Krispi Computer Vision Project
Updated 8 days ago
Here are a few use cases for this project:
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Automotive Safety Monitoring: Krispi could be used to monitor the safety measures in vehicles. For instance, it could be integrated into a vehicle's dash-cam system to ensure if the driver or passengers have their seatbelts on while in motion, issuing an alert if not.
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Traffic Rule Enforcement: The model could assist law enforcement agencies in identifying violations of traffic rules. For instance, it could monitor live feeds from traffic cameras, identifying cars where seatbelts are not being used, enabling real-time intervention or issuing of fines.
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Insurance Claim Verification: Within the insurance industry, Krispi could help verify claims related to car accidents. By analyzing provided images or footage, it could establish whether the drivers and passengers were wearing seatbelts at the time of the accident, aiding the decision-making process.
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Advanced Driver-Assistance Systems (ADAS): Krispi could be applied to increase the functionalities of ADAS in vehicles, providing alerts regarding seatbelt usage or windshield cleaning requirements, thereby enhancing the safety and user experience of the drive.
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Automotive Manufacturing Quality Control: The model could be leveraged in factory settings to ensure the correct assembly of cars. By quickly identifying whether all components, like windshield and seatbelts, are in place and correctly installed, it could expedite the quality check process and reduce human error.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
krispi-skcr3-kkyzw_dataset,
title = { Krispi Dataset },
type = { Open Source Dataset },
author = { yoww },
howpublished = { \url{ https://universe.roboflow.com/yoww/krispi-skcr3-kkyzw } },
url = { https://universe.roboflow.com/yoww/krispi-skcr3-kkyzw },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { oct },
note = { visited on 2024-11-04 },
}