Page 136 - Kaleidoscope Academic Conference Proceedings 2022
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Session 3: Services in future networks

             S3.1      Research on asset administration shell standard system architecture
                       Quanbo Lu (China University of Geosciences, Beijing,  China); Xinqi Shen (China Academy of
                       Information and Communications Technology, China);  Mei Li (China University of Geoscience,
                       Beijing, China)


                       Asset Administration Shell (AAS) is an important enabling technology to implement digital twins
                       for Industry 4.0(I4.0). It establishes cross-company interoperability. However, in the process of
                       AAS application, there is a lack of AAS standard references. Aiming at the problem of lacking
                       AAS  standardization,  this  paper  analyzes  the  requirement  of  AAS  standards  from  three
                       perspectives: AAS concept, the implementation of AAS key technologies, and AAS applications.
                       As a basis for research to establish the three dimensions of the standardized architecture, AAS
                       standard architecture is formed from the integration of architecture under different perspectives.
                       This provides guidance for the study and formulation of standards related to AAS standardization.

             S3.2      Research and standardization requirements for 5G network peak control technology in video
                       transmission
                       Zhiji  Deng  (Zhejiang  Provincial  Key  Laboratory  of  Harmonized  Application  of  Vision  &
                       Transmission, China and Zhejiang Dahua Technology Co. Ltd, China); Zhewei Fu, Ming Liu and
                       Xiangyu  Qu  (Zhejiang  Dahua  Technology  Co.  Ltd,  China);  Dong  Ding  (China  Mobile
                       Communications Corporation, China); Qi Ye, Weisheng Kong, Fei Wang, Jinyu Zhang, Hui Wan
                       (Zhejiang  Dahua  Technology  Co.  Ltd,  China);  Jian  Lou  (China  Mobile  Communications
                       Corporation, China)

                       The 5G network peak control technology in video transmission scenarios is used to solve the
                       problem of violent fluctuations in network peaks caused by the collision of I-frames (key frames)
                       during multichannel video transmission. Based on the research of key technologies such as I-frame
                       collision detection and network peak shift scheduling, through the Multiaccess Edge Computing
                       (MEC) external interface, the network data and video management system is opened to effectively
                       smooth the network peak during multichannel video transmission, and realize the number and
                       bandwidth  of  5G  terminal  access  under  5G  base  stations.  The  improved  utilization  rate  is
                       conducive to the large-scale promotion of 5G video surveillance scenarios.

             S3.3      A comparative analysis of Augmented Reality frameworks aimed at diverse computing
                       applications*
                       Mfundo A. Maneli and Omowunmi E. Isafiade (University of the Western Cape, South Africa)


                       Immersive systems such as Augmented Reality (AR) and Virtual Reality (VR) have proven useful
                       in diverse computing domains. However, there is little effort on accuracy measurements within
                       AR applications, which could greatly impact outcomes and decisions in certain domains, such as
                       crime scene investigations, among others. This paper aims to analyze and evaluate two existing
                       prominent AR frameworks, ARCore and ARKit, which support the development of diverse mobile
                       computing applications for immersive systems. This research developed prototype applications
                       and conducted comparison tests of measurement accuracy within the applications. The accuracy
                       was tested using four distance criteria across six different devices, spanning ARCore and ARKit
                       frameworks. A control experiment was used to benchmark the measurement accuracy. Relatively,
                       an instance of the experiment presented ARCore as reliable. Overall, ARKit proved to be more
                       accurate between the two frameworks, with an average accuracy of 99.36% as opposed to 89.42%
                       scored by ARCore. The obtained results can give insight on the choice of framework to consider
                       during AR application development for a specific domain, hence boosting quality of experience.










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