The stress level of the driver will have a great impact at the time of driving. This may have impact in driver performance and it may lead to many accidents. Many people tend to lose their lives due to driver’s stress level. Something which is not seen and identified is generally defined as stress. In this paper, different sensors like heartbeat, eyeblink sensors are used. Eye blinking, speed, steering angle, turn signal are the parameters that can be monitored while driving. These are generally used to examine the driver’s distractions. Real time data collection, sharing of data based on IOT, and data analytics are to be used here to overcome the challenges. In order to predicts the level of stress of the driver and his drowsiness at the rime of driving, heartbeat and eyeblink sensors are used. To use this in real time this sensor is attached to the driver’s glass. The data collected using this sensor is passed on to the microcontroller. The real time data is passed on to the system using the RS232 cable.

The data collected in real time from COM port is generally obtained using Net beans and these collected data are saved in SQL database. The data that are collected in real time can be tracked by the travel agencies, public care centers, vehicle departure points. The data of the driver is monitored in a system using visual basic. From the system, the driver data is updated into the cloud. If the driver’s heartbeat goes abnormal, automatically the engines get slowed down completely. The data collected in real time are refined from Net beans in format of an excel file. These data are then processed to the R studio for data analytics. In the R studio, programming is done for both clustering and classification which are processed for abnormal or normal conditions. The final data of the driver which are collected are finally stored in a private cloud for easy access.