Leveraging IT Solutions for Enhancing Reliability in Piggyback Transportation Systems

Abstract

This paper addresses the operational inefficiencies in piggyback transportation systems caused by unreliable maintenance procedures and limited cargo tracking capabilities. We propose an integrated IT framework that leverages Artificial Intelligence (AI), the Internet of Things (IoT), and Blockchain technologies. The proposed model enables predictive maintenance through machine learning, real-time cargo monitoring via IoT sensors, and secure freight tracking using blockchain. Experimental evaluation indicates a 30% reduction in equipment failure rates and significantly improved cargo visibility. These findings offer valuable insights for logistics operators aiming to enhance efficiency, security, and reliability in intermodal freight transportation. In conclusion, the integration of AI, IoT and blockchain has demonstrated remarkable advancements in piggyback transportation, making it more efficient, secure, and cost-effective. Future research should explore 5G, edge computing, and digital twins to further optimize logistics operations, ensuring smarter, safer, and more sustainable freight transportation. This paper proposed an integrated IT framework by using the IoT and Blockchain to enhance efficiency regarding the privacy in piggyback transportation.