DISTRACTED DRIVER DETECTION USING MACHINE LEARNING AND DEEP LEARNING

Ali Shahan; Enamul Haque

DISTRACTED DRIVER DETECTION USING MACHINE LEARNING AND DEEP LEARNING

creativework.keywords	Machine learning, deep learning, Driver distraction
dc.contributor.advisor	SHAHNEWAZ SIDDIQUE
dc.contributor.author	Ali Shahan
dc.contributor.author	Enamul Haque
dc.contributor.id	1520317042
dc.contributor.id	1531422642
dc.coverage.department	Electrical and Computer Engineering
dc.date.accessioned	2025-12-04
dc.date.accessioned	2025-12-04T09:41:22Z
dc.date.available	2025-12-04T09:41:22Z
dc.date.issued	2020-04-30
dc.description.abstract	One of the main reason of most car accidents is distracted driving, which is the act of driving while engaging in other such as texting, talking on the phone, etc. activities. Activities of that nature distract the driver from paying attention to the road. These distractions in turn compromise the safety of the driver, passengers, bystanders and others in other vehicles. 7,796 deaths due to accidents in 2018, a report of Bangladesh Passengers Welfare Association said at least 7,796 people were killed and 15,980 were injured in 6,048 accidents. The United States Department of Transportation states that one in five car accidents are caused by distracted drivers. This work looks at various images of distracted drivers taken from people performing different actions, some of which can be deemed as distracting whilst behind the wheel of a car. A mixture of various neural network is used in order to more accurately predict what activity a driver is being distracted by.
dc.description.degree	Undergraduate
dc.identifier.cd	600000275
dc.identifier.uri	https://repository.northsouth.edu/handle/123456789/1523
dc.language.iso	en_US
dc.publisher	North South University
dc.rights	@ NSU Library
dc.title	DISTRACTED DRIVER DETECTION USING MACHINE LEARNING AND DEEP LEARNING
dc.type	Project
oaire.citation.endPage	34
oaire.citation.startPage	1