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.
Monitoring Real-Time Fleet Emissions Through an Intelligent Fleet Management System
2024-09-24
9552699 byte
Conference paper
Electronic Resource
English
Intelligent fleet management system
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