| Issue |
E3S Web Conf.
Volume 712, 2026
2026 16th International Conference on Future Environment and Energy (ICFEE 2026)
|
|
|---|---|---|
| Article Number | 07005 | |
| Number of page(s) | 6 | |
| Section | Data-Driven Energy Systems Management and Decision Support | |
| DOI | https://doi.org/10.1051/e3sconf/202671207005 | |
| Published online | 19 May 2026 | |
A telematics platform for enhancing green energy efficiency in logistics
1 Department of Computer Engineering, Khon Kaen University, Thailand.
2 Smart City Operation Center, Khon Kaen University, Thailand.
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
The transport logistics sector remains a significant contributor to global greenhouse gas emissions, primarily CO2, demanding an urgent transition towards green energy and enhanced operational efficiency. While fleet monitoring is common, effective management necessitates granular analysis of both fleet performance and specific driver behaviours. This paper presents the development and implementation of a novel Internet of Things (loT) platform, designed to capture and analyse real-time telematics data from transport vehicles. The primary innovation of this platform lies in its methodological framework, which moves beyond conventional GPS tracking to perform granular CO2 quantification. It achieves this by programmatically disaggregating telematics data into distinct operational states, notably 'engine idling' versus 'vehicle running'. This disaggregation enables the precise calculation of emissions from high-waste activities. By correlating this granular emissions data with driver-specific behaviours and route patterns, the system provides logistics managers with high-value, actionable insights to reduce energy consumption. The objectives are twofold: to facilitate targeted driver feedback for modifying inefficient practices and to identify opportunities for route optimization. This contributes directly to green energy adoption through measurable fuel savings and emission reductions, offering a scalable solution for sustainable logistics.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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