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Artificial Intelligence-Based Solutions for Digital Music Education in 6G IOV Networks with Embedded Image Processing Using Convolutional Neural Networks
Yang Zhang and Shu Yu

Advancements in 6G technology, blockchain, and artificial intelligence (AI) have significantly impacted various sectors, notably the Internet of Vehicles (IoV) and digital music learning environments, due to their capabilities in secure data handling, real-time processing, and immersive content delivery. However, current IoV frameworks face data security, processing efficiency, and resource management challenges, crucial for sustaining high-speed, secure connectivity and practical digital music teaching tools. This paper proposes a blockchain-enhanced, AI-driven framework to improve security in 6G-enabled IoV networks while supporting embedded image processing for digital music teaching resources. The methodology involves integrating blockchain technology to secure data across IoV channels, utilizing Convolutional Neural Networks (CNNs) for high-accuracy image processing in digital music educational content, and employing 6G network protocols for enhanced data transmission. First, we implement a blockchain layer to provide decentralized security for IoV data transactions, protecting against unauthorized access. Secondly, the CNN-based AI module processes and categorizes digital music teaching materials precisely, allowing efficient content management. Thirdly, the 6G communication protocols enable fast data transmission, reducing latency and supporting real-time multimedia interaction. Finally, a resource management module optimizes bandwidth usage to facilitate uninterrupted learning experiences. Experimental results demonstrate the model’s success in enhancing network security, achieving over 95.6% accuracy in image processing, and significantly reducing latency in content transmission. Compared with existing models, the proposed system maintains high security, processing accuracy, and low latency in 6G-IoV networks. Future work will refine blockchain protocols to improve speed and efficiency while expanding AI capabilities to support broader educational applications in connected environments.

Keywords: blockchain, 6G networks, IoV, artificial intelligence, digital music teaching resources, embedded image processing convolutional neural networks