A systematic review of Metaverse environment

Authors

  • Asif Zaman Computer Science and Engineering, American International University, Bangladesh
  • Mushfiqur Rahman Abir Computer Science and Engineering, American International University, Bangladesh
  • Tanjil Hasan Sakib Computer Science and Engineering, American International University, Bangladesh
  • Asgor Hossain Reaj Computer Science and Engineering, American International University, Bangladesh

DOI:

https://doi.org/10.22105/metaverse.v1i1.17

Keywords:

Metaverse, Trust, Privacy, Security, Ethics

Abstract

The rise of the metaverse, a blend of virtual and augmented realities, opens vast possibilities for social engagement, economic transactions, and digital innovation. However, establishing a reliable metaverse involves significant technical and ethical hurdles. From a technical perspective, creating the metaverse necessitates a robust infrastructure, including high-speed internet, advanced hardware, and scalable platforms capable of supporting many simultaneous users. Key challenges include ensuring interoperability among various systems and maintaining cybersecurity to protect user data and privacy. On the ethical front, the metaverse must tackle issues related to digital identity, inclusivity, and equitable access, striving to bridge digital divides and ensure the representation of diverse demographics. Furthermore, there is a need to develop measures to combat misinformation, harassment, and digital addiction, which requires robust governance frameworks. This paper delves into these complex challenges, advocating for a multi-stakeholder approach that brings together policymakers, technologists, and ethicists to establish comprehensive standards and regulations. By addressing both the technical and ethical aspects, the objective is to create a Metaverse that is secure, inclusive, and advantageous for all users.

References

Moneta, A. (2020). Architecture, heritage, and the Metaverse. Traditional dwellings and settlements review, 32(1), 37–49.

Díaz, J. E. M., Saldaña, C. A. D., & Avila, C. A. R. (2020). Virtual world as a resource for hybrid education. International journal of emerging technologies in learning, 15(15), 94–109. DOI:10.3991/ijet.v15i15.13025

Wang, Y., Su, Z., Zhang, N., Xing, R., Liu, D., Luan, T. H., & Shen, X. (2023). A survey on Metaverse: fundamentals, security, and privacy. IEEE communications surveys and tutorials, 25(1), 319–352. DOI:10.1109/COMST.2022.3202047

Duan, H., Li, J., Fan, S., Lin, Z., Wu, X., & Cai, W. (2021). Metaverse for social good: a university campus prototype [presentation]. Proceedings of the 29th acm international conference on multimedia (pp. 153–161). https://doi.org/10.1145/3474085.3479238

Park, S. M., & Kim, Y. G. (2022). A Metaverse: taxonomy, components, applications, and open challenges. IEEE access, 10, 4209–4251. DOI:10.1109/ACCESS.2021.3140175

Narin, N. G. (2021). A content analysis of the Metaverse articles. Journal of Metaverse, 1(1), 17–24. https://dergipark.org.tr/en/pub/jmv/issue/67581/1051382

Kraus, S., Kanbach, D. K., Krysta, P. M., Steinhoff, M. M., & Tomini, N. (2022). Facebook and the creation of the Metaverse: radical business model innovation or incremental transformation? International journal of entrepreneurial behaviour and research, 28(9), 52–77. DOI:10.1108/IJEBR-12-2021-0984

Toreini, E., Aitken, M., Coopamootoo, K., Elliott, K., Zelaya, C. G., & van Moorsel, A. (2020). The relationship between trust in AI and trustworthy machine learning technologies [presentation]. FAT* 2020 - proceedings of the 2020 conference on fairness, accountability, and transparency (pp. 272–283). DOI: 10.1145/3351095.3372834

Guo, Y., Yu, T., Wu, J., Wang, Y., Wan, S., Zheng, J., … & Dai, Q. (2022). Artificial intelligence for Metaverse: a framework. CAAI artificial intelligence research, 1(1), 54–67. DOI:10.26599/air.2022.9150004

Jones, R. K., & Lee, D. N. (1981). Why two eyes are better than one: the two views of binocular vision. Journal of experimental psychology: human perception and performance, 7(1), 30–40. DOI:10.1037/0096-1523.7.1.30

Tunca, S., Sezen, B., & Wilk, V. (2023). An exploratory content and sentiment analysis of the guardian Metaverse articles using leximancer and natural language processing. Journal of Big Data, 10(1), 82. DOI:10.1186/s40537-023-00773-w

Hemp, P. (2006). Avatar-based marketing. Harvard business review, 84(6), 48–57.

Kou, Y., & Gui, X. (2023). Harmful design in the Metaverse and how to mitigate it: a case study of user-generated virtual worlds on roblox [presentation]. Proceedings of the 2023 acm designing interactive systems conference (pp. 175–188). DOI: 10.1145/3563657.3595960

Ponce, B. A., Menendez, M. E., Oladeji, L. O., Fryberger, C. T., & Dantuluri, P. K. (2014). Emerging technology in surgical education: combining real-time augmented reality and wearable computing devices. Orthopedics, 37(11), 751–757. DOI:10.3928/01477447-20141023-05

El Faqir, Y., Arroyo, J., & Hassan, S. (2020). An overview of decentralized autonomous organizations on the blockchain [presentation]. Proceedings of the 16th international symposium on open collaboration (pp. 1–8). https://doi.org/10.1145/3412569.3412579

Chrétien-Ichikawa, S. (2022). Shanghai fashion and post-1990s youth through the Phygital Lens. In Creative industries and digital transformation in China (pp. 117–146). Springer. DOI: 10.1007/978-981-19-3049-2_6

Maeng, Y., Lee, C. C., & Yun, H. (2023). Understanding antecedents that affect customer evaluations of head-mounted display VR devices through text mining and deep neural network. Journal of theoretical and applied electronic commerce research, 18(3), 1238–1256. DOI:10.3390/jtaer18030063

Huynh-The, T., Pham, Q. V., Pham, X. Q., Nguyen, T. T., Han, Z., & Kim, D. S. (2023). Artificial intelligence for the Metaverse: a survey. Engineering applications of artificial intelligence, 117, 105581. DOI:10.1016/j.engappai.2022.105581

Cheong, B. C. (2022). Avatars in the Metaverse: potential legal issues and remedies. International cybersecurity law review, 3(2), 467–494. DOI:10.1365/s43439-022-00056-9

Yang, Q., Zhao, Y., Huang, H., Xiong, Z., Kang, J., & Zheng, Z. (2022). Fusing Blockchain and AI with Metaverse: a survey. IEEE open journal of the computer society, 3, 122–136. DOI:10.1109/OJCS.2022.3188249

Regner, F., Schweizer, A., & Urbach, N. (2019). NFTs in practice-non-fungible tokens as core component of a Blockchain-based event ticketing application [presentation]. 40th international conference on information systems, icis 2019 (pp. 1–17). https://www.fim-rc.de/Paperbibliothek/Veroeffentlicht/1045/wi-1045.pdf

Zhang, H., Lee, S., Lu, Y., Yu, X., & Lu, H. (2023). A survey on Big Data technologies and their applications to the Metaverse: past, current and future. Mathematics, 11(1), 96. DOI:10.3390/math11010096

Tang, F., Chen, X., Zhao, M., & Kato, N. (2023). The roadmap of communication and networking in 6g for the Metaverse. IEEE wireless communications, 30(4), 72–81. DOI:10.1109/MWC.019.2100721

Kiong, L. V. (2022). Web3 made easy: a comprehensive guide to Web3: everything you need to know about web3, Blockchain, DeFi, Metaverse, NFT and GameFi. Liew Voon Kiong. https://l1nq.com/NCLkG

Adams, D. (2022). Virtual retail in the Metaverse: customer behavior analytics, extended reality technologies, and immersive visualization systems. Linguistic and philosophical investigations, 21(21), 73–88. DOI:10.22381/lpi2120225.

Kshetri, N. (2022). Web 3.0 and the Metaverse shaping organizations’ brand and product strategies. IT professional, 24(02), 11–15. DOI:10.1109/MITP.2022.3157206

Wagner, R., & Cozmiuc, D. (2022). Extended reality in marketing—a multiple case study on internet of things platforms. Information (Switzerland), 13(6), 278. DOI:10.3390/info13060278

McLean, G., & Wilson, A. (2019). Shopping in the digital world: examining customer engagement through augmented reality mobile applications. Computers in human behavior, 101, 210–224. https://doi.org/10.1016/j.chb.2019.07.002

Drapkin, A. (2023). Metaverse companies: who’s involved and who’s investing in 2023. https://tech.co/news/metaverse-companies-whos-involved-whos-investing

Dincelli, E., & Yayla, A. (2022). Immersive virtual reality in the age of the Metaverse: a hybrid-narrative review based on the technology affordance perspective. Journal of strategic information systems, 31(2), 101717. DOI:10.1016/j.jsis.2022.101717

Hennig-Thurau, T., Aliman, D. N., Herting, A. M., Cziehso, G. P., Linder, M., & Kübler, R. V. (2023). Social interactions in the Metaverse: framework, initial evidence, and research roadmap. Journal of the academy of marketing science, 51(4), 889–913. DOI:10.1007/s11747-022-00908-0

Ong, T., Wilczewski, H., Paige, S. R., Soni, H., Welch, B. M., & Bunnell, B. E. (2021). Extended reality for enhanced telehealth during and beyond covid-19: viewpoint. JMIR serious games, 9(3), e26520. DOI:10.2196/26520

Khan, N., Muhammad, K., Hussain, T., Nasir, M., Munsif, M., Imran, A. S., & Sajjad, M. (2021). An adaptive game-based learning strategy for children road safety education and practice in virtual space. Sensors, 21(11), 3661. DOI:10.3390/s21113661

Wiederhold, B. K., & Riva, G. (2022). Metaverse creates new opportunities in healthcare. Annual review of cybertherapy and telemedicine, 20, 3–7. https://psycnet.apa.org/record/2023-49082-001

Schumacher, P. (2022). The Metaverse as opportunity for architecture and society: design drivers, core competencies. Architectural intelligence, 1(1), 11. DOI:10.1007/s44223-022-00010-z

Thomason, J. (2022). Metaverse, token economies, and non-communicable diseases. Global health journal, 6(3), 164–167.

Mourtzis, D., Angelopoulos, J., & Panopoulos, N. (2023). Blockchain integration in the era of industrial Metaverse. Applied sciences (Switzerland), 13(3), 1353. DOI:10.3390/app13031353

Hosain, T., Zaman, A., Abir, M. R., Akter, S., Mursalin, S., & Khan, S. S. (2024). Synchronizing object detection: applications, advancements and existing challenges. IEEE access, 12, 54129–54167. DOI:10.1109/ACCESS.2024.3388889

Hosain, M. T., Jim, J. R., Mridha, M. F., & Kabir, M. M. (2024). Explainable AI approaches in deep learning: advancements, applications and challenges. Computers and electrical engineering, 117, 109246. DOI:10.1016/j.compeleceng.2024.109246

Hosain, M. T., Anik, M. H., Rafi, S., Tabassum, R., Insia, K., & Siddiky, M. M. (2023). Path to gain functional transparency in artificial intelligence with meaningful explainability. Journal of Metaverse, 3(2), 166–180. DOI:10.57019/jmv.1306685

Hawblitzel, C., Howell, J., Lorch, J. R., Narayan, A., Parno, B., Zhang, D., & Zill, B. (2014). Ironclad apps:{End-to-End} security via automated {Full-System} verification [presentation]. 11th USENIX symposium on operating systems design and implementation (OSDI 14) (pp. 165–181). https://www.usenix.org/conference/osdi14

Koh, N., Li, Y., Li, Y., Xia, L., Beringer, L., Honoré, W., … & Zdancewic, S. (2019). From C to interaction trees: specifying, verifying, and testing a networked server [presentation]. Proceedings of the 8th ACM SIGPLAN international conference on certified programs and proofs (pp. 234–248). https://doi.org/10.1145/3293880.3294106

Miron, M., Tolan, S., Gómez, E., & Castillo, C. (2021). Evaluating causes of algorithmic bias in juvenile criminal recidivism. Artificial intelligence and law, 29(2), 111–147. DOI:10.1007/s10506-020-09268-y

Bhargavan, K., Delignat-Lavaud, A., Fournet, C., Kohlweiss, M., Pan, J., Protzenko, J., … & Zinzindohoué, J. K. (2017). Implementing and proving the TLS 1.3 record layer [presentation]. SP 2017-38th IEEE symposium on security and privacy (pp. 463–482). https://inria.hal.science/hal-01674096/

Rassmann, K. A. (2022). A goal, question, metric approach to coherent use integration within the devops lifecycle. https://drum.lib.umd.edu/handle/1903/29022

Jim, J. R., Hosain, M. T., Mridha, M. F., Kabir, M. M., & Shin, J. (2023). Towards trustworthy Metaverse: advancements and challenges. IEEE access, 11, 118318–118347. DOI:10.1109/ACCESS.2023.3326258

Liddicoat, J., & Doria, A. (2011). Human rights and internet protocols : comparing processes and principles. Retrieved july, 13, 1–13. https://www.internetsociety.org/wp-content/uploads/2017/08/Human20Rights20and20Internet20Protocols-20Comparing20Processes20and20Principles.pdf

Yellowlees, P. M., & Marks, S. (2007). Problematic internet use or internet addiction? Computers in human behavior, 23(3), 1447–1453.

Chang, C. L., Hung, J. L., Tien, C. W., Tien, C. W., & Kuo, S. Y. (2020). Evaluating robustness of ai models against adversarial attacks [presentation]. Proceedings of the 1st ACM workshop on security and privacy on artificial intelligence (pp. 47–54). https://doi.org/10.1145/3385003.3410920

Bessen, J. E., Impink, S. M., Reichensperger, L., & Seamans, R. (2020). GDPR and the importance of data to AI startups. NYU stern school of business. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3576714

Wachter, S., & Mittelstadt, B. (2019). A right to reasonable inferences: re-thinking data protection law in the age of Big Data and AI. Columbia business law review, 2019(2), 494–620. https://heinonline.org/HOL/LandingPage?handle=hein.journals/colb2019&div=15&id=&page=

Zhou, J., Chen, F., & Holzinger, A. (2022). Towards explainability for AI fairness. In XxAI - beyond explainable AI (Vol. 13200 LNAI, pp. 375–386). DOI: 10.1007/978-3-031-04083-2_18

Dwivedi, Y. K., Kshetri, N., Hughes, L., Rana, N. P., Baabdullah, A. M., Kar, A. K., … & Yan, M. (2023). Exploring the darkverse: a multi-perspective analysis of the negative societal impacts of the Metaverse. Information systems frontiers, 25(5), 2071–2114. DOI:10.1007/s10796-023-10400-x

Kshetri, N. (2022). Policy, ethical, social, and environmental considerations of Web3 and the Metaverse. IT professional, 24(3), 4–8. DOI:10.1109/MITP.2022.3178509

Langvardt, K. (2017). Regulating online content moderation. Geo. LJ, 106, 1353. https://heinonline.org/HOL/LandingPage?handle=hein.journals/glj106&div=39&id=&page=

Voigt, P., & dem Bussche, A. (2017). The eu general data protection regulation (GDPR). Springer.

Gorlini, C., Dixen, L., & Burelli, P. (2023). Investigating the uncanny valley phenomenon through the temporal dynamics of neural responses to virtual characters. 2023 IEEE conference on games (CoG) (pp. 1–8). IEEE. DOI: 10.1109/CoG57401.2023.10333130

Zhang, X., Min, G., Li, T., Ma, Z., Cao, X., & Wang, S. (2023). AI and Blockchain empowered Metaverse for Web 3.0: vision, architecture, and future directions. IEEE communications magazine, 61(8), 60–66. DOI:10.1109/MCOM.004.2200473

Mahmoud, M., Rizou, S., Panayides, A. S., Kantartzis, N. V., Karagiannidis, G. K., Lazaridis, P. I., & Zaharis, Z. D. (2023). A survey on optimizing mobile delivery of 360° videos: edge caching and multicasting. IEEE access, 11, 68925–68942. DOI:10.1109/ACCESS.2023.3292335

Published

2024-08-01

How to Cite

Zaman, A., Abir, M. R., Sakib, T. H., & Reaj, A. H. . (2024). A systematic review of Metaverse environment. Metaversalize, 1(1), 1-20. https://doi.org/10.22105/metaverse.v1i1.17

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