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Driving is a complex activity with the continuously changing environment. Safe driving can be challenged by changes in drivers’ physical, emotional, and mental condition. Population in the developed world is aging, so the number of older drivers is increasing. Older drivers have relatively higher incidences of crashes precipitated by drivers’ medical emergencies when compared to another age group. On the elderly population, automakers are paying more attention to developing cars that can measure and monitor the drivers’ health status to protect them. In recent years, the automotive industry has been integrating health, wellness, and wellbeing technologies into cars with Internet of Things (IoT). A broad range of applications is possible for the IoT-based elderly smart healthcare monitoring systems.

IoT (Internet of things) is considered most innovative technology in smart healthcare monitoring system which is able to show real-time physiological parameters feed data to web cloud, analysis using machine learning, artificial intelligence and big data. Stroke is most deadly diseases and real-time monitoring is desired to detect stroke onset during regular activities. The aim of our study is to develop a Real-time health monitoring system for elderly drivers using air cushion seat and IoT devices in order to detect stroke onset during driving. We have also made a prototype of brain stroke detection system using Quad-chamber air cushion system and IoT devices. This system can measure ECG, EEG, heart rate, seat pressure balance data, face/eye tracking etc. using IoT sensors, compare real-time data with reference data, predict abnormality, generate alarm and send message to relatives and emergency services if any stroke onset happens in order to provide emergency assistance to driver.