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Volume 9 Issue 12
Dec.  2022

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2022  >  9(12): 2047-2054
Y. Shen, Y. H. Liu, Y. L. Tian, and X. X. Na, "Parallel Sensing in Metaverses: Virtual-Real Interactive Smart Systems for “6S” Sensing, " IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp.2047-2054, Dec. 2022. doi: 10.1109/JAS.2022.106115
Citation: Y. Shen, Y. H. Liu, Y. L. Tian, and X. X. Na, "Parallel Sensing in Metaverses: Virtual-Real Interactive Smart Systems for “6S” Sensing, " IEEE/CAA J. Autom. Sinica, vol. 9, no. 12, pp.2047-2054, Dec. 2022. doi: 10.1109/JAS.2022.106115
shu

Parallel Sensing in Metaverses: Virtual-Real Interactive Smart Systems for "6S" Sensing

doi: 10.1109/JAS.2022.106115
  • 1.

    School of Artificial Intelligence, University of Chinese Academy of Science, Beijing 100190, China

  • 2.

    The State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing 100190, China

  • 3.

    Department of Engineering, University of Cambridge, Trumpington Street, CB2 1PZ, United Kingdom

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    Abstract
  • In the construction of Metaverses, sensors that are referred to as the "bridge of information transmission", play a key role. The functionality and efficiency of today's sensors, which operate in a manner similar to physical sensing, are frequently constrained by their hardware and software. In this research, we proposed the Parallel Sensing framework, which includes background, concept, basic methods and typical application of parallel sensing. In our formulation, sensors are redefined as the integration of real physical sensors and virtual software-defined sensors based on parallel intelligence, in order to boost the performance of the sensors. Each sensor will have a parallel counterpart in the virtual world within the framework of parallel sensing. Digital sensors serve as the brain of sensors and maintain the same properties as physical sensors. Parallel sensing allows physical sensors to operate in discrete time periods to conserve energy, while cloud-based descriptive, predictive, and prescriptive sensors operate continuously to offer compensation data and serve as guardians. To better illustrate parallel sensing concept, we show some example applications of parallel sensing such as parallel vision, parallel point cloud and parallel light fields, both of which are designed by construct virtual sensors to extend small real data to virtual big data and then boost the performance of perception models. Experimental results demonstrate the effective of parallel sensing framework. The interaction between the real and virtual worlds enables sensors to operate actively, allowing them to intelligently adapt to various scenarios and ultimately attain the goal of "Cognitive, Parallel, Crypto, Federated, Social and Ecologic" 6S sensing.

     

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    • References(40)
  • [1]
    G. C. Burdea et al. , Virtual reality technology. John Wiley & Sons, 2003.
    [2]
    M. M. Hassan et al. , "Guest Editorial for Special Issue on Blockchain for Internet-of-Things and Cyber-Physical Systems, " IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 12, p. 1867, 2021. doi: 10.1109/JAS.2021.1004219
    [3]
    T. Dillon et al., "Cloud computing: issues and challenges, " in 2010 24th IEEE international conference on advanced information networking and applications. IEEE, 2010, pp. 27–33.
    [4]
    Q. Wang et al. , "Digital Twin for Human-Robot Interactive Welding and Welder Behavior Analysis, " IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 2, pp. 334–343, 2021. doi: 10.1109/JAS.2020.1003518
    [5]
    X. Wang et al. , "Acp-based social computing and parallel intelligence: Societies 5.0 and beyond, " CAAI Transactions on Intelligence Technology, vol. 1, no. 4, pp. 377–393, 2016. doi: 10.1016/j.trit.2016.11.005
    [6]
    F. -Y. Wang et al. , "Parallel driving in CPSS: A unified approach for transport automation and vehicle intelligence, " IEEE/CAA Journal of Automatica Sinica, vol. 4, no. 4, pp. 577–587, 2017. doi: 10.1109/JAS.2017.7510598
    [7]
    A. Dosovitskiy et al., "CARLA: An open urban driving simulator, " in Conference on robot learning. PMLR, 2017, pp. 1–16.
    [8]
    Z. Song et al., "Omniverse-opends: Enabling agile developments for complex driving scenarios via reconfigurable abstractions, " in International Conference on Human-Computer Interaction, 2022.
    [9]
    B. R. Kent, 3D scientific visualization with blender. Morgan & Claypool Publishers San Rafael, CA, USA, 2015.
    [10]
    F. -Y. Wang, "Parallel Sensing and Parallel Blockchain for Transportation 5.0: From RFID to IoT for ITS in CPSS, " in The 11th Annual IEEE International Conference on RFID. IFAC, 2017.
    [11]
    X. Li et al. , "From features engineering to scenarios engineering for trustworthy AI: I & I, C & C, and V & V, " IEEE Intelligent Systems, vol. 37, no. 4, pp. 18–26, 2022. doi: 10.1109/MIS.2022.3197950
    [12]
    H. Lu et al. , "Guest editorial for special issue on cognitive computing for collaborative robotics, " IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 7, p. 1221, 2021. doi: 10.1109/JAS.2021.1004042
    [13]
    F. -Y. Wang et al. , "Steps toward parallel intelligence, " IEEE/CAA Journal of Automatica Sinica, vol. 3, no. 4, pp. 345–348, 2016. doi: 10.1109/JAS.2016.7510067
    [14]
    S. Wang et al. , "Decentralized autonomous organizations: Concept, model, and applications, " IEEE Transactions on Computational Social Systems, vol. 6, no. 5, pp. 870–878, 2019. doi: 10.1109/TCSS.2019.2938190
    [15]
    F. -Y. Wang, "The engineering of intelligence: DAO to I & I, C & C, and V & V for intelligent systems, " The International Journal of Intelligent Control and Systems, vol. 1, no. 3, pp. 1–5, 2021.
    [16]
    L. Li et al. , "A review of applications in federated learning, " Computers & Industrial Engineering, vol. 149, p. 106854, 2020.
    [17]
    F. -Y. Wang et al. , "Parallel ecology for intelligent and smart cyber–physical–social systems, " IEEE Transactions on Computational Social Systems, vol. 7, no. 6, pp. 1318–1323, 2020. doi: 10.1109/TCSS.2020.3044129
    [18]
    F. -Y. Wang, "Parallel system methods for management and control of complex systems, " CONTROL AND DECISION. , vol. 19, pp. 485–489, 2004.
    [19]
    Y. Liu et al. , "Metaradars: Acp-based intelligent radar systems in metaverses, " Journal of Intelligent Science and Technology, vol. 2, no. 1, pp. 12–17, 2022.
    [20]
    J. Mei et al. , "Incorporating human domain knowledge in 3-d lidar-based semantic segmentation, " IEEE Transactions on Intelligent Vehicles, vol. 5, no. 2, pp. 178–187, 2020. doi: 10.1109/TIV.2019.2955851
    [21]
    E. Asher et al. , "Methods and models for simulating autonomous vehicle sensors, " IEEE Transactions on Intelligent Vehicles, vol. 5, no. 4, pp. 684–692, 2020. doi: 10.1109/TIV.2020.3003524
    [22]
    T. Hanke et al., "Generation and validation of virtual point cloud data for automated driving systems, " in 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2017, pp. 1–6.
    [23]
    J. Thieling et al. , "Scalable and physical radar sensor simulation for interacting digital twins, " IEEE Sensors Journal, vol. 21, no. 3, pp. 3184–3192, 2020.
    [24]
    T. A. Wheeler et al., "Deep stochastic radar models, " in 2017 IEEE Intelligent Vehicles Symposium (Ⅳ). IEEE, 2017, pp. 47–53.
    [25]
    R. Weston et al., "There and back again: Learning to simulate radar data for real-world applications, " in 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2021, pp. 12 809–12 816.
    [26]
    B. Mildenhall et al. , "NeRF: Representing scenes as neural radiance fields for view synthesis, " Communications of the ACM, vol. 65, no. 1, pp. 99–106, 2021.
    [27]
    W. Zhu et al. , "Applications and research trends of digital human models in the manufacturing industry, " Virtual reality & intelligent hardware, vol. 1, no. 6, pp. 558–579, 2019.
    [28]
    I. Ahmed et al. , "Towards collaborative robotics in top view surveillance: A framework for multiple object tracking by detection using deep learning, " IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 7, pp. 1253–1270, 2021. doi: 10.1109/JAS.2020.1003453
    [29]
    Y. Tian et al. , "Training and testing object detectors with virtual images, " IEEE/CAA Journal of Automatica Sinica, vol. 5, no. 2, pp. 539–546, 2018. doi: 10.1109/JAS.2017.7510841
    [30]
    W. Li et al. , "Aads: Augmented autonomous driving simulation using data-driven algorithms, " Science robotics, vol. 4, no. 28, p. eaaw0863, 2019. doi: 10.1126/scirobotics.aaw0863
    [31]
    P. Gao et al., "Dc-loc: Accurate automotive radar based metric localization with explicit doppler compensation, " in 2022 International Conference on Robotics and Automation (ICRA). IEEE, 2022, pp. 4128–4134.
    [32]
    K. Nima et al. , "Real-time driver maneuver prediction using lstm, " IEEE Transactions on Intelligent Vehicles, vol. 5, no. 4, pp. 714–724, 2020. doi: 10.1109/TIV.2020.3003889
    [33]
    W. He et al. , "Modeling and trajectory tracking control for flapping-wing micro aerial vehicles, " IEEE/CAA Journal of Automatica Sinica, vol. 8, no. 1, pp. 148–156, 2021. doi: 10.1109/JAS.2020.1003417
    [34]
    Y. Shen et al. , "Radar foundation models towards natural interactions and smart operations of radar systems, " The International Journal of Intelligent Control and Systems, vol. 2, no. 1, pp. 11–16, 2021.
    [35]
    X. Li et al. , "Paralleleye-cs: A new dataset of synthetic images for testing the visual intelligence of intelligent vehicles, " IEEE Transactions on Vehicular Technology, vol. 68, no. 10, pp. 9619–9631, 2019. doi: 10.1109/TVT.2019.2936227
    [36]
    K. Wang et al. , "Parallel vision for perception and understanding of complex scenes: methods, framework, and perspectives, " Artificial Intelligence Review, vol. 48, no. 3, pp. 299–329, 2017. doi: 10.1007/s10462-017-9569-z
    [37]
    Y. Tian et al. , "Parallel point clouds: Hybrid point cloud generation and 3d model enhancement via virtual–real integration, " Remote Sensing, vol. 13, no. 15, p. 2868, 2021. doi: 10.3390/rs13152868
    [38]
    F. -Y. Wang and Y. Shen, "Parallel light field: A perspective and a framework, " IEEE/CAA Journal of Automatica Sinica, vol. 9, no. 11, pp. 1871–1873, 2022. https://www.ieee-jas.net/en/article/id/80376b4c-274f-4a11-a3a6-6426bc8b0382
    [39]
    F. -Y. Wang, "Parallel light field and parallel optics, from optical computing experiment to optical guided intelligence, " The State Key Laboratory for Management and Control of Complex Systems, Tech. Rep., 2018. [Online]. Available: http://www.sklmccs.ia.ac.cn/2018reports.html
    [40]
    F. -Y. Wang et al. , "Parallel light field: the framework and processes, " Chinese Journal of Intelligent Science and Technology, vol. 3, no. 1, pp. 110–122, 2021.
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