Monitoring fleet vehicle operation is a crucial aspect of fleet management systems, typically involving the analysis of GPS and/or on-board diagnostics (OBD) data from fleet vehicles. Given the increasing emphasis on environmental responsibility within fleet management, there is a growing demand for monitoring vehicle emissions. This study aims to integrate machine learning models for emission estimation into an intelligent fleet management system (IFMS) designed for light-duty vehicle fleets. These emission models are trained using real-driving data from fleet vehicles and have the capability to provide real-time emission estimates based on the OBD data of each vehicle. The developed IFMS is hardware-agnostic, allowing for wireless data collection, and enables the real-time reporting of fleet emissions, including CO2, CO, HC, and NOx.


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    Title :

    Monitoring Real-Time Fleet Emissions Through an Intelligent Fleet Management System




    Publication date :

    2024-09-24


    Size :

    9552699 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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