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9 articles for “Driver Drowsiness Detection”
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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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Driver Anti-Sleep Alarming and Protection
Abstract: Road accidents due to driver drowsiness is one of the biggest problems worldwide, which kills thousands of people every year. Fatigue slows the reaction time, reduces the concentration, and, most importantly, impairs the judgment, thus making drowsy driving as dangerous as drunk driving. To reduce such accidents, various technologies have been employed to develop driver anti-sleep devices. These include sensor-based detection, camera-based eye monitoring, EEG analysis, and real-time alert systems. …
Published in International Journal of Electronics Automation · Vol. 4, Issue 1, 2026 Read article
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An approach of Computer Vision Methods for Driver’s Drowsiness and Yawn Detection
Abstract: Numerous studies have demonstrated that 4,444 traffic crashes are primarily caused by driver drowsiness. Due to advancements in digital computer systems, tiredness behaviour may now be studied by researchers worldwide. The goal of this project is to increase road safety by preventing accidents caused by sleepy drivers. To view the driver's face, use real-time facial recognition technology. A driver's attentiveness and reaction time may be impacted by weariness, which raises …
Published in International Journal of Optical Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 21–26 Read article
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DRIVE-DEFENDER: A Driver Safety-oriented Alcohol and Drowsiness Detection System
Abstract: DRIVE-DEFENDER presents a pioneering approach in driver safety through the development of a real-time machine learning system for alcohol detection. The detrimental impact of alcohol-impaired driving on road safety necessitates efficient detection mechanisms. Current methodologies are often hindered by their cost, invasiveness, and reliance on specialized sensors. DRIVE-DEFENDER utilizes a camera for recording the face of the driver in real time, employing image processing techniques to identify facial landmarks. These …
Published in Journal of Open Source Developments · Vol. 11, Issue 1, 2024 · pp. 15–26 Read article
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An IoT-Based Integrated Vehicle Safety System for Accident Detection and Driver Monitoring
Abstract: Driver fatigue, alcohol and slow response of emergency services are among a significant issue of road accidents. The paper will provide a real-life example of an IoT-based vehicle safety system, which will combine the accident detection, driver drowsiness and alcohol sensors with a cohesive system. The proposed system consists of use of accelerometer for sudden collision detection, infrared eye blink sensor for determining alertness of the driver and MQ-3 alcohol …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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ADAS Implementation & Drowsiness Detection in Vehicle
Abstract: Driver fatigue is a leading cause of road accidents, especially in public and commercial transportation, posing serious risks to passenger and pedestrian safety. To address this critical safety issue effectively, this research study presents an AI-powered ADAS designed specifically for BS6-compliant buses, using real-time fatigue detection to prevent accidents. The system integrates a Raspberry Pi equipped with an AI Hat+ module to monitor driver drowsiness by detecting prolonged eye closures …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 1, 2026 · pp. 28–36 Read article
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Enhancing Road Safety: A System for Vehicular Accident Detection, Prevention, and Rescue Alerts
Abstract: The Vehicular Accident Detection, Prevention, and Rescue Alert System is a comprehensive solution aimed at bolstering road safety by integrating multiple advanced technologies. It merges drowsiness detection, alcohol level monitoring, and instant emergency alerts to mitigate accidents and expedite rescue efforts. Modern computer vision and machine learning techniques are used by the Drowsiness Detection Alarm to track driver conduct and spot drowsiness indicators. Upon detecting drowsiness, an immediate alarm is …
Published in International Journal of Solid State Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 7–11 Read article
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IoT-Based School Bus Transportation Safety and Tracking System
Abstract: The safety of children during school commutes is a growing concern for both parents and school administrations. This paper presents an IoT-based School Bus Transportation Safety System that offers real-time tracking, biometric authentication, and emergency detection to ensure the safety of school children. The system utilizes a combination of NodeMCU, Arduino Uno, GPS, fingerprint modules, and sensors to provide a secure and efficient school transportation process. Parents and administrators can …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 1, 2025 · pp. 56–65 Read article
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Driver Drowsiness Alert System
Abstract: In the present era, the increasing frequency of accidents during prolonged road trips, primarily attributed to driver fatigue, is a matter of serious concern. Recognizing this challenge, our goal is to develop a driver drowsiness alert system to effectively address and alleviate these incidents. Theproposed system utilizes a webcam to capture real-time images of the driver's eyes, employingmachine learning algorithms to promptly identify signs of fatigue. Upon detecting drowsiness, the …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article