• OMKAR KALE
• SRUSHTI GADHAVE
• REVATI DESHMUKH

Today’s world is moving world. Everyone becomes multi-tasker. They want to handle multiple tasks at a time. While driving also the do another works like talking on the phone or another person, chatting, also they face traffic problems. So it is necessary to be aware while driving. If the driver mind is distracted, then it causes an accident. Today, 80% of death caused due to the accident and the main reason was the driver unawareness. To overcome this issue, we need to aware while driving. This article proposes the system for auto alerting the driver when it is distracted. Depending on the size of data to be collected from the OBD-II, numerous algorithms can be dedicated for data mining of DB such as a dedicated algorithm may be used for collecting data for distance covered by a vehicle, vehicle’s speed, then for acceleration, rpm, etc. The reviews a range of issues pertaining to driver modeling for the detection and assessment of distraction. The areas addressed include 1) understanding driver behavior and distraction, 2) maneuver recognition and distraction analysis, 3) glance behavior and visual tracking, and 4) mobile platform advancements for in-vehicle data collection and human-machine interface.

Glance Behavior, Human Machine Interface, Face Detection, Distraction Detection, Alert Sound, OBD Data.

"Cloud Based Driver Monitoring and Vehicle Diagnostics with OBD Telematics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.a511-a517, June-2022, Available :http://www.jetir.org/papers/JETIR2206059.pdf

"Cloud Based Driver Monitoring and Vehicle Diagnostics with OBD Telematics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppa511-a517, June-2022, Available at : http://www.jetir.org/papers/JETIR2206059.pdf