Abstract: Vehicles have become the main part of regular life. Situations and circumstances demand the usage of vehicles in this urban life. Transportation carbon emission is a significant contributor to the increase of greenhouse gases, which directly threatens the change of climate and human health. Under the pressure of the environment, it is very important to measure transportation carbon emissions on a real-time basis. We get the transportation carbon emission information by calculating the combustion of fossil fuel in the transportation sector. In this paper, we predict the vehicle's real-time carbon emission using an MQ2 Gas sensor based on the Support Vector Machine (SVM) algorithm to observe datasets in the city, and the GPS data helps to locate the vehicle's current location. An initial warning is given to the driver regarding the amount of CO2 gas with the help of an LCD, buzzer, and later the same information is transferred to the Police Control Room in case of negligence. Here the hardware (carbon emission sensor) device which connected to the android application, and the application sends the data to the cloud server (RTO) through the Global System of Mobile Communication (GSM). When there is an excess amount of CO2 release from the vehicle, an alert message is sent to the vehicle owner.

Keywords: CO2, GSM, MQ2 Gas Sensor, GPS, Support Vector Machine (SVM).

PDF | DOI: 10.17148/IJARCCE.2021.10333

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