Accident-Avoidance System using latest Sensing Systems

The most frequent causes of traffic accidents are exhaustion and drowsiness. The number of traffic accidents caused by sleepy and fatigued drivers rises every year. This suggested study introduces a computer - aided detection software system that will be useful in reducing the number of traffic acci...

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Bibliographic Details
Published in2022 5th International Conference on Contemporary Computing and Informatics (IC3I) pp. 595 - 599
Main Authors Khan, Mizan Ali, Kaur, Sarabpreet
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.12.2022
Subjects
Alarm systems
D-Lib
Detection System and ADAS
Doppler Cascade Algorithm
Libraries
OpenCV
PERCLOS
Prediction algorithms
Sensors
Sleep
Software systems
Surveillance
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Summary:The most frequent causes of traffic accidents are exhaustion and drowsiness. The number of traffic accidents caused by sleepy and fatigued drivers rises every year. This suggested study introduces a computer - aided detection software system that will be useful in reducing the number of traffic accidents that are mostly the result of driver sleepiness. This surveillance system uses the DLib library and deep learning techniques to identify and forecast the outcomes. Additionally, this program has an alarm system to warn the user if they start to feel sleepy. A much-improved face tracking method that we utilized may increase the prediction's accuracy. To identify facial traits, it employs 68 face references. The 68 landmark method is more efficient and efficient in distinguishing face features than the PERCLOS and Doppler cascade algorithms.
DOI:10.1109/IC3I56241.2022.10072743