Driver Drowsiness Detection System Using Raspberry Pi
Anishka Sharma
, Garv Verma , Manas Mittal , Manmay Garg , Meetu Rani
The number of road accidents attributed to driver fatigue and drowsiness continues to rise, prompting the need for
effective and affordable driver monitoring systems. This paper presents a novel approach to detecting driver
drowsiness using a Raspberry Pi microcontroller, integrated with computer vision and sensor technologies. The
system utilizes facial recognition and eye-tracking algorithms to monitor the driver’s facial expressions, along with
to notify a fleet owner about driver drowsiness in real time, we can incorporate an IoT-based communication
system to send alerts. This can be done by integrating the Raspberry Pi with a cloud service or a mobile app using
SMS, email, or real-time notifications.. The goal of this system is to offer a reliable and accessible solution to
reduce road accidents by alerting drivers of potential drowsiness in real-time.
"Driver Drowsiness Detection System Using Raspberry Pi", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 3, page no.c472-c477, March-2025, Available :https://ijsdr.org/papers/IJSDR2503258.pdf
Volume 10
Issue 3,
March-2025
Pages : c472-c477
Paper Reg. ID: IJSDR_301202
Published Paper Id: IJSDR2503258
Downloads: 000166
Research Area: Science and Technology
Country: meerut, uttar pradesh, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
