Intelligent Vehicle Monitoring System
- DOI
- 10.2991/978-94-6239-650-0_8How to use a DOI?
- Keywords
- Internet of Things (IOT); Onboard Diagnostics (OBD); Machine Learning (ML); Fleet Management; Auto encoders; Predictive Maintenance; Vehicle Monitoring; CAN bus
- Abstract
With the advent of Internet of Things (IoT) technologies and On-Board Diagnostics (OBD) systems in modern vehicles has enabled continuous real-time data collection from vehicular sensors paving new way for predictive maintenance. In this paper, we have summarized architectures of various recent research papers by assessing the way they get vehicular parameters-either using OBD-II data or external sensors, preprocessing techniques applied on those data and how they gained useful insights for the data. Apart from traditional architecture, this paper also proposes a newer architecture, to enhance data collection, onboard vehicle maintenance and secure transmission of data to the cloud.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Ashwin Pillai AU - Tanmay Salavkar AU - Srushti Wategaonkar AU - Harsh Rao AU - Deepa Ekhande PY - 2026 DA - 2026/04/20 TI - Intelligent Vehicle Monitoring System BT - Proceedings of the Conference on Technologies for Future Cities (CTFC 2025) PB - Atlantis Press SP - 107 EP - 119 SN - 3005-155X UR - https://doi.org/10.2991/978-94-6239-650-0_8 DO - 10.2991/978-94-6239-650-0_8 ID - Pillai2026 ER -