Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jun 10, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Journey tracker: driver alerting system with a deep learning approach.

N L Yashaswini¹, Vanishri Arun¹, B M Shashikala²

¹Department of Information Science and Engineering, JSS Science and Technology University, Mysuru, Karnataka, India.

Frontiers in Robotics and AI

|October 21, 2024

Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Editorial: Application of computational intelligence techniques for lifestyle related diseases management.

Frontiers in digital health·2026

Same author

From needs to app: A user-centred design approach for developing mobile health interventions in oncology care.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners·2026

Same author

Economic evaluation of a digital health intervention for cancer care: Cost-utility analysis of the OncoCare app.

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners·2026

Same author

Enhancing Chemotherapy Adherence in Cancer Management: A Quasi-Experimental Trial of a Smartphone Application.

Cancer investigation·2025

Same author

"Development and validation of a web-based platform for streamlining chemotherapy management in oncology".

Journal of oncology pharmacy practice : official publication of the International Society of Oncology Pharmacy Practitioners·2025

Same author

Gluten identification from food images using advanced deep learning and transfer learning methods.

Journal of food science and technology·2025

Same journal

Editorial: Robotic applications for a sustainable future.

Frontiers in robotics and AI·2026

Same journal

Passive wheels on legged robots: a survey.

Frontiers in robotics and AI·2026

Same journal

Politeness cannot make up for robots' errors.

Frontiers in robotics and AI·2026

Same journal

Workers expect basic social skills but limited autonomy from future robots - a qualitative interview study and taxonomy for robot social skills.

Frontiers in robotics and AI·2026

Same journal

Human-robot interaction in sustainable hospitality: how robot type shapes customer emotions, green perceptions, and service loyalty.

Frontiers in robotics and AI·2026

Same journal

Dynamic variance-aware federated tuning for efficient autonomous vehicle perception under non-IID settings.

Frontiers in robotics and AI·2026

See all related articles

This summary is machine-generated.

A new journey tracker system uses EfficientNet to detect driver drowsiness, improving public transport safety. This AI system achieved 95% accuracy, alerting drivers and enabling penalties for enhanced professionalism.

Area of Science:

Computer Science
Artificial Intelligence
Transportation Safety

Background:

Driver drowsiness is a significant safety risk in public transportation.
Existing systems may lack accuracy or real-time monitoring capabilities.

Purpose of the Study:

To develop and evaluate an AI-powered journey tracker system for detecting driver drowsiness.
To enhance public transportation safety and driver accountability.

Main Methods:

A custom EfficientNet model was trained on the Media Research Lab (MRL) eye dataset.
Eye regions were isolated, reflections filtered, and a baseline behavior established.
The 'swish' activation function and models trained from scratch were utilized.

Main Results:

Keywords:

baseline behavior custom EfficientNet media research lab pupil detection swish activation function

More Related Videos

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

Related Experiment Videos

Last Updated: Jun 10, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

The system achieved a 95% accuracy rate in detecting driver drowsiness.
The 'swish' activation function outperformed other tested functions.
Models trained from scratch showed better performance than pre-trained models.

Conclusions:

The developed system effectively monitors driver alertness and detects drowsiness.
This technology promotes safer public transportation and professional driver conduct.
Personalization data and pupil detection enhance alert and penalty triggers.