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From the recent advances in Driver Monitoring Systems (DMS) from automotive domain, research on Human Computer Interaction (HCI) based on emotion analytics has gained good interest from the research circles. Distraction and drowsiness will be causing more percentage of traffic accidents, but with the use of advanced DMS technology, we can significantly reduce these distractions and can make the driving a safer activity. Our proposed solution/approach with disguised emotion detection with analytics is enabled by machine learning and image processing algorithms to ensure that the detection of drowsiness or distraction is very accurate. The proposed method will inform the HMI system to provide an alert to wake up the driver if he or she is in drowsy state or take the proactive/necessary actions with the help of active safety systems. Emotion analytics is a technique which is used to analyze the emotion of an individual. It is used to recognize the change in the emotion.

In recent years, research on Human Computer Interaction (HCI) based on emotion recognition using behavioral and physiological signals have attracted immense interest in research circles. Lighting inside the automotive make us feel differently about our driving and how we feel or behave. From the literature, it is observed that ambient lighting makes an impact on the driving experience and it delivers an emotional atmosphere inside the automotive. Driving fatigue can be reduced if the lighting is controlled properly. These days, ambient interior lighting can be considered to be the point of fashion for high end automotive and also impact driver’s mood and comfort. There are different types of automotive based lighting automation systems available but emotion based control is in early or nascent stages of research. Speech controlled light control systems, control the light by the recognition of speech of the user and by using facial expressions lighting can be controlled.