This study examines the integration of Internet of Things (IoT) and Green Vehicle Routing Problems (GVRP) to create modern, eco-friendly fleet management system that overcomes the limitations of traditional system through real-time data analytics, predictive maintenance, and optimized decision-making. While existing research on GVRP focuses on theoretical route optimizations, reductions in fuel consumption and greenhouse gas emissions, incorporating real-time IoT data can further aid in measuring these impacts accurately, and understanding their combined potential. In this novel study, the proposed system integrates Teltonika FMC003 telematics device, cloud computing, and GVRP algorithms to promote sustainable and cost-effective advanced fleet management.
Advanced Fleet Management Systems: IoT and GVRP for Greener Logistics
Zahid A.;Petrillo A.;De Felice F.;Forcina A.
2025-01-01
Abstract
This study examines the integration of Internet of Things (IoT) and Green Vehicle Routing Problems (GVRP) to create modern, eco-friendly fleet management system that overcomes the limitations of traditional system through real-time data analytics, predictive maintenance, and optimized decision-making. While existing research on GVRP focuses on theoretical route optimizations, reductions in fuel consumption and greenhouse gas emissions, incorporating real-time IoT data can further aid in measuring these impacts accurately, and understanding their combined potential. In this novel study, the proposed system integrates Teltonika FMC003 telematics device, cloud computing, and GVRP algorithms to promote sustainable and cost-effective advanced fleet management.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
