Intelligent Distributed Computing and Systems (INDUCE) Research Laboratory, Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Abu Dhabi 15551, United Arab Emirates.
National Water and Energy Center, United Arab Emirates University, Abu Dhabi 15551, United Arab Emirates.
Sensors (Basel). 2022 Aug 1;22(15):5750. doi: 10.3390/s22155750.
The recent upsurge of smart cities' applications and their building blocks in terms of the Internet of Things (IoT), Artificial Intelligence (AI), federated and distributed learning, big data analytics, blockchain, and edge-cloud computing has urged the design of the upcoming 6G network generation, due to their stringent requirements in terms of the quality of services (QoS), availability, and dependability to satisfy a Service-Level-Agreement (SLA) for the end users. Industries and academia have started to design 6G networks and propose the use of AI in its protocols and operations. Published papers on the topic discuss either the requirements of applications via a top-down approach or the network requirements in terms of agility, performance, and energy saving using a down-top perspective. In contrast, this paper adopts a holistic outlook, considering the applications, the middleware, the underlying technologies, and the 6G network systems towards an intelligent and integrated computing, communication, coordination, and decision-making ecosystem. In particular, we discuss the temporal evolution of the wireless network generations' development to capture the applications, middleware, and technological requirements that led to the development of the network generation systems from 1G to AI-enabled 6G and its employed self-learning models. We provide a taxonomy of the technology-enabled smart city applications' systems and present insights into those systems for the realization of a trustworthy and efficient smart city ecosystem. We propose future research directions in 6G networks for smart city applications.
近年来，物联网 (IoT)、人工智能 (AI)、联邦和分布式学习、大数据分析、区块链和边缘云计算等智能城市应用及其构建块的兴起，促使人们设计即将到来的 6G 网络，因为这些应用对服务质量 (QoS)、可用性和可靠性提出了严格的要求，以满足最终用户的服务级别协议 (SLA)。工业界和学术界已经开始设计 6G 网络，并提出在其协议和操作中使用人工智能。关于该主题的已发表论文要么通过自上而下的方法讨论应用程序的要求，要么从灵活性、性能和节能的角度使用自下而上的观点讨论网络要求。相比之下，本文采用整体观点，考虑应用程序、中间件、底层技术和 6G 网络系统，以实现智能和集成的计算、通信、协调和决策生态系统。特别是，我们讨论了无线网络代发展的时间演变，以捕捉导致从 1G 到 AI 支持的 6G 的网络代系统发展的应用程序、中间件和技术要求，以及其采用的自学习模型。我们对基于技术的智能城市应用系统进行了分类，并深入了解这些系统，以实现值得信赖和高效的智能城市生态系统。我们为智能城市应用的 6G 网络提出了未来的研究方向。
