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4 articles for “eye aspect ratio”
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Driver Drowsiness Detection System Using Python, OpenCV and Raspberry Pi
Abstract: The number of accidents and deaths can be greatly decreased by using intelligent systems to prevent auto accidents. Human mistakes, such as drowsy driving, are one of the variables that significantly contribute to accidents. The system looks for symptoms of fatigue and sleepiness on a person's face while they are driving. It is based on an image processing technique. This project presents a way to analyze and anticipate driver drowsiness …
Published in Trends in Opto-electro & Optical Communication · Vol. 13, Issue 2, 2023 · pp. 6–15 Read article
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Live Integrated Facial Observation (L.I.F.O.)
Abstract: A human face is the most influential part of humans that can uniquely identify a person. Using all the facial characteristics as biometric, the LIFO system can be applicable in many different ways. Like in everyday life, the most mandatory task in any organization is attendance marking. Earlier, people used to mark their presence using paperwork but now along with the advancement of technology, this system has also changed and …
Published in Journal of Advancements in Robotics Read article
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Driver Drowsiness Detection System
Abstract: One of the main causes of road accidents worldwide in recent years is driver fatigue. Assessing a driver's mood, or how sleepy they are, is a clear approach to gauge their level of exhaustion. Therefore, detecting driver fatigue is very important to save lives and property. The creation of a prototype drowsiness detection system is the aim of this research. The system operates in real time, continuously capturing images and …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 16–21 Read article
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An Experimental Analysis on Enhancement of Electric Vehicle Safety using ADAS Technology and Forward Collision Avoidance with an Automatic Braking System
Abstract: The rapid expansion of the automobile sector in developing nations has intensified road safety concerns, particularly in congested urban environments where human error accounts for approximately 90% of all accidents. This paper presents and experimentally validates an integrated Advanced Driver Assistance System (ADAS) for electric vehicles comprising three complementary safety modules: a Forward Collision Avoidance System (FCAS) employing an HC-SR04 ultrasonic sensor interfaced with an Arduino Uno R3 to detect …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 20–30 Read article