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Vehicle Carbon Emission Based Air Pollution Monitoring and Alert Using Deep Learning
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Ramasami S , Maha Vishnu G , Amal Raj Sanjay J and LogeshKannan M


This study was carried out to analyzethevariationsof hazardous pollutants like Carbon Monoxide (CO), CarbonOxides (COx), and Nitrogen Oxides (NOx) in Tamil Nadu.Theprogram focuses on using advanced techniques to improve airpollution monitoring and reporting based on carbon emissionsfromvehicles.Themaingoalistocreateanintelligentco mmunicationsystemthatmonitorsusingdeeplearning,analyzes, and reduces the impact of carbon emissions on thevehicle.Thesystemusesdeeplearningtechniquestoprocessan dinterpret large amounts of emissions data from a variety ofsources,includingroadsensorsandvehiclemonitoringequipme nt.Byintegratingadvancedneuralnetworks,thesystem can detect major vehicle emissions and identify emissionpatterns,enablingmonitoringandanalysis.Thesystemw illimmediately alert authorities and stakeholders when a carbon emission increaseisdetected.Thesewarningsarenecessarymeasuresforim mediateresolutionandcorrectionofenvironmentalimpact.Thesy stemalsoincludesvehicleidentificationandtrackingsystemstoen surecontinuousmonitoring of the person's vehicle and facilitate intervention. Itaims to contribute to environmental sustainability by providingbetterinformationonthesourceandimpactofairpollutio n. Keywords:Deeplearning,neural network,Tracking System,VehicleEmission.

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