DETECTION OF DISTRACTED DRIVERS ON THE ROAD USING DEEP LEARNING APPROACH
B.Vanipriya,M.E.
, Muthu Shruthi S , Archana Priya S , IreneChristinaAndrea p , Pavithra S
Keywords— ,CNN, Lethargic, CRRI, OpenCV
Abstract—Although there are many factors that contribute to
traffic accidents, such as breaking traffic laws, driving too fast,
etc., one of them is drowsy driving. According to the Central
Road Research Institute, sleepy/drowsy driving causes 40% of
collisions (CRRI). Every year, incidents caused by drivers
falling asleep at the wheel result in the deaths of roughly 1.5
lakh individuals. Convolutional Neural Network (CNN)
algorithms can be used to identify the sleepy drivers and warn
them whenever they appear to be falling asleep to resolve this
problem. With the help of the CNN algorithm, which is built on
the TensorFlow and Keras frameworks, we take pictures of the
person riding the wheels and categories them as open or closed.
The current algorithm functions properly when compared to the
CNN algorithm.
"DETECTION OF DISTRACTED DRIVERS ON THE ROAD USING DEEP LEARNING APPROACH", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.11, Issue 2, page no.517-520, February-2024, Available :https://tijer.org/TIJER/papers/TIJERB001081.pdf
Volume 11
Issue 2,
February-2024
Pages : 517-520
Paper Reg. ID: TIJER_151085
Published Paper Id: TIJERB001081
Downloads: 000282
Research Area: Science and Technology
Country: thiruvallur ,chennai, Tamilnadu, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
