Distracted Driving Computer Vision Project
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Here are a few use cases for this project:
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Road Safety Monitoring: The "Distracted Driving" model could be integrated into vehicles or road surveillance systems to monitor the behavior of drivers in real-time. Actions like drinking, texting, talking on the phone, or nodding off could trigger alerts to the driver and interventions to prevent potential accidents.
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Driver Assistance Systems Development: Technology companies involved in the production of advanced driver assistance systems (ADAS) can use this model to enhance their products’ ability to understand and react to the driver’s behavior and actions.
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Automotive Insurance: Insurance companies might utilize this computer vision model to assess the risk levels of potential clients by evaluating their driving habits. This could then directly influence the pricing of their car insurance policy.
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Research on Distracted Driving: Academics and researchers can use this model to study the prevalence and consequences of different types of distractions while driving, enabling the development of stronger road safety policies and measures at a policy-making level.
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Driver Education: The "Distracted Driving" model could be used in driving schools to train and make beginner drivers aware of the implications of various actions that can lead to distracted driving, hence promoting safer driving habits.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
distracted-driving-v2wk5_dataset,
title = { Distracted Driving Dataset },
type = { Open Source Dataset },
author = { Ipylot project },
howpublished = { \url{ https://universe.roboflow.com/ipylot-project/distracted-driving-v2wk5 } },
url = { https://universe.roboflow.com/ipylot-project/distracted-driving-v2wk5 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2022 },
month = { jul },
note = { visited on 2024-11-21 },
}