Real-Time Helmet and Triple Riding Detection System with Automated Email Notifications for Enhanced Road Safety

This study proposes the development of a real-time computer vision-based system for detecting motorcycle riders not wearing helmets and triple riding. The system uses the YOLO object detection algorithm to locate motorcycles, riders and helmets from surveillance footage. The system detects such violations as no helmet or more than two riders on a motorcycle, it may capture a photo or video clip and will send out automated email notifications to the concerned authorities or the registered owner of the motorcycle. This innovative approach fills in the gaps of manual monitoring by providing scalability, real time processing, and automated proof of evidence collection to further improve road safety by enforcing traffic regulations.

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Publication Details

Published
2025-03-28
DOI
https://doi.org/10.1109/icdsaai65575.2025.11011898
Citations
1
Primary Topic
IoT and GPS-based Vehicle Safety Systems
Type
article
Field-Weighted Citation Impact
0.71
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article

Real-Time Helmet and Triple Riding Detection System with Automated Email Notifications for Enhanced Road Safety

Srinidhi Srinivasan, Raghav Sundar, Rushika. LG
1 citations
IoT and GPS-based Vehicle Safety Systems
0.71
article

Real-Time Helmet and Triple Riding Detection System with Automated Email Notifications for Enhanced Road Safety

Srinidhi Srinivasan, Raghav Sundar, Rushika. LG
article en
1 citations

Abstract

This study proposes the development of a real-time computer vision-based system for detecting motorcycle riders not wearing helmets and triple riding. The system uses the YOLO object detection algorithm to locate motorcycles, riders and helmets from surveillance footage. The system detects such violations as no helmet or more than two riders on a motorcycle, it may capture a photo or video clip and will send out automated email notifications to the concerned authorities or the registered owner of the motorcycle. This innovative approach fills in the gaps of manual monitoring by providing scalability, real time processing, and automated proof of evidence collection to further improve road safety by enforcing traffic regulations.

Sathyabama Institute of Science and Technology (IN)
Openalex Percentile: Top 32%
IoT and GPS-based Vehicle Safety Systems
0.71
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