农业元宇宙：关键技术、应用情景、挑战与展望

doi:10.12133/j.smartag.SA202206006

摘要/Abstract

摘要：

元宇宙这一新兴概念受到了产、学、研各界的广泛关注。农业与元宇宙的结合将极大地推动农业信息化和智能化发展，为农业智能化转型升级提供新动能。为深入分析元宇宙在农业领域的应用研究可行性，本文首先分析了农业元宇宙的概念，以及区块链、非同质化代币、5G/6G、人工智能、物联网、三维重建、云计算、边缘计算和扩展现实等元宇宙农业应用的关键技术。接着讨论了元宇宙在虚拟农场、农业教学系统和农产品追溯系统三个农业应用领域的主要情景，最后总结了农业元宇宙面临的系统建立、通信基础、硬件设备和运营等方面的主要挑战，并展望了未来的发展方向。本文可为元宇宙在农业的应用研究提供指导。

关键词: 农业元宇宙, 区块链, 扩展现实, 数字孪生, 平行农业, 虚拟农场, 农产品追溯系统, 农业教学系统

Abstract:

As an emerging concept, metaverse has attracted extensive attention from industry, academia and scientific research field. The combination of agriculture and metaverse will greatly promote the development of agricultural informatization and agricultural intelligence, provide new impetus for the transformation and upgrading of agricultural intelligence. Firstly, to expound feasibility of the application research of metaverse in agriculture, the basic principle and key technologies of agriculture metaverse were briefly described, such as blockchain, non-fungible token, 5G/6G, artificial intelligence, Internet of Things, 3D reconstruction, cloud computing, edge computing, augmented reality, virtual reality, mixed reality, brain computer interface, digital twins and parallel system. Then, the main scenarios of three agricultural applications of metaverse in the fields of virtual farm, agricultural teaching system and agricultural product traceability system were discussed. Among them, virtual farm is one of the most important applications of agricultural metaverse. Agricultural metaverse can help the growth of crops and the raising of livestock and poultry in the field of agricultural production, provide a three-dimensional and visual virtual leisure agricultural experience, provide virtual characters in the field of agricultural product promotion. The agricultural metaverse teaching system can provide virtual agricultural teaching similar to natural scenes, save training time and improve training efficiency by means of fragmentation. Traceability of agricultural products can let consumers know the production information of agricultural products and feel more confident about enterprises and products. Finally, the challenges in the development of agricultural metaverse were summarized in the aspects of difficulties in establishing agricultural metaverse system, weak communication foundation of agricultural metaverse, immature agricultural metaverse hardware equipment and uncertain agricultural meta universe operation, and the future development directions of agricultural metaverse were prospected. In the future, researches on the application of metaverse, agricultural growth mechanism, and low power wireless communication technologies are suggested to be carried out. A rural broadband network covering households can be established. The industrialization application of agricultural meta universe can be promoted. This review can provide theoretical references and technical supports for the development of metaverse in the field of agriculture.

Key words: agricultural metaverse, blockchain, extended reality, digital twins, parallel agriculture, virtual farm, agri-food supply chain traceability system, agricultural education system

中图分类号:

TP391.9

陈枫, 孙传恒, 邢斌, 罗娜, 刘海深. 农业元宇宙：关键技术、应用情景、挑战与展望[J]. 智慧农业(中英文), 2022, 4(4): 126-137.

CHEN Feng, SUN Chuanheng, XING Bin, LUO Na, LIU Haishen. Agricultural Metaverse: Key Technologies, Application Scenarios, Challenges and Prospects[J]. Smart Agriculture, 2022, 4(4): 126-137.

参考文献

1	NING H, WANG H, LIN Y, et al. A survey on metaverse: The state-of-the-art, technologies, applications, and challenges[J/OL]. arXiv: , 2021.
2	Introducing Meta: A social technology company[EB/OL]. [2022-05-30]. .
3	北京日报. 国内首家获批元宇宙行业协会揭牌[EB/OL]. [2022-05-20]. .
4	赵春江. 智慧农业发展现状及战略目标研究[J]. 智慧农业, 2019, 1(1): 1-7.
4	ZHAO C. State-of-the-art and recommended developmental strategic objectives of smart agriculture[J]. Smart Agriculture, 2019, 1(1): 1-7.
5	王文喜, 周芳, 万月亮, 等. 元宇宙技术综述[J]. 工程科学学报, 2022, 44(4): 744-756.
5	WANG W, ZHOU F, WAN Y, et al. A survey of metaverse technology[J]. Chinese Journal of Engineering, 2022, 44(4): 744-756.
6	袁勇, 王飞跃. 区块链技术发展现状与展望[J]. 自动化学报, 2016, 42(4): 481-494.
6	YUAN Y, WANG F. Blockchain: The state of the art and future trends[J]. Acta Automatica Sinica, 2016, 42(4): 481-494.
7	曾诗钦, 霍如, 黄韬, 等. 区块链技术研究综述: 原理, 进展与应用[J]. 通信学报, 2020, 41(1): 134-151.
7	ZENG S, HUO R, HUANG T, et al. Survey of blockchain: Principle, progress and application[J]. Journal on Communications, 2020, 41(1): 134-151.
8	DOWLING M. Is non-fungible token pricing driven by cryptocurrencies?[J]. Finance Research Letters, 2022, 44: ID 102097.
9	秦蕊, 李娟娟, 王晓, 等. NFT: 基于区块链的非同质化通证及其应用[J]. 智能科学与技术学报, 2021, 3(2): 234-242.
9	QIN R, LI J, WANG X, et al. NFT: Blockchain-based non-fungible token and applications[J]. Chinese Journal of Intelligent Science and Technology, 2021, 3(2): 234-242.
10	WANG Q, LI R, WANG Q, et al. Non-fungible token (NFT): Overview, evaluation, opportunities and challenges[J/OL]. arXiv:, 2021.
11	BAO H, ROUBAUD D. Non-fungible token: A systematic review and research agenda[J]. Journal of Risk and Financial Management, 2022, 15(5): ID 215.
12	SHAFI M, MOLISCH A F, SMITH P J, et al. 5G: A tutorial overview of standards, trials, challenges, deployment, and practice[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(6): 1201-1221.
13	DOGRA A, JHA R K, JAIN S. A survey on beyond 5G network with the advent of 6G: Architecture and emerging technologies[J]. IEEE Access, 2020, 9: 67512-67547.
14	CAMBRIA E, WHITE B. Jumping NLP curves: A review of natural language processing research[J]. IEEE Computational Intelligence Magazine, 2014, 9(2): 48-57.
15	VOULODIMOS A, DOULAMIS N, DOULAMIS A, et al. Deep learning for computer vision: A brief review[J]. Computational Intelligence and Neuroscience, 2018, 2018: 1-2.
16	PARK D H, KIM H K, CHOI I Y, et al. A literature review and classification of recommender systems research[J]. Expert Systems with Applications, 2012, 39(11): 10059-10072.
17	YNAG Q, ZHAO Y, HUANG H, et al. Fusing blockchain and AI with metaverse: A survey[J/OL]. arXiv:, 2022.
18	WILLIAMS T, SZAFIR D, CHAKRABORTI T, et al. Virtual, augmented, and mixed reality for human-robot interaction (vam-hri)[C]// 2019 14th ACM/IEEE International Conference on Human-Robot Interaction. Piscataway, New York, USA: IEEE, 2019: 671-672.
19	ZHANG J, ZONG C. Deep neural networks in machine translation: An overview[J]. IEEE Intelligent Systems, 2015, 30(5): 16-25.
20	PHILLIPS-WREN G. AI tools in decision making support systems: A review[J]. International Journal on Artificial Intelligence Tools, 2012, 21(2): ID 1240005.
21	FAROOQ M U, WASEEM M, MAZHAR S, et al. A review on Internet of Things (IoT)[J]. International Journal of Computer Applications, 2015, 113(1): 1-7.
22	MADAKAM S, LAKE V, LAKE V, et al. Internet of Things (IoT): A literature review[J]. Journal of Computer and Communications, 2015, 3(5): ID 164.
23	LI Z, WANG J, HIGGS R, et al. Design of an intelligent management system for agricultural greenhouses based on the internet of things[C]// 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC). Piscataway, New York, USA: IEEE, 2017, 2: 154-160.
24	HAN J, LIN N, RUAN J, et al. A model for joint planning of production and distribution of fresh produce in agricultural internet of things[J]. IEEE Internet of Things Journal, 2020, 8(12): 9683-9696.
25	ZHANG J, RAO Y, MAN C, et al. Identification of cucumber leaf diseases using deep learning and small sample size for agricultural Internet of Things[J]. International Journal of Distributed Sensor Networks, 2021, 17(4): ID 15501477211007407.
26	HAM H, WESLEY J, HENDRA H. Computer vision based 3D reconstruction: A review[J]. International Journal of Electrical and Computer Engineering, 2019, 9(4): ID 2394.
27	MA Z, LIU S. A review of 3D reconstruction techniques in civil engineering and their applications[J]. Advanced Engineering Informatics, 2018, 37: 163-174.
28	POLLEFEYS M, NISTéR D, FRAHM J M, et al. Detailed real-time urban 3D reconstruction from video[J]. International Journal of Computer Vision, 2008, 78(2): 143-167.
29	GOMES L, BELLON O R P, SILVA L. 3D reconstruction methods for digital preservation of cultural heritage: A survey[J]. Pattern Recognition Letters, 2014, 50: 3-14.
30	YIMYAM P, CLARK A. 3D reconstruction and feature extraction for agricultural produce grading[C]// 2016 8th International Conference on Knowledge and Smart Technology (KST). Piscataway, New York, USA: IEEE, 2016: 136-141.
31	MOONRINTA J, CHAIVIVATRAKUL S, DAILEY M, et al. Fruit detection, tracking, and 3D reconstruction for crop mapping and yield estimation[C]// 2010 11th International Conference on Control Automation Robotics & Vision. Piscataway, New York, USA: IEEE, 2010: 1181-1186.
32	朱荣胜, 李帅, 孙永哲, 等. 作物三维重构技术研究现状及前景展望[J]. 智慧农业(中英文), 2021, 3(3): 94-115.
32	ZHU R, LI S, SUN Y, et al. Research advances and prospects of crop 3D reconstruction technology[J]. Smart Agriculture, 2021, 3(3): 94-115.
33	RASHID A, CHATURVEDI A. Cloud computing characteristics and services: A brief review[J]. International Journal of Computer Sciences and Engineering, 2019, 7(2): 421-426.
34	SITTóN-CANDANEDO I, ALONSO R S, CORCHADO J M, et al. A review of edge computing reference architectures and a new global edge proposal[J]. Future Generation Computer Systems, 2019, 99: 278-294.
35	KARAR M E, ALSUNAYDI F, ALBUSAYMI S, et al. A new mobile application of agricultural pests recognition using deep learning in cloud computing system[J]. Alexandria Engineering Journal, 2021, 60(5): 4423-4432.
36	GOYA W A, DE ANDRADE M R, ZUCCHI A C, et al. The use of distributed processing and cloud computing in agricultural decision-making support systems[C]// 2014 IEEE 7th International Conference on Cloud Computing. Piscataway, New York, USA: IEEE, 2014: 721-728.
37	FAST-BERGLUND ?, GONG L, LI D. Testing and validating extended reality (XR) technologies in manufacturing[J]. Procedia Manufacturing, 2018, 25: 31-38.
38	BERRYMAN D R. Augmented reality: A review[J]. Medical Reference Services Quarterly, 2012, 31(2): 212-218.
39	HALARNKAR P, SHAH S, SHAH H, et al. A review on virtual reality[J]. International Journal of Computer Science Issues, 2012, 9(6): ID 325.
40	ROKHSARITALEMI S, SADEGHI-NIARAKI A, CHOI S M. A review on mixed reality: Current trends, challenges and prospects[J]. Applied Sciences, 2020, 10(2): ID 636.
41	RAMADAN R A, VASILAKOS A V. Brain computer interface: Control signals review[J]. Neurocomputing, 2017, 223: 26-44.
42	ALLISON B Z, WOLPAW E W, WOLPAW J R. Brain-computer interface systems: Progress and prospects[J]. Expert review of Medical Devices, 2007, 4(4): 463-474.
43	刘大同, 郭凯, 王本宽, 等. 数字孪生技术综述与展望[J]. 仪器仪表学报, 2018, 39(11): 1-10.
43	LIU D, GUO K, WANG B, et al. Summary and perspective survey on digital twin technology[J]. Chinese Journal of Scientific Instrument, 2018, 39(11): 1-10.
44	WRIGHT L, DAVIDSON S. How to tell the difference between a model and a digital twin[J]. Advanced Modeling and Simulation in Engineering Sciences, 2020, 7(1): 1-13.
45	VAN D B S, KLOPPENBURG S, KOK E J, et al. Digital twins in agri-food: Societal and ethical themes and questions for further research[J]. NJAS: Impact in Agricultural and Life Sciences, 2021, 93(1): 98-125.
46	顾生浩, 卢宪菊, 王勇健, 等. 数字孪生系统在农业生产中的应用探讨[J]. 中国农业科技导报, 2021, 23(10): 82-89.
46	GU S, LU X, WANG Y, et al. Application of agricultural digital twin system in crop production system[J]. Journal of Agricultural Science and Technology, 2021, 23(10): 82-89.
47	王飞跃. 平行系统方法与复杂系统的管理和控制[J]. 控制与决策, 2004, 19(5): 485-489.
47	WANG F. Parallel system methods for management and control of complex systems[J]. Control and Decision, 2004, 19(5): 485-489.
48	王飞跃. 人工社会, 计算实验, 平行系统--关于复杂社会经济系统计算研究的讨论[J]. 复杂系统与复杂性科学, 2004(4): 25-35.
48	WANG F. Artificial societies, computational expermients, and parallel systems: A discussion on computational theory of complex social-economic systems[J]. Complex Systems and Complexity Science, 2004(4): 25-35.
49	尹培丽, 王建华, 陈阳泉, 等. 平行测量: 复杂测量系统的一个新型理论框架及案例研究[J]. 自动化学报, 2018, 44(3): 425-433.
49	YIN P, WANG J, CHEN Y, et al. Parallel measurements: A new theory and framework for complex measurement system and a case study[J]. Acta Automatica Sinica, 2018, 44(3): 425-433.
50	张俊, 许沛东, 王飞跃. 平行系统和数字孪生的一种数据驱动形式表示及计算框架[J]. 自动化学报, 2020, 46(7): 1346-1356.
50	ZHANG J, XU P, WANG F. Parallel systems and digital twins: A data-driven mathematical representation and computational framework[J]. Acta Automatica Sinica, 2020, 46(7): 1346-1356.
51	NASIRAHMADI A, HENSEL O. Toward the next generation of digitalization in agriculture based on digital twin paradigm[J]. Sensors, 2022, 22(2): ID 498.
52	NEETHIRAJAN S, KEMP B. Digital twins in livestock farming[J]. Animals, 2021, 11(4): ID 1008.
53	GHANDAR A, AHMED A, ZULFIQAR S, et al. A decision support system for urban agriculture using digital twin: A case study with aquaponics[J]. IEEE Access, 2021, 9: 35691-35708.
54	LI W, ZHU D, WANG Q. A single view leaf reconstruction method based on the fusion of ResNet and differentiable render in plant growth digital twin system[J]. Computers and Electronics in Agriculture, 2022, 193: ID 106712.
55	PYLIANIDIS C, OSINGA S, ATHANASIADIS I N. Introducing digital twins to agriculture[J]. Computers and Electronics in Agriculture, 2021, 184: ID 105942.
56	VERDOUW C, TEKINERDOGAN B, BEULENS A, et al. Digital twins in smart farming[J]. Agricultural Systems, 2021, 189: ID 103046.
57	CHAUX J D, SANCHEZ-LONDONO D, BARBIERI G. A digital twin architecture to optimize productivity within controlled environment agriculture[J]. Applied Sciences, 2021, 11(19): ID 8875.
58	康孟珍, 王秀娟, 华净, 等. 平行农业: 迈向智慧农业的智能技术[J]. 智能科学与技术学报, 2019, 1(2): 107-117.
58	KANG M, WANG X, HUA J, et al. Parallel agriculture: Intelligent technology toward smart agriculture[J]. Chinese Journal of Intelligent Science and Technology, 2019, 1(2): 107-117.
59	DE REFFYE P, JAEGER M. Modèles mathématiques du développement et de la croissance de l' architecture des plantes. Le cas du modèle GreenLab[M]. Paris: Editions Matériologiques, 2011.
60	GUTIé RREZ-ESTRADA J C, PULIDO-CALVO I, BILTON D T. Consistency of fuzzy rules in an ecological context[J]. Ecological Modeling, 2013, 251: 187-198.
61	袁勇, 周涛, 周傲英, 等. 区块链技术: 从数据智能到知识自动化[J]. 自动化学报, 2017, 43(9): 1485-1490.
61	YUAN Y, ZHOU T, ZHOU A, et al. Blockchain technology: From data intelligence to knowledge automation[J]. Acta Automatica Sinica, 2017, 43(9): 1485-1490.
62	王飞跃. 平行控制与数字孪生: 经典控制理论的回顾与重铸[J]. 智能科学与技术学报, 2020, 2(3): 293-300.
62	WANG F. Parallel control and digital twins: Control theory revisited and reshaped[J]. Chinese Journal of Intelligent Science and Technology, 2020, 2(3): 293-300.
63	赵春江, 李瑾, 冯献. 面向2035年智慧农业发展战略研究[J]. 中国工程科学, 2021, 23(4): 1-9.
63	ZHAO C, LI J, FENG X. Development strategy of smart agriculture for 2035 in China[J]. Strategic Study of CAE, 2021, 23(4): 1-9.
64	黑龙江农业科学. “元宇宙+农业”如何改变农业?[EB/OL]. [2022-05-31]. .
65	超级码. 超级码硬核发布浙江首个元宇宙智慧茶园, 数字农业高玩来袭[EB/OL]. [2022-06-10]. .
66	NICOLA K. What is the future of the metaverse for indoor agriculture?[EB/OL]. [2022-05-18]. .
67	泰国网. 泰国开启"元宇宙果园"[EB/OL]. [2022-05-18]. .
68	南方农村报. 从化荔枝节盛大开幕!国内首个荔枝元宇宙虚拟直播来了[EB/OL]. [2022-07-18]. .
69	南方农村报. 首个预制菜元宇宙人"小鲜妹"将直播![EB/OL]. [2022-05-18]. .
70	环球网. 数字农业高玩来袭, 超级码科技股份硬核发布浙江首个元宇宙智慧茶园[EB/OL]. [2022-05-18]. .
71	IFDIL I, SITUMORANG D D B, FIRMAN F, et al. Virtual reality in metaverse for future mental health-helping profession: An alternative solution to the mental health challenges of the COVID-19 pandemic[J]. Journal of Public Health, 2022: ID fdac049.
72	PARK S, KIM S. Identifying world types to deliver gameful experiences for sustainable learning in the metaverse[J]. Sustainability, 2022, 14(3): ID 1361.
73	KHANSULIVONG C, WICHA S, TEMDEE P. Adaptive of new technology for agriculture online learning by metaverse: A case study in faculty of agriculture, national university of Laos[C]// 2022 Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering. Piscataway, New York, USA: IEEE, 2022: 428-432
74	杨信廷, 钱建平, 孙传恒, 等. 农产品及食品质量安全追溯系统关键技术研究进展[J]. 农业机械学报, 2014, 45(11): 212-222.
74	YANG X, QIAN J, SUN C, et al. Key technologies for establishment agricultural products and food quality safety traceability systems[J]. Transactions of the CSAM, 2014, 45(11): 212-222.
75	钱建平, 吴文斌, 杨鹏. 新一代信息技术对农产品追溯系统智能化影响的综述[J]. 农业工程学报, 2020, 36(5): 182-191.
75	QIAN J, WU W, YANG P. Review on agricultural products smart traceability system affected by new generation information technology[J]. Transactions of the CSAE, 2020, 36(5): 182-191.
76	孙传恒, 于华竟, 徐大明, 等. 农产品供应链区块链追溯技术研究进展与展望[J]. 农业机械学报, 2021, 52(1): 1-13.
76	SUN C, YU H, XU D, et al. Review and prospect of agri-products supply chain traceability based on blockchain technology[J]. Transactions of the CSAM, 2021, 52(1): 1-13.

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