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Open Access

A Values-Driven Cyber-Farm of Trigram Metaverse Based on Autonomic Crowd-Dispatching

School of Computer Science, Fudan University, Shanghai 200433, China
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Abstract

The objective of this work is to apply cutting-edge digital techniques to address several identified essential problems, from which farmers, farming, and farms have suffered for centuries. It has been found that the participants in the metaverse-related agricultural applications have been designed to be users rather than residents. There is another critical setback for the metaverse to be a fusion cyber-physical space, in which the cyber space is subject to different values principles from the physical space. A trigram metaverse of Cyber-Farm is proposed to be constructed on a unified trigram space through the fusion of cyber, physical, and values spaces. As a parallel and superstructure to the cyber and physical spaces, the values space enables the cyber space and physical space to follow the same values principles through its autonomic, values-driven, and crowd-dispatching governance system. Unlike in the existing metaverse-related agricultural applications, the Cyber-Farm participants are the subjects/residents rather than the users of a Cyber-Farm. The agricultural elements are coming into being and evolving in the interlinked and fusion trigram space. The basic production means, production relations, and superstructure of the trigram metaverse have been discussed. Both the connotations and scopes of farm, farmer, and farming have been redefined in the trigram metaverse of Cyber-Farm. The intentions, scenarios, principles, and businesses of the Cyber-Farm have been restructured. Basically, the Cyber-Farm can address the identified essential problems with today’s agriculture, while a grand vision is to bring about farm-featured Utopias parallel to human communities.

Keywords

digital twinmetaversedigital agriculturecyber spacecrowd intelligence science

References

[1]

F. Chen, C. H. Sun, B. Cing, N. Luo, and H. S. Liu, Agricultural metaverse: Key technologies, application scenarios, challenges and prospects, (in Chinese), Smart Agriculture, vol. 4, no. 4, pp. 126–137, 2022.
Google Scholar
[2]

M. Kang, X. Wang, H. Wang, J. Hua, P. D. Reffye, and F. Y. Wang, The development of AgriVerse: Past, present, and future, IEEE Trans. Syst. Man Cybern. Syst., vol. 53, no. 6, pp. 3718–3727, 2023.
DOI Google Scholar
[3]

X. Wang, M. Kang, H. Sun, P. D. Reffye, and F. Y. Wang, DeCASA in AgriVerse: Parallel agriculture for smart villages in metaverses, IEEE/CAA J. Autom. Sin., vol. 9, no. 12, pp. 2055–2062, 2022.
DOI Google Scholar
[4]
Y. Li, L. Liu, and S. Sun, Study on soil water and salt information model of digital farmland, in Proc. 2022 Int. Conf. Virtual Reality, Human-Computer Interaction and Artificial Intelligence (VRHCIAI), Changsha, China, 2022, pp. 123–127.
DOI
[5]
C. C. Kuo, Y. H. Shiau, C. P. Huang, C. Y. Shen, and W. F. Tsai, Application of virtual reality in ecological farmland navigating system, in Proc. 7th Int. Conf. High Performance Computing and Grid in Asia Pacific Region, Tokyo, Japan, 2004, pp. 285–288.
[6]
S. C. Huang, A Virtual-grid farmland data-gathering locations decision algorithm for the mobile sink in wireless sensor network, in Proc. 2015 7th Int. Conf. Ubiquitous and Future Networks, Sapporo, Japan, 2015, pp. 667–671.
[7]
T. Luor, H. Lu, H. Yu, and T. Kuo, Instant noodle’s vs. hybrid electric vehicle’s AE effect in a social network game: An empirical study of happy farm, in Proc. Int. Conf. Software Intelligence Technologies and Applications & Int. Conf. Frontiers of Internet of Things 2014, Hsinchu, China, 2014, pp. 200–206.
DOI
[8]
P. Tangworakitthaworn, V. Tengchaisri, and P. Sudjaidee, Serious game enhanced learning for agricultural engineering education: Two games development based on IoT technology, in Proc. 2020 - 5th Int. Conf. Information Technology (InCIT), Chonburi, Thailand, 2020, pp. 82–86.
DOI
[9]
F. Y. Wang, Digital agriculture and parallel intelligence: Towards complex adaptive systems for smart agriculture, Tech. Rep., CASIA, CASKL-CSIS, Beijing, China, 2005.
[10]

F. Yang, K. Wang, Y. Han, and Z. Qiao, A cloud-based digital farm management system for vegetable production process management and quality traceability, Sustainability, vol. 10, no. 11, p. 4007, 2018.
DOI Google Scholar
[11]
M. Lee, J. Hwang, and H. Yoe, Agricultural production system based on IoT, in Proc. 2013 IEEE 16th Int. Conf. Computational Science and Engineering, Sydney, Australia, 2013, pp. 833–837.
DOI
[12]

L. C. Ngugi, M. Abelwahab, and M. Abo-Zahhad, Recent advances in image processing techniques for automated leaf pest and disease recognition—A review, Inf. Process. Agric., vol. 8, no. 1, pp. 27–51, 2021.
DOI Google Scholar
[13]
P. Sacramento, A. Deligant, S. Loekken, and P. P. Mathieu, EO space and multi-source data visualization using Virtual Reality in the ESA Φ-Lab, in Proc. 2022 IEEE Int. Conf. Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), Rome, Italy, 2022, pp. 737–741.
DOI
[14]

X. R. Fan, M. Z. Kang, E. Heuvelink, P. D. Reffye, and B. G. Hu, A knowledge-and-data-driven modeling approach for simulating plant growth: A case study on tomato growth, Ecol. Model., vol. 312, pp. 363–373, 2015.
DOI Google Scholar
[15]

E. Heuvelink, Evaluation of a dynamic simulation model for tomato crop growth and development, Ann. Bot., vol. 83, no. 4, pp. 413–422, 1999.
DOI Google Scholar
[16]
Z. Lv, Virtual reality based human-computer interaction system for metaverse, in Proc. 2023 IEEE Conf. Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Shanghai, China, 2023, pp. 757–758.
DOI
[17]
E. Kruijff and B. E. Riecke, Navigation interfaces for virtual reality and gaming: Theory and practice, in Proc. 2017 IEEE Virtual Reality (VR), Los Angeles, CA, USA, 2017, pp. 433–434.
DOI
[18]
M. Meier, P. Streli, A. Fender, and C. Holz, Demonstrating the use of rapid touch interaction in virtual reality for prolonged interaction in productivity scenarios, in Proc. 2021 IEEE Conf. Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), Lisbon, Portugal, 2021, pp. 761–762.
DOI
[19]

Q. Wang, W. Jiao, P. Wang, and Y. Zhang, Digital twin for human-robot interactive welding and welder behavior analysis, IEEE/CAA J. Autom. Sin., vol. 8, no. 2, pp. 334–343, 2021.
DOI Google Scholar
[20]
Y. Li, B. Wu, Z. Zhong, and J. Shen, Cyber-A(nima): Modelling, reasoning and applications, in Proc. 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), San Francisco, CA, USA, 2017, pp. 1–8.
DOI
[21]

Y. Chai, C. Miao, B. Sun, Y. Zheng, and Q. Li, Crowd science and engineering: Concept and research framework, International Journal of Crowd Science, vol. 1, no. 1, pp. 2–8, 2017.
DOI Google Scholar
[22]

K. Wang, Z. Yang, B. Liang, and W. Ji, An intelligence optimization method based on crowd intelligence for IoT devices, International Journal of Crowd Science, vol. 5, no. 3, pp. 218–227, 2021.
DOI Google Scholar
[23]

A. Xing and H. Sun, A crowd equivalence-based massive member model generation method for crowd science simulations, International Journal of Crowd Science, vol. 6, no. 1, pp. 23–33, 2022.
DOI Google Scholar
[24]
Y. Chen, Z. Wang, X. Liu, and X. Wei, A new NFT model to enhance copyright traceability of the off-chain data, in Proc. 2022 Int. Conf. Culture-Oriented Science and Technology (CoST), Lanzhou, China, 2022, pp. 157–162.
DOI
[25]
Q. Wang, R. Li, Q. Wang, and S. Chen, Non-fungible token (NFT): Overview, evaluation, opportunities and challenges, arXiv preprint arXiv: 2105.07447, 2021.
[26]

L. Ante, Non-fungible token (NFT) markets on the Ethereum blockchain: Temporal development, cointegration and interrelations, Econ. Innov. N. Technol., vol. 32, no. 8, pp. 1216–1234, 2023.
DOI Google Scholar
[27]
A. Singhal, Divya, N. Singhal, and K. Sharma, Metaverse: Cryptocurrency price analysis using Monte Carlo simulation, in Proc. 2023 Int. Conf. Computer Communication and Informatics (ICCCI), Coimbatore, India, 2023, pp. 1–8.
DOI
[28]

K. Jian, Energy coin: A universal digital currency based on free energy, Am. J. Mod. Energy, vol. 6, no. 5, pp. 95–100, 2020.
DOI Google Scholar
[29]
Y. Li, X. Liang, X. Zhu, and B. Wu, A blockchain-based autonomous credit system, in Proc. 2018 IEEE 15th Int. Conf. E-Business Engineering (ICEBE), Xi’an, China, 2018, pp. 178–186.
DOI
[30]

F. Y. Wang, R. Qin, J. Li, X. Wang, H. Qi, X. Jia, and B. Hu, Federated management: Toward federated services and federated security in federated ecology, IEEE Trans. Comput. Soc. Syst., vol. 8, no. 6, pp. 1283–1290, 2021.
DOI Google Scholar
International Journal of Crowd Science
Volume 7 Issue 4,
December 2023
Pages 200-211
DOI: 10.26599/IJCS.2023.9100027
Cite this article:
Li Y. A Values-Driven Cyber-Farm of Trigram Metaverse Based on Autonomic Crowd-Dispatching. International Journal of Crowd Science, 2023, 7(4): 200-211. https://doi.org/10.26599/IJCS.2023.9100027

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Received: 20 June 2023
Revised: 23 October 2023
Accepted: 03 November 2023
Published: 22 December 2023
© The author(s) 2024.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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