Cognitive Decision Support Framework for Internet of Vehicles in 6G Networks through Machine Learning and Edge Intelligence

This article is a development of a Cognitive Decision Support Framework (CDSF) of the Internet of Vehicles (IoV) application with the use of 6 G networks, machine learning and edge intelligence to provide real-time communication and autonomous decision-making to vehicles. The framework uses federated learning, situation-based reasoning, and cognition nodes as the source of minimizing response time and maximizing resource optimization. The experimental outcomes represent the correct decision in the best scenario of 31.6 % and convey the information in$\mathbf{4 2 \%}$less time and require$\mathbf{2 8 \%}$less power as compared to the traditional IoV systems. The model recorded the F1 score at 0.94 on dynamic traffic of the system as a proof of it being effective when dealing with changing mobility environments. This publication makes the CDSF a versatile, strong, and uncompromising safe base design to$6 \mathrm{G}-\text{IoV}$ecosystems to enable smart coordination among the vehicles in smart transport networks.