Biosensor-driven IoT wearables for accurate body motion tracking and localization
The domain of human locomotion identification through smartphone sensors is witnessing
rapid expansion within the realm of research. This domain boasts significant potential across …
rapid expansion within the realm of research. This domain boasts significant potential across …
MobilityDL: a review of deep learning from trajectory data
Trajectory data combines the complexities of time series, spatial data, and (sometimes
irrational) movement behavior. As data availability and computing power have increased, so …
irrational) movement behavior. As data availability and computing power have increased, so …
Three-year review of the 2018–2020 SHL challenge on transportation and locomotion mode recognition from mobile sensors
The Sussex-Huawei Locomotion-Transportation (SHL) Recognition Challenges aim to
advance and capture the state-of-the-art in locomotion and transportation mode recognition …
advance and capture the state-of-the-art in locomotion and transportation mode recognition …
Summary of SHL challenge 2023: Recognizing locomotion and transportation mode from GPS and motion sensors
In this paper we summarize the contributions of participants to the fifth Sussex-Huawei
Locomotion-Transportation (SHL) Recognition Challenge organized at the HASCA …
Locomotion-Transportation (SHL) Recognition Challenge organized at the HASCA …
Transportation mode recognition based on low-rate acceleration and location signals with an attention-based multiple-instance learning network
C Siargkas, V Papapanagiotou… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Transportation mode recognition (TMR) is a critical component of human activity recognition
(HAR) that focuses on understanding and identifying how people move within transportation …
(HAR) that focuses on understanding and identifying how people move within transportation …
[PDF][PDF] Deep Learning From Trajectory Data: a Review of Deep Neural Networks and the Trajectory Data Representations to Train Them.
Trajectory data combines the complexities of time series, spatial data, and (sometimes
irrational) movement behavior. As data availability and computing power have increased, so …
irrational) movement behavior. As data availability and computing power have increased, so …
A multimodal IoT-based locomotion classification system using features engineering and Recursive neural network
Locomotion prediction for human welfare has gained tremendous interest in the past few
years. Multimodal locomotion prediction is composed of small activities of daily living and an …
years. Multimodal locomotion prediction is composed of small activities of daily living and an …
Human activity recognition with AutoML using smartphone radio data
D Balabka, D Shkliarenko - Adjunct Proceedings of the 2021 ACM …, 2021 - dl.acm.org
Participants of the fourth edition of SHL recognition challenge 2021 aim to recognize eight
locomotion and transportation activities in a user-independent manner based on radio data …
locomotion and transportation activities in a user-independent manner based on radio data …
ModeSense: Ubiquitous and accurate transportation mode detection using serving cell tower information
Recent transportation mode detection systems propose leveraging signals from only the
serving cell tower to ensure ubiquity and practical deployability across all phones. However …
serving cell tower to ensure ubiquity and practical deployability across all phones. However …
Phased human activity recognition based on GPS
R Sekiguchi, K Abe, suzuki shogo, M Kumano… - Adjunct Proceedings of …, 2021 - dl.acm.org
This paper describes an activity recognition method for Sussex-Huawei Locomotion-
Transportation (SHL) recognition challenge by team TDU_BSA_BCI. The classification …
Transportation (SHL) recognition challenge by team TDU_BSA_BCI. The classification …