AI/machine learning has demonstrated significant success in transforming massive and complex data sets into highly accurate knowledge as outcomes, greatly facilitating analysis, intelligence, decision making, and automation across a number of diverse systems. Through integration with advances in data processing, computing, and networking technologies, AI/machine learning is capable of providing a viable means for carrying out big modeling and intelligence and has achieved significant success in a number of fields. However, in order to achieve an AI-enabled Internet of Dependable and Controllable Things, AI/machine learning in Internet-of-Things (IoT) systems must overcome significant challenges and exceptional requirements for connectivity, latency, scalability, accessibility, security, and resiliency that IoT systems pose. Thus, the seamless integration of AI/machine learning into IoT systems creates tremendous opportunities for new research and necessitates interdisciplinary efforts to address these challenges.

中文翻译：

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客座社论：人工智能赋能的可靠可控物联网特刊


人工智能/机器学习在将大量复杂的数据集转化为高度准确的知识结果方面取得了巨大成功，极大地促进了跨多个不同系统的分析、智能、决策和自动化。通过与数据处理、计算和网络技术的进步相结合，人工智能/机器学习能够为进行大建模和智能提供可行的手段，并在多个领域取得了重大成功。然而，为了实现基于人工智能的可靠可控物联网，物联网 (IoT) 系统中的人工智能/机器学习必须克服连接性、延迟、可扩展性、可访问性、安全性和可用性方面的重大挑战和特殊要求。物联网系统带来的弹性。因此，人工智能/机器学习与物联网系统的无缝集成为新研究创造了巨大的机会，并且需要跨学科的努力来应对这些挑战。