Tang, Qinrui und Jahan, Kanwal und Roth, Michael (2022) Deep CNN-BiLSTM Model for Transportation Mode Detection Using Smartphone Accelerometer and Magnetometer. 2022 IEEE Intelligent Vehicles Symposium (IV), 2022-06-05 - 2022-06-09, Aachen, Germany. doi: 10.1109/IV51971.2022.9827275.
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Offizielle URL: https://ieeexplore.ieee.org/document/9827275
Kurzfassung
Transportation mode detection from smartphone data is investigated as a relevant problem in the multi-modal transportation systems context. Neural networks are chosen as a timely and viable solution. The goal of this paper is to solve such a problem with a combination model of Convolutional Neural Network (CNN) and Bidirectional-Long short-term memory (BiLSTM) only processing accelerometer and magnetometer data. The performance in terms of accuracy and F1 score on the Sussex-Huawei Locomotion-Transportation (SHL) challenge 2018 dataset is comparable to methods that require the processing of a wider range of sensors. The uniqueness of our work is the light architecture requiring less computational resources for training and consequently a shorter inference time.
elib-URL des Eintrags: | https://elib.dlr.de/188137/ | ||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag, Poster) | ||||||||||||||||
Titel: | Deep CNN-BiLSTM Model for Transportation Mode Detection Using Smartphone Accelerometer and Magnetometer | ||||||||||||||||
Autoren: |
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Datum: | Juni 2022 | ||||||||||||||||
Referierte Publikation: | Ja | ||||||||||||||||
Open Access: | Ja | ||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||
DOI: | 10.1109/IV51971.2022.9827275 | ||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||
Stichwörter: | mode detection, self-supervised learning, deep learning, SHL dataset, BiLSTM, batch normalization | ||||||||||||||||
Veranstaltungstitel: | 2022 IEEE Intelligent Vehicles Symposium (IV) | ||||||||||||||||
Veranstaltungsort: | Aachen, Germany | ||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||
Veranstaltungsbeginn: | 5 Juni 2022 | ||||||||||||||||
Veranstaltungsende: | 9 Juni 2022 | ||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||
HGF - Programm: | Verkehr | ||||||||||||||||
HGF - Programmthema: | Verkehrssystem | ||||||||||||||||
DLR - Schwerpunkt: | Verkehr | ||||||||||||||||
DLR - Forschungsgebiet: | V VS - Verkehrssystem | ||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | V - VMo4Orte - Vernetzte Mobilität für lebenswerte Orte | ||||||||||||||||
Standort: | Berlin-Adlershof , Braunschweig | ||||||||||||||||
Institute & Einrichtungen: | Institut für Verkehrssystemtechnik | ||||||||||||||||
Hinterlegt von: | Tang, Qinrui | ||||||||||||||||
Hinterlegt am: | 09 Sep 2022 15:16 | ||||||||||||||||
Letzte Änderung: | 14 Okt 2024 14:53 |
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