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dc.contributor.author | Qamar-Ul-Islam, 01-235142-062 | |
dc.contributor.author | Aymen Nizam, 01-235142-016 | |
dc.date.accessioned | 2018-09-06T04:57:49Z | |
dc.date.available | 2018-09-06T04:57:49Z | |
dc.date.issued | 2018 | |
dc.identifier.uri | http://hdl.handle.net/123456789/7424 | |
dc.description | Supervised by Dr.Muhammad Asfand-e-yar | en_US |
dc.description.abstract | Due to rapid increase in traffic number of people are becoming the victims of immense traffic jams. Heavy traffic density results in overnight driving and driver fatigue. This ends up with causing number of accidents. The driver sleeping mode application will run on real time bases using image processing techniques. The Application used Haar Cascade Classifier for face detection and for eye tracking KLT algorithm is used. The application will generate alarm once the drowsy is detected. Driver Sleeping Mode detection application will show the driver status based on the conditions driver is in. The alarm will be canceled bases on face detection despite of pressing button to cancel alarm, this will help drivers to maintain their focus while driving. Hence resulting in overcoming the rate of accidents. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Bahria University Islamabad Campus | en_US |
dc.relation.ispartofseries | BS IT;MFN 6916 | |
dc.subject | Information Technology | en_US |
dc.title | Driver Sleeping Mode Detection Application | en_US |
dc.type | Thesis | en_US |