A Novel Approach to Vehicular CO2 Emission Predictive Modelling

S. Sahay, P. M. Pawar, D. N. Sonawane

Abstract


Climate change today is a global crisis requiring grave concern to the extent that governments worldwide have realized that if this problem is left unmitigated, catastrophic events may occur, ultimately jeopardizing humanity’s survival. Climate change is primarily due to too much presence of greenhouse gases, mainly CO2, in the atmosphere. Vehicular exhaust is one of the main contributors to the emissions of CO2. Although specialized sensors exist for CO2 monitoring, they are inefficient and not highly prevalent. This study suggests a workable, pragmatic, and feasible monitoring system for vehicular CO2 emissions that involves an LSTM network trained and tested based on OBD-II data available in the public domain. Also, this work presents a comparison of the proposed model with a latter-day solution. This proposed system could be deployed on the cloud, with the IoT-based dongles put in the vehicles that can collect in-sensor data from vehicles and send them to the cloud for processing the data, where the deployed model can give real-time predictions of CO2 emissions.

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References


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