Exploring the Confluence of IoT and Metaverse: Future Opportunities and Challenges
Abstract
:1. Introduction
2. Global Adoption Surveys
- The metaverse is most popular among young adults aged 25–34, followed by those aged 16–24.
- Europe is the largest market for the metaverse, followed by North America and Asia Pacific.
- The Asia Pacific region is expected to be the fastest-growing market for the metaverse due to the increasing adoption of virtual and augmented reality technology in the region.
3. System Architecture and Integration
- IoT Devices: These are the physical devices that are connected to the internet and capable of collecting and transmitting data. They may include sensors, actuators, and communication capabilities. Examples include smart thermostats, cameras, and wearable devices.
- Edge Gateways: These are devices that act as intermediaries between IoT devices and the cloud. They are responsible for collecting and processing data from IoT devices and transmitting them to the cloud. Edge gateways are important for edge computing, which enables low-latency processing of data.
- Cloud Platforms: These are servers and software that are responsible for storing, analysing, and processing data from IoT devices. They may include platforms such as Amazon Web Services or Microsoft Azure.
- Metaverse Platforms: These are the virtual worlds wherein users can interact with each other and digital objects in real time. They may include platforms such as Second Life or VRChat.
- Blockchain Networks: These are decentralised and distributed ledger technologies that are responsible for secure and transparent transactions within the metaverse. They may include platforms such as Ethereum or EOS.
- AI and ML Models: These are used to analyse and make sense of the vast amounts of data generated by IoT devices and to create more realistic and engaging virtual environments.
- Data Security and Privacy: This component is necessary to ensure that data transmitted and stored are protected against unauthorised access and breaches. This is essential for keeping user data private and safe.
- 1.
- Wi-Fi: Wi-Fi is a popular choice for network connectivity as it is widely available and can provide high-speed and reliable connectivity. IoT devices can connect to a Wi-Fi network using a built-in wireless module or an external adapter.
- 2.
- Cellular: Cellular networks, such as 3G, 4G, and 5G, can provide IoT devices with a reliable and secure connection, even in remote or hard-to-reach areas. This option is particularly useful for IoT devices that are located in areas where Wi-Fi is not available.
- 3.
- Low-power wide-area networks (LPWANs): LPWANs, such as LoRaWAN, Sigfox, and NB-IoT, are designed specifically for low-power IoT devices and can provide long-range connectivity. They are particularly useful for IoT devices that are located in remote areas or require low power consumption.
- 4.
- Satellite: Satellite networks can provide IoT devices with connectivity in remote or hard-to-reach areas where other types of networks are not available. This option is particularly useful for IoT devices that are located in areas with no cellular or Wi-Fi coverage.
- 5.
- Mesh networks: Mesh networks are a type of network that allows IoT devices to communicate with each other directly, without the need for a central hub. This type of network is particularly useful for IoT devices that are located in remote or hard-to-reach areas, as it allows for increased reliability and scalability.
- IEEE P2413: This is a standard developed by the Institute of Electrical and Electronics Engineers (IEEE) that defines a reference architecture for the metaverse [47,49]. It provides a framework for the integration of virtual and physical worlds and covers areas such as security, identity, and data management.
- Open Metaverse Interface (OMI): This is a framework that provides a common set of APIs and protocols for different virtual worlds and metaverse platforms. It allows for the interoperability of different virtual worlds and makes it easier for developers to create applications that can be used across multiple platforms [46].
- Virtual Reality Modelling Language (VRML): This is a standard for representing 3D interactive vector graphics, designed particularly for the World Wide Web. VRML is being succeeded by X3D, which is an ISO standard for 3D graphics, and is also compatible with VRML [52].
- OpenXR: This is an open standard for virtual and augmented reality that aims to provide a common API for different VR and AR hardware and software platforms. This makes it easier for developers to create VR and AR applications that can be used across different hardware and software platforms [53].
- ISO/IEC 30141: This is an ISO/IEC standard that describes the requirements and characteristics of an IoT system. It covers various aspects, including security, data management, device management, and communication protocols, which can be applied to IoT systems that collect data from the metaverse [54].
4. Metaverse Platforms and Digital Twins
- Somnium Space: A decentralised and blockchain-based metaverse platform that allows users to buy, rent, and monetise virtual land. Somnium Space is focused on creating a seamless and realistic VR experience, allowing users to interact with each other and the virtual world in real time [61].
- Blue Marble: A metaverse platform that uses blockchain technology to create a decentralised and community-driven virtual world (https://thebluemarble.io/ accessed on 16 January 2023). It allows users to create and share content, as well as engage in commerce and social activities.
5. Artificial Intelligence and Data Processing
- Machine Learning Algorithms: These algorithms can be used to learn from data generated by IoT devices and make predictions about future behaviour [87,88]. Examples include supervised learning algorithms like linear regression and decision trees, unsupervised learning algorithms like k-means and hierarchical clustering, and deep learning algorithms like convolutional neural networks and recurrent neural networks [81].
- Natural Language Processing (NLP) Algorithms: These algorithms can be used to process and understand natural language input, which can be used to improve the user experience by enabling more intuitive and personalised interactions with IoT devices [89]. Examples include part-of-speech tagging, syntactic parsing, and sentiment analysis [90].
- Anomaly Detection Algorithms: These algorithms can be used to detect unusual or abnormal behaviour in IoT data, which can help to identify potential security threats and improve the overall reliability of IoT systems. Examples include statistical methods like Mahalanobis distance and density-based methods like local outlier factor [93,94].
- Generative Algorithms: These algorithms can be used to generate new data that can be used to create new experiences in the metaverse, for example, creating new virtual environments, digital avatars, or digital characters [98].
6. Security and Privacy
7. End-User Applications
8. Future Challenges and Open Issues
9. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
AI | Artificial Intelligence |
AR | Augmented Reality |
CS | Cybersecurity |
DApps | Decentralised Applications |
DDOS | Distributed Denial of Service |
DLT | Distributed Ledger Technology |
GDPR | General Data Protection Regulation |
IDC | International Data Corporation |
IoT | Internet of Things |
IIoT | Industrial Internet of Things |
LPWAN | Low-Power Wide-Area Networks |
ML | Machine Learning |
MR | Mixed Reality |
NB-IOT | Narrow Band IoT |
NLP | Natural Language Processing |
OMI | Open Metaverse Interface |
SD-WAN | Software-Defined Wide-Area Networking |
VR | Virtual Reality |
VRML | Virtual Reality Modelling Language |
VWF | Virtual World Framework |
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Connectivity | Data Rates | Frequency | Latency | Coverage | Cost |
---|---|---|---|---|---|
WiFi | 100–300 Mbps | 2.4/5 GHz | 150 ms | Indoors | Economical |
Cellular 5G | 1 Gbps | 26/66 GHz | 20–50 ms | Outdoors/indoors | Expensive |
LPWAN | 10–50 Kbps | 433 MHz | 300 ms | Indoors | Economical |
Satellite | 10–50 Mbps | 10-/2 GHz | 550 ms | Outdoors | Expensive |
NB-IoT | 60 Kbps | 900 MHz | 1.5 s | Outdoors/indoors | Economical |
Tools | Description | References |
---|---|---|
Unity | Unity is a popular game engine and development platform that can be used to create virtual environments and digital twins. It has built-in support for IoT devices, making it easy to integrate real-world data into virtual environments. | [75] |
Unreal Engine | Similar to Unity, Unreal Engine is another popular game engine and development platform that can be used to create digital twins. It also has built-in support for IoT devices and can be used to create highly detailed and realistic virtual environments. | [76] |
ThingWorx | ThingWorx is an IoT platform that can be used to connect and manage IoT devices, as well as to create and implement digital twin models. It offers a wide range of features and tools for integrating real-world data into virtual environments, such as data visualisation, analytics, and machine learning. | [77,78] |
AWS IoT | AWS IoT is a cloud-based platform that can be used to connect and manage IoT devices, as well as to create and implement digital twin models. It offers a wide range of tools and services to support the integration of IoT and metaverse, such as AWS IoT SiteWise, AWS IoT Things Graph, and AWS IoT Analytics. | [79] |
Bosch IoT | Bosch IoT Suite is an IoT platform that provides a set of tools and services for connecting, managing, and analysing IoT devices. The platform also includes a digital twin capability that allows customers to create virtual models of physical assets, enabling them to make better-informed decisions based on real-time data. | [80] |
Platform | Explanation of Cyber Incident | Year |
---|---|---|
Second Life | A group of hackers known as the “Griefers” launched a series of attacks on the virtual world Second Life. They used a variety of tactics, such as creating fake avatars to flood the virtual world with unwanted objects and stealing virtual currency from other users. The attacks caused widespread disruption and damage to the virtual world and its economy. | 2007 |
World of Warcraft | Hackers launched a distributed denial of service (DDoS) attack on the popular online game World of Warcraft. The attack caused the game’s servers to become overloaded and caused widespread disruption to the game’s player base. | 2010 |
Pokemon Go | The popular mobile game Pokemon Go was targeted by a DDoS attack. The attack caused the game’s servers to become overloaded, making it difficult for players to access the game. | 2016 |
Roblox | A massively multiplayer online game platform was targeted by a cyber-attack that resulted in unauthorised access to user data, specifically user’s information like email addresses and hashed passwords. | 2021 |
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Asif, R.; Hassan, S.R. Exploring the Confluence of IoT and Metaverse: Future Opportunities and Challenges. IoT 2023, 4, 412-429. https://doi.org/10.3390/iot4030018
Asif R, Hassan SR. Exploring the Confluence of IoT and Metaverse: Future Opportunities and Challenges. IoT. 2023; 4(3):412-429. https://doi.org/10.3390/iot4030018
Chicago/Turabian StyleAsif, Rameez, and Syed Raheel Hassan. 2023. "Exploring the Confluence of IoT and Metaverse: Future Opportunities and Challenges" IoT 4, no. 3: 412-429. https://doi.org/10.3390/iot4030018
APA StyleAsif, R., & Hassan, S. R. (2023). Exploring the Confluence of IoT and Metaverse: Future Opportunities and Challenges. IoT, 4(3), 412-429. https://doi.org/10.3390/iot4030018