Predictive Modelling of In-Vehicle CO2 Concentration Using Sensor Data Analytics

Research
14 Sep 2018

 

Divya Lohani, Anurag Barthwal and Debopam Acharya, "Predictive Modelling of In-Vehicle CO2 Concentration Using Sensor Data Analytics”, accepted in IEEE Sensors 2018, October 28-31, New Delhi, India.

In densely populated metropolitan cities, people spend an average of 45 – 150 minutes inside a vehicle commuting to their workplace. Most of these travellers often experiences short term health conditions like drowsiness, breathlessness, discomfort and headache. Many accidents have been reported due to drowsiness while driving. There has been considerable increase in the number of death/choking cases reported due to CO2 buildup inside the vehicle. This work attempts to use a sensing system that can be retrofitted in any vehicle to measure the CO2 levels inside it and use this sensed data to perform predictive analysis inside the vehicle chamber.

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