GLMLP-TRANS: A transportation mode detection model using lightweight sensors integrated in smartphones

X Liu - Computer Communications, 2022 - Elsevier
Transportation mode detection (TMD), as an essential part of Intelligent Transportation
Systems, aims at analyzing human current transportation activities, and can be widely …

Combining residual and LSTM recurrent networks for transportation mode detection using multimodal sensors integrated in smartphones

C Wang, H Luo, F Zhao, Y Qin - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In recent years, with the rapid development of public transportation, the ways people travel
has become more diversified and complicated. Transportation mode detection, as a …

Transportation mode detection using temporal convolutional networks based on sensors integrated into smartphones

P Wang, Y Jiang - Sensors, 2022 - mdpi.com
In recent years, with the development of science and technology, people have more and
more choices for daily travel. However, assisting with various mobile intelligent services by …

LSTM network for transportation mode detection

S Kumar, A Damaraju, A Kumar, S Kumari… - Journal of Internet …, 2021 - jit.ndhu.edu.tw
Abstract The study of Transportation Mode Detection (TMD) has become a popular research
field in recent years. It will be a crucial part of Smart mobility and Smart cities in upcoming …

Feature Pyramid biLSTM: Using Smartphone Sensors for Transportation Mode Detection

Q Tang, H Cheng - arXiv preprint arXiv:2310.11087, 2023 - arxiv.org
The widespread utilization of smartphones has provided extensive availability to Inertial
Measurement Units, providing a wide range of sensory data that can be advantageous for …

Transportation mode detection combining CNN and vision transformer with sensors recalibration using smartphone built-in sensors

Y Tian, D Hettiarachchi, S Kamijo - Sensors, 2022 - mdpi.com
Transportation Mode Detection (TMD) is an important task for the Intelligent Transportation
System (ITS) and Lifelog. TMD, using smartphone built-in sensors, can be a low-cost and …

[HTML][HTML] Feature pyramid biLSTM: Using smartphone sensors for transportation mode detection

Q Tang, H Cheng - Transportation Research Interdisciplinary Perspectives, 2024 - Elsevier
The wide utilization of smartphones has provided extensive availability to Inertial
Measurement Units, providing a wide range of sensory data that can be advantageous for …

A deep learning model for transportation mode detection based on smartphone sensing data

X Liang, Y Zhang, G Wang, S Xu - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Understanding people's transportation modes is beneficial for empowering many intelligent
transportation systems, such as supporting urban transportation planning. Yet, current …

Toward transportation mode recognition using deep convolutional and long short-term memory recurrent neural networks

Y Qin, H Luo, F Zhao, C Wang, J Wang, Y Zhang - IEEE Access, 2019 - ieeexplore.ieee.org
With the rapid development of mobile Internet techniques, using the sensor-rich
smartphones to sense various contexts attracts much attention, such as transportation mode …

Deep CNN-BiLSTM model for transportation mode detection using smartphone accelerometer and magnetometer

Q Tang, K Jahan, M Roth - 2022 IEEE Intelligent Vehicles …, 2022 - ieeexplore.ieee.org
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 …