Internet Of Vehicles Projects for M.E, M.Tech, Masters, MS abroad, and PhD students. These Internet Of Vehicles ieee projects are implemented with future work and extension for final year project submission with research paper publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Internet Of Vehicles Projects
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Hierarchical Reinforcement Learning for Multi-Layer Multi-Service NonTerrestrial Vehicular Edge Computing
This project focuses on improving computing for smart vehicles. It combines ground-based and satellite edge computing to help vehicles process data faster and in more areas. The system uses machine learning to decide where and how much data to process for lower delay and energy use. Simulations show that this approach works better than existing methods. -
Multi-Objective Secure Task Offloading Strategy for Blockchain-Enabled IoV-MEC Systems: A Double Deep Q-Network Approach
This project focuses on improving communication between connected vehicles using the Internet of Vehicles. It introduces a smart system that makes real-time decisions to save energy, reduce delays, and lower costs. The approach uses advanced learning algorithms and blockchain to keep data secure and reliable. Tests showed it performs better than existing methods in energy use, speed, and overall efficiency. -
Research on Task-Offloading Delay in the IoV Based on a Queuing Network
This project studies how vehicles can send computing tasks to nearby servers to get results faster. It finds the best way to balance the workload on servers so that tasks are completed quickly and fairly. The study also looks at how the number of vehicles and servers affects task delays. The results help improve response time for computing tasks in vehicle networks. -
Secure Data Dissemination Scheme for Digital Twin Empowered Vehicular Networks in Open RAN
This project focuses on making communication between smart vehicles safer and more reliable. It creates a system where vehicles can verify each other and trust the information they share. It uses virtual models of the network, machine learning to spot unusual activity, and blockchain to confirm data. Tests show that this approach works better than many existing methods.
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