Metaverses-Based Parallel Oil Fields in CPSS: A Framework and Methodology

Wang, Xingxia; Cheng, Xiang; Lu, Jingwei; Kwan, Oliver; Li, Shixing; Ping, Zhixing

doi:10.1109/tsmc.2022.3228934

Cited by 11 publications

(1 citation statement)

References 97 publications

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“…This approach allows for the resolution of modeling, analysis, and experimentation issues within a unified theoretical framework and has found wide application across various domains. For instance, in the field of complex engineering, it has been applied to real-time safety monitoring of visual intelligence [20], transportation systems [21], oil fields [22], metaverse [23], and so on [24][25][26][27]. In agricultural engineering, it has been utilized for monitoring and managing crop cultivation, precision control of crop manufacturing, and fine control of high-value plant species [28].…”

Section: Introductionmentioning

confidence: 99%

ACP-Based Space Systems: Design, Development, and Operation

Cai,

Meng,

Wang

2024

International Journal of Aerospace Engineering

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In the context of the rapid advancements in space technology and the increasing complexity of space missions, there is a growing need for efficient and effective approaches to tackle the multifaceted challenges faced by space systems. Traditional methods often fall short in providing comprehensive support throughout the entire life cycle of space systems. To address these challenges, this paper presents a novel parallel space system architecture based on ACP (artificial systems, computational experiments, and parallel execution) and explores its applications in the design, development, and operation of space systems. The proposed architecture integrates artificial systems with actual space systems and employs computational experiments to generate extensive sample data. This approach enhances the accuracy of the artificial systems’ model and optimizes the performance of the real systems, facilitating parallel advancements between the two. The design, development, and operation processes of Q-Sat, implemented using the ACP framework, serve as a case study to illustrate the advantages of parallel space systems. Following adjustments made to the discrepancies between parallel systems under the ACP-based space system framework, the accuracy of missing orbit compensation improved by 86.5%, and the 24-hour forecast positional error was reduced by approximately 65 m. Furthermore, this paper discusses future trends, emphasizing the increasing efficiency and reliability of digitized, integrated, and adaptive space systems. The findings contribute to the understanding of parallel space systems and provide valuable insights for further advancements in the field.

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Section: Introductionmentioning

confidence: 99%

ACP-Based Space Systems: Design, Development, and Operation

Cai,

Meng,

Wang

2024

International Journal of Aerospace Engineering

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Parallel intelligence in three decades: a historical review and future perspective on ACP and cyber-physical-social systems

Wang,

Yang,

Liu

et al. 2024

Artif Intell Rev

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Recent advances in human-in-the-loop or human-centric research have sparked a new wave of scientific exploration. These studies have enhanced the understanding of complex social systems and contributed to more sustainable artificial intelligence (AI) ecosystems. However, the incorporation of human or social factors increases system complexity, making traditional approaches inadequate for managing these complex systems and necessitating a novel operational paradigm. Over decades of work, a mature and comprehensive theory of parallel intelligence (PI) has been established. Rooted in cyber-physical-social systems (CPSS), PI adapts flexibly to various situations within complex systems through the ACP framework (Artificial systems, Computational experiments, and Parallel execution), ensuring system reliability. This paper provides a detailed review and a novel perspective on PI, beginning with the historical and philosophical origins of CPSS and proceeding to present both the fundamental framework and technological implementations of PI. PI-based Industry 5.0 is highlighted, where three pillars are adopted to help realize the supposed vision. Additionally, the paper outlines applications of PI in multiple fields, such as transportation, healthcare, manufacturing, and agriculture, and discusses the opportunities and challenges for imaginative intelligence. The continuous exploration of PI is expected to eventually facilitate the realization of “6S”-based (safe, secure, sustainable, sensitive, service, and smart) parallel ecosystems.

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