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Book ChapterDOI

An AI Approach for Real-Time Driver Drowsiness Detection–-A Novel Attempt with High Accuracy

TLDR
A system which is capable of monitoring the person's consciousness, acceleration pattern and the angle of vehicle’s steering simultaneously to detect the deviation and drowsiness of the driver is introduced.
Abstract
Despite the sophisticated technology that could prevent accidents of vehicles on highways, many lives are claimed due to the drowsiness of drivers According to the data reported by the NHTSA (National Highway Traffic Safety Administration) of USA, 846 succumb to death and it has become a major threat these days which is evident from 83,000 cases registered due to drowsy driving Drowsiness is the feeling of being sleepy or being inactive towards activities and this causes a sleeping sensation which leads to closure of eyelids while driving resulting in major accidents There are systems in action that could detect physical awaken of the driver, but detecting the drowsiness and deviation of the driver is a challenging problem in the field of transportation Many factors could influence the drivers to fall asleep during their journeys and the chances of getting drowsy increases in night times than in the dawn and journeys did alone are even more dangerous So, we introduce a system which is capable of monitoring the person’s consciousness, acceleration pattern and the angle of vehicle’s steering simultaneously to detect the deviation and drowsiness of the driver The process of drowsiness and deviation detection of the driver has been done using image processing techniques Our proposed system alerts the driver by comparing the acceleration pattern to the Eye Aspect Ratio (EAR) for drowsiness It also monitors his facial movements, changes in steering angle to detect the deviation

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Citations
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Proceedings ArticleDOI

A Novel System for Real Time Drowsiness Warning and Engine Ignition Authorization using Face Recognition

TL;DR: In this paper, the authors proposed two automotive solutions to enhance safety and security features in vehicles by applying transfer learning on CNN based pretrained model MobileNetV2, which achieved 98.75% accuracy.
Journal ArticleDOI

Identifying Fake Reviews in Relation with Property and Political Data Using Deep Learning

TL;DR: In this article , the authors used LSTM and BERT (Bidirectional Encoder Representations from Transformers) algorithms in the first module and GPT2 (Generative Pre-Trained Transformer 2) in the second module.
Journal ArticleDOI

A novel approach for context-aware sensor optimization in a smart home

TL;DR: In this article , a spatial and temporal context representation of real-time sensor data is derived with the help of ontology model that captures real time sensor data, which helps sensor optimization in multi-resident living with concurrent activity occurrence.

Nss_a_376755 1641..1649

TL;DR: In this article , a data science research center, Department of Computer Science, Faculty of Science, Chiang Mai University, Chai Mai, 50200, Thailand; Data Science Research Center, Department, Statistics, Faculty, Science, and Computer Engineering, University of the Kingdom of Thailand.
References
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Journal ArticleDOI

Detecting driver drowsiness based on sensors: a review.

TL;DR: It is concluded that by designing a hybrid drowsiness detection system that combines non-intusive physiological measures with other measures one would accurately determine the drowsy level of a driver.
Proceedings ArticleDOI

Driver Fatigue Detection Based on Eye Tracking

TL;DR: The authors have made an attempt to design a system that uses video camera that points directly towards the driver's face in order to detect fatigue, and if the fatigue is detected a warning signal is issued to alert the driver.
Journal ArticleDOI

Accident prevention and prescription by analysis of vehicle and driver behaviour

TL;DR: A set of algorithms are proposed in the paper, and are implemented to predict accidents, which includes alerting the driver if an accident is predicted, and also recording and saving audio and visuals if a accident is detected.
Journal Article

Investigation on Life Rescue Technologies on Road-airbags and Anti-lock Braking System (ABS)

TL;DR: In this paper, a survey is presented on whether the use of airbags and ABS is beneficial to help curb road accidents, and an analysis of how a human life can be saved by implementing these technologies.
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