FR_Traffic_Violations_mobile_3 Computer Vision Project
Updated 2 days ago
Here are a few use cases for this project:
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Automotive Safety Compliance: The "Seat_belt_detection" model can be used by traffic law enforcement agencies to identify and fine violators who are not wearing seatbelts or helmets. The model can analyze surveillance footage or images to pinpoint these infractions.
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Insurance Claims Validation: Insurance companies can utilize the model to verify the veracity of claims related to accidents. Lack of seatbelt usage or helmet could affect claim payouts.
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Driver Behavior Analysis: Companies managing a fleet of vehicles can use this model to monitor driver behavior concerning seatbelt usage and helmet usage for bikers, promoting safety compliance within the organization.
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Road Safety Campaigns: Governments or non-profit organizations advocating for road safety can use the model to quantify the percentage of people not following safety rules, like wearing seatbelts or helmets, for targeted campaign planning.
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Distracted Driving Detection: The model can also be used in detecting distracted driving by monitoring if the driver is using a mobile while driving or riding, hence acting as a preventive measure for road accidents.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
fr_traffic_violations_mobile_3_dataset,
title = { FR_Traffic_Violations_mobile_3 Dataset },
type = { Open Source Dataset },
author = { ZHONG WEI },
howpublished = { \url{ https://universe.roboflow.com/zhong-wei-u8cav/fr_traffic_violations_mobile_3 } },
url = { https://universe.roboflow.com/zhong-wei-u8cav/fr_traffic_violations_mobile_3 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { oct },
note = { visited on 2024-11-01 },
}