AI/ML-Enabled Intelligent IoT Connectivity Chip Design for High-Availability Computing System in Hyperscale Cloud and SDV-EV Infrastructure
Keywords:
Artificial intelligence, Electric vehicle infrastructure, Internet of things, Real-time monitoring, System-on-chipAbstract
The rapid growth of the Internet of Things (IoT) ecosystem and the increasing demand for Electric Vehicles (EVs) have driven the need for efficient, scalable, and high-performance hardware solutions. Artificial Intelligence (AI) and Machine Learning (ML) have become key enablers of intelligent decision-making and optimization in hyperscale-cloud and EV infrastructure. To fully harness the potential of AI/ML in IoT systems, specialized silicon chips System-on-Chip (SoC) solutions are essential. These SoCs must integrate data processing, connectivity, and energy management capabilities to ensure high availability and performance in various environments. This paper explores the role of AI/ML-enabled IoT connectivity chip design for hyperscale-cloud and EV infrastructure, emphasizing the integration of AI/ML in silicon design and providing a comparative analysis of competitive silicon architectures for high-availability computing systems. As the United States accelerates its transition to sustainable transportation, the adoption of EVs relies on the efficiency, scalability, and reliability of the supporting charging infrastructure. The convergence of AI, ML, and IoT collectively known as AIoT offers the potential to optimize EV charging stations, enhance energy distribution, and drive technological innovation. The paper highlights how AIoT-powered intelligent connectivity and high-availability systems can optimize EV charging networks, supporting economic growth and the successful adoption of Software Defined Vehicle Infrastructure (SDV)-EVs.
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