Smart Driving Application for a Safe Ride- A Comparative Analysis of Drowsiness Detection Methods


Manda Ukey


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.


How to Cite
Ukey, M. (2021). Smart Driving Application for a Safe Ride- A Comparative Analysis of Drowsiness Detection Methods. International Journal of Next-Generation Computing, 12(5).


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