Version 1
: Received: 18 December 2023 / Approved: 18 December 2023 / Online: 18 December 2023 (12:21:08 CET)
How to cite:
Lee, E.; Kim, T.; Khan, J.; Zaman, U.; Ku, J.; Kim, K. A Study on Micro-Mobility Data Collection System Using Incremental Learning Techniques. Preprints2023, 2023121330. https://doi.org/10.20944/preprints202312.1330.v1
Lee, E.; Kim, T.; Khan, J.; Zaman, U.; Ku, J.; Kim, K. A Study on Micro-Mobility Data Collection System Using Incremental Learning Techniques. Preprints 2023, 2023121330. https://doi.org/10.20944/preprints202312.1330.v1
Lee, E.; Kim, T.; Khan, J.; Zaman, U.; Ku, J.; Kim, K. A Study on Micro-Mobility Data Collection System Using Incremental Learning Techniques. Preprints2023, 2023121330. https://doi.org/10.20944/preprints202312.1330.v1
APA Style
Lee, E., Kim, T., Khan, J., Zaman, U., Ku, J., & Kim, K. (2023). A Study on Micro-Mobility Data Collection System Using Incremental Learning Techniques. Preprints. https://doi.org/10.20944/preprints202312.1330.v1
Chicago/Turabian Style
Lee, E., Jaebin Ku and Kyungsup Kim. 2023 "A Study on Micro-Mobility Data Collection System Using Incremental Learning Techniques" Preprints. https://doi.org/10.20944/preprints202312.1330.v1
Abstract
This study addressed the need for efficient data collection in micro-mobility using low-end hardware, focusing on developing a system capable of handling large real-time data streams. We proposed a novel data collection system that leverages incremental learning techniques, enabling AI-based services for micro-mobility passengers through smartphones. Our approach utilizes 3-axis acceleration sensors integrated into micro-mobility devices, collecting motion data in real-time. This data is processed through an incremental learning pre-processing server, employing the Broad Learning System algorithm, to ensure robust performance in noisy, real-world environments. The use of incremental learning is pivotal, allowing our system to adapt continuously to new data, enhancing the accuracy and relevance of the AI services provided to passengers. This research not only advances the technical capabilities in micro-mobility data handling but also has the potential to enhance the overall passenger experience through improved AI-based services.
Keywords
incremental learning; micro-mobility; data collection system; AI-based services; Broad Learning System algorithm
Subject
Engineering, Transportation Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
