Open AccessSmart Driving Application for a Safe Ride- A Comparative Analysis of Drowsiness Detection Methods
Author(s) -
Manda Ukey
Publication year - 2021
Publication title -
international journal of next-generation computing
Language(s) - English
Resource type - Journals
eISSN - 2229-4678
pISSN - 0976-5034
DOI - 10.47164/ijngc.v12i5.443
Subject(s) - covid-19 , computer security , duration (music) , computer science , transport engineering , engineering , internet privacy , medicine , art , literature , disease , pathology , infectious disease (medical specialty)
Covid pandemic has given a boost to online shopping and hence the product delivery. As a result, the number of services like carpooling, product delivery for online shopping, food delivery services like zomato, swiggy, ubereats, etc. have increased tremendously. These services have added number of drivers to the already existing large number of automobile users on road. Also these services are provided without any restricted time duration causing considerable increase in road traffic during rush hours. These conditions result into driver fatigue, rash driving, micro sleeps and even drowsiness. Driving in these peak times is not only dangerous but also may result into accidents and casualties. Fatigued driving is consequently converted into drowsiness and is the major cause of road accidents. Worldwide many people become victim of it and lose their lives due to drowsiness. However, if the driver fatigue is detected early and some prior indication of it is given, it may prevent many accidents and can save lives. Many automobile vendors are providing driver assistance solutions inbuilt in the cars. However, the accuracy of these solutions is again a point of discussion. To address this issue, the presented paper provides a detailed survey on different non- invasive methods of real-time detection of driver fatigue and drowsiness with their comparative solutions.