• Mr. Dr. P. Raja.
• Mr. Abdirahman.

One of the leading incidents and accidents worldwide is driver weariness. One of the most reliable methods of determining driver weariness is to recognize the driver's tiredness. The goal of this project is to create a working prototype of a sleepiness detection technique. This device monitors the drivers face and sounds a warning if he or she appears to be tired. The program is a great surveillance system that isn't obtrusive. The objective is to improve the motorist's wellbeing without becoming intrusive. The motorist's eye blink is observed in this research. When a motorist's eyes are closed for an infinite length of duration, the driver is considered drowsy and an alert is raised. This has already been programmed for the recognition of facial characteristics, OpenCV was used with the face landmark detection model.

Driver Drowsiness Detection for Safety Assistance Using IOT and Machine Learning

"Driver Drowsiness Detection for Safety Assistance Using IOT and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.e481-e485, May-2022, Available :http://www.jetir.org/papers/JETIR2205560.pdf

"Driver Drowsiness Detection for Safety Assistance Using IOT and Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppe481-e485, May-2022, Available at : http://www.jetir.org/papers/JETIR2205560.pdf