Predictive Modelling of In-Vehicle CO 2 Concentration Using Sensor Data Analytics

TLDR: In this article, the authors use a sensing system that can be retrofitted in any old or new vehicle to measure the CO 2 level inside the vehicle and use this sensed data to perform statistical and stochastic analysis of the growth pattern of CO 2 inside the chamber.

Abstract: In densely populated metropolitan cities, people spend an average of 45–150 minutes inside a vehicle commuting to their workplace. Most of these travelers 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 CO 2 buildup inside the vehicle. Even though Vehicle Indoor Air Quality is an important parameter, the general awareness about it is very low, and only few high end new models of automobiles have indoor air quality sensing systems, with limited capability. This paper attempts to use a sensing system that can be retrofitted in any old or new vehicle to measure the CO 2 level inside the vehicle and use this sensed data to perform statistical and stochastic analysis of the growth pattern of CO 2 inside the vehicle chamber.