Real-Time Smart Optimization of Multimodal Node Operations: Toward Greener and More Efficient Logistics Networks

Multimodal logistics transport is a huge sector all over the world, and despite many problems related to inefficiencies, supply chain disruptions, environmental concerns, etc., this sector is constantly growing. This research is about how dynamic optimization, and advanced digital systems like artificial intelligence (AI), Internet of Things (IoT), machine learning (ML), and blockchain can revolutionize this massive industry and improve the environmental performance of the system, which is crucial for the system to perform in the long run. This research also highlights how conceptual and critical digital layered architecture can be made for this system using the transformative potential of Industry 4.0 technologies. The practical aspect of this research showcases the IoT-based simulator using Teltonika FMC003 devices, connected through a Python-based Transmission Control Protocol (TCP) server and integrated with the ThingsBoard IoT monitoring platform. The simulator offers real-time fleet management, GPS tracking, reliability, and robust responsiveness for the fleet management system. Digitized multimodal transport is a significant step in transforming traditional logistics operations into intelligent, efficient, resilient, and sustainable operations with low carbon footprints in the transport sector.