Real time image processing monitoring system based IoT

Object detection is a significant task that forms the basis for many image processing and computer vision applications. Automobiles and vehicles are engrained in popular culture as one of the most versatile and convenient means of transportation. While it is a convenient and popular means of transportation, it is also quite dangerous. Every year, several people are killed in car accidents caused by another vehicle or object. A Method for Preventing Mishaps Many incidents can be prevented if drivers avoid exposure and evasion, which are caused by things like loss of control, irresponsible driving, exhausted or drunk drivers, and a lack of concentration on the road. The market currently does not provide a standard safety feature in any car, nor does it provide the use of sensory equipment to identify potentially dangerous objects at a defined distance. The goal of this study is to create intelligent driver monitoring software that identifies tiredness and helps to avoid traffic accidents. A driver and a publicly accessible online tracking program The technology measures him if he blinks his eyes. It is done by measuring the distance between the eyes or by staring at specified spots. Python is the programming language utilized in the development of the software system. It uses the OPENCV and Media Pipe libraries, a Media Pipe Face Mesh technique is used in this paper. The system can calculate the time of nap, and it triggers beep sound if the nap occurs in any time. the system take consider, if the driver haver 30 or more of that value in napping. It will be send alarm message IOT system with the current location of driver to driver family.