Virtual Witness: Advancing Road Safety Through Automated Incident Detection and Analysis

We present Virtual Witness, an innovative comprehensive AI-powered system that integrates interior and exterior vehicle cameras with advanced machine learning to deliver real-time road safety monitoring and incident analysis. By automating the detection of driver distractions, fatigue, unsafe behaviors, and external hazards, the system generates detailed incident reports without the need for manual data analysis. Virtual Witness (VW) addresses critical gaps in existing solutions which will offer a robust, long-term approach to improving driving habits and road safety worldwide. We will show the architecture, methodology, data processes, and potential for global deployment.

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Publication Details

Published
2025-03-22
DOI
https://doi.org/10.1109/southeastcon56624.2025.10971268
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Virtual Witness: Advancing Road Safety Through Automated Incident Detection and Analysis

Ramesh Annavajjala, A. K. Deb, Sumit Chakravarty, Ryan Jewett
Anomaly Detection Techniques and Applications
article

Virtual Witness: Advancing Road Safety Through Automated Incident Detection and Analysis

Ramesh Annavajjala, A. K. Deb, Sumit Chakravarty, Ryan Jewett
article en

Abstract

We present Virtual Witness, an innovative comprehensive AI-powered system that integrates interior and exterior vehicle cameras with advanced machine learning to deliver real-time road safety monitoring and incident analysis. By automating the detection of driver distractions, fatigue, unsafe behaviors, and external hazards, the system generates detailed incident reports without the need for manual data analysis. Virtual Witness (VW) addresses critical gaps in existing solutions which will offer a robust, long-term approach to improving driving habits and road safety worldwide. We will show the architecture, methodology, data processes, and potential for global deployment.

Kennesaw State University (US)
Openalex Percentile: Top 96%
Anomaly Detection Techniques and Applications
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