Internet of Vehicles
PulseAugur coverage of Internet of Vehicles — every cluster mentioning Internet of Vehicles across labs, papers, and developer communities, ranked by signal.
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New WGAN framework uses RL and game theory for resource-constrained vehicles
Researchers have developed an adaptive multi-discriminator Wasserstein GAN (MD-WGAN) framework designed for resource-constrained Internet of Vehicles (IoV) environments. This framework integrates reinforcement learning …
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AI optimizes traffic signals, cutting delays and emissions
Researchers have developed a reinforcement learning (RL) system to optimize traffic signal control in urban intersections, particularly for IoT-enabled environments. The system, utilizing Proximal Policy Optimization (P…
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GANs enhance image transmission for connected vehicles
Researchers have developed a new generative adversarial network (GAN)-based semantic communication framework designed to improve image transmission efficiency and fidelity in the Internet of Vehicles (IoV). This framewo…
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HEART framework tackles multi-model training for vehicle AI
Researchers have developed a new framework called HEART to address the challenges of multi-model training in Hierarchical Federated Learning (HFL) for vehicle-edge-cloud architectures. This framework aims to minimize gl…
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New framework optimizes federated fine-tuning for energy-constrained vehicles
Researchers have developed a new framework for federated fine-tuning of foundation models in edge-assisted Internet of Vehicles (IoV) networks. This approach addresses challenges related to energy constraints, diverse t…
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DAIRE AI model offers real-time detection of vehicle network attacks
Researchers have developed DAIRE, a lightweight AI model designed to detect and classify cyberattacks on the Controller Area Network (CAN) within the Internet of Vehicles (IoV). This framework utilizes a specialized art…