de pas souff...

An A⁎ -based routing graph is proposed to assist PDR indoor and outdoor navigation with handheld devices. Measurements are provided by inertial and magnetic sensors together with a GNSS receiver. The novelty of this work lies in providing a realistic motion support that mitigates the absence of obstacles and enables the calibration of the PDR model...