A Survey of Internet of Things and Cyber-Physical Systems: Standards, Algorithms, Applications, Security, Challenges, and Future Directions

Inf. Comput. Pub Date : 2023-07-08 DOI:10.3390/info14070388
Kwok Tai Chui, B. B. Gupta, Jiaqi Liu, Varsha Arya, N. Nedjah, Ammar Almomani, Priyanka Chaurasia
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引用次数: 1

Abstract

The smart city vision has driven the rapid development and advancement of interconnected technologies using the Internet of Things (IoT) and cyber-physical systems (CPS). In this paper, various aspects of IoT and CPS in recent years (from 2013 to May 2023) are surveyed. It first begins with industry standards which ensure cost-effective solutions and interoperability. With ever-growing big data, tremendous undiscovered knowledge can be mined to be transformed into useful applications. Machine learning algorithms are taking the lead to achieve various target applications with formulations such as classification, clustering, regression, prediction, and anomaly detection. Notably, attention has shifted from traditional machine learning algorithms to advanced algorithms, including deep learning, transfer learning, and data generation algorithms, to provide more accurate models. In recent years, there has been an increasing need for advanced security techniques and defense strategies to detect and prevent the IoT and CPS from being attacked. Research challenges and future directions are summarized. We hope that more researchers can conduct more studies on the IoT and on CPS.
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物联网和网络物理系统综述:标准、算法、应用、安全、挑战和未来方向
智慧城市愿景推动了物联网(IoT)和网络物理系统(CPS)等互联技术的快速发展和进步。本文对近年来(2013年至2023年5月)物联网和CPS的各个方面进行了调查。它首先从确保具有成本效益的解决方案和互操作性的行业标准开始。随着大数据的不断增长,大量未被发现的知识可以被挖掘并转化为有用的应用。机器学习算法通过分类、聚类、回归、预测和异常检测等公式率先实现各种目标应用。值得注意的是,人们的注意力已经从传统的机器学习算法转向了高级算法,包括深度学习、迁移学习和数据生成算法,以提供更准确的模型。近年来,越来越需要先进的安全技术和防御策略来检测和防止物联网和CPS受到攻击。总结了研究面临的挑战和未来的发展方向。我们希望更多的研究人员能够对物联网和CPS进行更多的研究。
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