With the current development of technology, smart mobile phone is widely used as a method of observing human behavior. With the taxi drivers on roads, the amount of road accidents have also increased. Automation is crucial as the random nature of the above-stated incidents. As the goal of this research, a novel approach, a mobile phone based taxi driver wellbeing monitoring system that is capable of automatically detecting drowsiness, emotional misbehavior and high speed driving is proposed to implement using Machine Learning. This document provides an outline of the proposed system and a summary of outcomes authors have achieved when training appropriate machine learning models to work with real-time data. Systems’ functionality includes identifying human sleepy eyes, irrational emotions and high speed using the mobile device.

Machine Learning drowsiness detection emotion detection mask detection taxy