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Communication Dans Un Congrès Année : 2021

Kick-scooters detection in sensor-based transportation mode classification methods

Résumé

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, biking, taking bus and tramway. Results show that kick-scooters can be precisely detected up to 99% for three different sensor placements: on-foot, waist-attached and in the trouser's pocket. Thus, this paper provides a first contribution where kick-scooters can be classified and studied for further applications such as mobility behavior analysis and navigation.
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Dates et versions

hal-03225632 , version 1 (12-05-2021)

Identifiants

Citer

Fadoua Taia Alaoui, Hassen Fourati, Alain Kibangou, Bogdan Robu, Nicolas Vuillerme. Kick-scooters detection in sensor-based transportation mode classification methods. CTS 2021 - 16th IFAC Symposium on Control in Transportation Systems, Jun 2021, Lille (virtual), France. pp.1-6, ⟨10.1016/j.ifacol.2021.06.043⟩. ⟨hal-03225632⟩
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