• Pratiksha Kulkarni
• Nischitha G

Driver distraction is defined as an activity performed by a driver that diverts attention away from the driver’s primary ones and that can be the leading cause of motor vehicle accidents. The driver is the most important participant in vehicle control, including steering, throttling, braking, maneuvering, and other operations. These primary tasks must be accomplished safely for all traffic participants. This project proposes a driver distraction detection system that identifies various types of distractions through a camera observing the driver. Our goal is to build a high accuracy that captures the live movement of the driver and to distinguish whether the driver is driving safely or conducting a particular kind of distraction. Based on these activities, the system will classify them accordingly using a proper Machine Learning technique and instruct the driver about the distraction.

- Distracted driver, Machine Learning, TensorFlow, caffe model.

"Real-time Behavior Analysis of an Inattentive Driver", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.f328-f333, May-2021, Available :http://www.jetir.org/papers/JETIR2105711.pdf

"Real-time Behavior Analysis of an Inattentive Driver", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppf328-f333, May-2021, Available at : http://www.jetir.org/papers/JETIR2105711.pdf