Table of Content

AI Powered Human-centric Computing with Cloud and Edge

Submission Deadline: 01 March 2023 (closed)

Guest Editors

Prof. Lianyong Qi, China University of Petroleum (East China), China.
Dr. Quanwang Wu, Chongqing University, China.
Dr. Dharavath Ramesh, Indian Institute of Technology (ISM), India. 
Dr. Zhizhong Liu, Yantai University, China.
Dr. Yang Xu, Hunan University, China.


In the past decade, human-centric computing (HCC) has emerged as a cross-disciplinary research domain that enables the effective integration of various human-related computational elements, benefiting the interactions and collaborations among the physical devices, cyber space and people significantly. Through intelligent HCC techniques, software and hardware engineers can develop various human-computer applications conveniently to satisfy the users’ sophisticated functional and non-functional requirements.  However, HCC applications have been generating an unprecedented volume of industrial data and therefore, require the support of powerful computing and storage infrastructures.  Fortunately, modern computing paradigms, e.g., cloud and edge, provide a promising way to provision HCC applications the cloud/edge resources in an economic and flexible manner. The adaption of cloud/edge computing to HCC applications is a fundamental challenge and raise a variety of issues, e.g., time-efficient data transmission, energy-aware resource offloading, secure communications & collaborations, and so on.  Recently, Artificial Intelligence (AI) has emerged as one of the key technologies to realize intelligent cloud/edge data processing. AI algorithms have the capability to process the streaming data generated at cloud/edge networks, and provide powerful tools to deal with complex big data analytics. Therefore, the adaptation of AI-based methods is highly demanded to achieve their full potentials in cloud/edge-based HCC applications. The security and privacy issues also call for efforts in order to guarantee service quality delivered by cloud/edge-based HCC applications.


• Human-centered semantic analyses in Cloud/Edge
• Knowledge-driven human-computer interaction in Cloud/Edge
• Collaborative systems and decisions in Cloud/Edge
• Intelligent big data analyses in HCC with Cloud/Edge
• Security, privacy and trust in Cloud/Edge
• AI algorithms for multi-agent systems in HCC
• People-cyber-physical interactions in Cloud/Edge
• AI powered smart applications in HCC
• Computation offloading and cost optimization in Cloud/Edge
• Intelligent interfaces and user modeling
• Smart service quality optimization in HCC with Cloud/Edge
• Multimedia applications in HCC with Cloud/Edg

Published Papers

  • Open Access


    A Task-Oriented Hybrid Cloud Architecture with Deep Cognition Mechanism for Intelligent Space

    Yongcheng Cui, Guohui Tian, Xiaochun Cheng
    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1385-1408, 2023, DOI:10.32604/cmc.2023.040246
    (This article belongs to this Special Issue: AI Powered Human-centric Computing with Cloud and Edge)
    Abstract Intelligent Space (IS) is widely regarded as a promising paradigm for improving quality of life through using service task processing. As the field matures, various state-of-the-art IS architectures have been proposed. Most of the IS architectures designed for service robots face the problems of fixed-function modules and low scalability when performing service tasks. To this end, we propose a hybrid cloud service robot architecture based on a Service-Oriented Architecture (SOA). Specifically, we first use the distributed deployment of functional modules to solve the problem of high computing resource occupancy. Then, the Socket communication interface layer is designed to improve the… More >

  • Open Access


    Ship Detection and Recognition Based on Improved YOLOv7

    Wei Wu, Xiulai Li, Zhuhua Hu, Xiaozhang Liu
    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 489-498, 2023, DOI:10.32604/cmc.2023.039929
    (This article belongs to this Special Issue: AI Powered Human-centric Computing with Cloud and Edge)
    Abstract In this paper, an advanced YOLOv7 model is proposed to tackle the challenges associated with ship detection and recognition tasks, such as the irregular shapes and varying sizes of ships. The improved model replaces the fixed anchor boxes utilized in conventional YOLOv7 models with a set of more suitable anchor boxes specifically designed based on the size distribution of ships in the dataset. This paper also introduces a novel multi-scale feature fusion module, which comprises Path Aggregation Network (PAN) modules, enabling the efficient capture of ship features across different scales. Furthermore, data preprocessing is enhanced through the application of data… More >

  • Open Access


    Application of Blockchain Sharding Technology in Chinese Medicine Traceability System

    Fuan Xiao, Tong Lai, Yutong Guan, Jiaming Hong, Honglai Zhang, Guoyu Yang, Zhengfei Wang
    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 35-48, 2023, DOI:10.32604/cmc.2023.038937
    (This article belongs to this Special Issue: AI Powered Human-centric Computing with Cloud and Edge)
    Abstract Traditional Chinese Medicine (TCM) is one of the most promising programs for disease prevention and treatment. Meanwhile, the quality of TCM has garnered much attention. To ensure the quality of TCM, many works are based on the blockchain scheme to design the traceability scheme of TCM to trace its origin. Although these schemes can ensure the integrity, sharability, credibility, and immutability of TCM more effectively, many problems are exposed with the rapid growth of TCM data in blockchains, such as expensive overhead, performance bottlenecks, and the traditional blockchain architecture is unsuitable for TCM data with dynamic growth. Motivated by the… More >

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