AIoT for Road Safety: Unified Vehicle Speed and License Plate Recognition in Bangladesh

DOI

10.2991/978-94-6239-664-7_46How to use a DOI?

Keywords

Computer Vision; YOLOv8; EasyOCR; Internet of Things (IoT); AIoT Framework; Intelligent Transportation Systems

Abstract

Road safety in Bangladesh remains a critical challenge with overspeeding and limited enforcement contributing to thousands of accidents each year. Most of the existing ANPR research focuses on plate detection alone, with none of them linking vehicle identity with driving behavior. In this paper, we bridge this important gap by proposing an AIoT integrated framework that combines Bangla license plate recognition with real-time vehicle speed estimation. Our system uses a YOLOv8-based detector combined with EasyOCR trained over 393 annotated Bangla plates, complemented with heavy augmentation to make up for dataset scale. More than 4,000 vehicle events have been collected using a rig of dual infrared IoT sensors for the measurement of speed, where every incident gets synchronized into a unified record including plate text, speed, timestamp, and location, securely transmitted to the cloud server. The experimental evaluation using our methodology achieved 96.2% mAP for plate detection, 1.52% CER, and 5.53% WER in OCR, and a 2.8% error margin for IoT speed estimation with respect to the radar benchmark. The integrated system precisely flagged overspeeding and generated actionable evidence. Given the low-cost architecture and IoT connectivity, the proposed framework shows immense potential for deployment on highways, school zones, and urban corridors to support smart city initiatives and enhance national road safety.

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.

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TY  - CONF
AU  - Abdullah Al Noman
AU  - Nushrat Jahan Mila
AU  - Abdullah Al Mamun
AU  - Dipta Chandra Banik
AU  - Mridul Banik
AU  - Jia Uddin
PY  - 2026
DA  - 2026/06/08
TI  - AIoT for Road Safety: Unified Vehicle Speed and License Plate Recognition in Bangladesh
BT  - Proceedings of the International Conference on Intelligent Data Analysis and Applications (IDAA 2025)
PB  - Atlantis Press
SP  - 664
EP  - 678
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-664-7_46
DO  - 10.2991/978-94-6239-664-7_46
ID  - AlNoman2026
ER  -