IEEE Access Special Section Editorial: Urban Computing and Intelligence

Rongbo Zhu, Lu Liu, Maode Ma, Hongxiang Li, Shiwen Mao
2021 IEEE Access  
EDITORIAL IEEE ACCESS SPECIAL SECTION EDITORIAL: URBAN COMPUTING AND INTELLIGENCE Urban computing utilizes unobtrusive and ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods to create win-winwin solutions which intelligently improve people's lives, urban environments, and city operation systems. With the help of cloud computing, the Internet of Things, device-todevice (D2D) communication, artificial intelligence (AI), big data, and
more » ... an computing and intelligence will bridge the gap of ubiquitous sensing, intelligent computing, cooperative communication, and mass data management technologies, to create novel solutions that improve urban environments, human life quality, and smart city systems. Thus, urban computing and intelligence has recently attracted significant attention from industry and academia for building smart cities. It is obvious that urban computing and intelligence will enable and promote a large class of applications, and has emerged with a great potential to change our lives and improve user experience. As the urban size increases, total costs and resource consumption, performance will decrease and the security of the systems will face serious threats. Recent advances in artificial intelligence (AI), cloud/fog/edge computing, big data, and novel communication techniques show that urban computing and intelligence still struggles with fundamental, long-standing problems. How to enhance distributed computing and processing performance with distributed machine learning (ML), common sense, intelligent interaction, data security, and novel applications is worth exploring. This Special Section aims to report high-quality research on recent advances toward the realization of artificial intelligence models, intelligent networking, heterogeneous data analytics, urban sensing and energy management, and so on, to cope with challenges in the real world. This Special Section has provided a platform for researchers and practitioners from both academia and industry in the area of urban computing and intelligence. In the article "CAD: Command-level anomaly detection for vehicle-road collaborative charging network," by Li et al., the authors discuss charging piles installed on roadside parking spaces and smart poles on the roadside of the internet electric vehicles. A command-level anomaly detection (CAD) method is proposed for a vehicle-road collaborative 130690 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 9, 2021
doi:10.1109/access.2021.3111669 fatcat:qmiy5ngnyvfcvbe5is7estlfou