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Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Vaghasiya, Nikita | - |
dc.date.accessioned | 2021-01-04T08:55:04Z | - |
dc.date.available | 2021-01-04T08:55:04Z | - |
dc.date.issued | 2020-06-01 | - |
dc.identifier.uri | http://10.1.7.192:80/jspui/handle/123456789/9529 | - |
dc.description.abstract | 360 Degree car dash-cams are used to continuous recording of the external view and internal view (front and back respectively) that provide pieces of evidence in case of unexpected traffic-related accidents and incidents happen. Most car accidents happen at sides of the car and Drowsiness of the driver. Using AI-based 360 degree dash-cam utilize facial recognition to know the driver feels drowsy or tried. This report presents driver drowsiness detection using face recognition which helps to prevent the accident. To determine the driver's drowsiness using the behavior measures method which includes the eye open or close, eye blinking and mouth open or closed, etc... are monitor by the camera and give an alert message if any of these drowsiness symptoms are detect. | en_US |
dc.publisher | Institute of Technology | en_US |
dc.relation.ispartofseries | 18MCEC17; | - |
dc.subject | Computer 2018 | en_US |
dc.subject | Project Report 2018 | en_US |
dc.subject | Computer Project Report | en_US |
dc.subject | Project Report | en_US |
dc.subject | 18MCE | en_US |
dc.subject | 18MCEC | en_US |
dc.subject | 18MCEC17 | en_US |
dc.title | Artificial Intelligence base 360 Dash-Camera | en_US |
dc.type | Dissertation | en_US |
Appears in Collections: | Dissertation, CE |
Files in This Item:
File | Description | Size | Format | |
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18MCEC17.pdf | 18MCEC17 | 5.6 MB | Adobe PDF | ![]() View/Open |
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