The Industrial Metaverse paradigm can be broadly described as a virtual environment that integrates various technologies such as augmented reality and mixed reality to enhance business operations and processes. It aims to streamline workflows, reduce error rates, improve efficiency, and provide a more engaging experience for employees. The promise of the Industrial Metaverse to drive sustainability and resource efficiency is compelling. Using advanced technologies such as the Industrial Metaverse is vital in an endeavor to have a competitive edge in a rapidly evolving business environment. However, the environmental impact of the technologies underpinning the Industrial Metaverse, like data centers and network infrastructure, should not be overlooked. The ecological footprint of these technologies must be considered in the sustainability equation. Researchers have warned that, by 2025, without sustainable artificial intelligence (AI) practices, AI will consume more energy than the human workforce, significantly offsetting zero carbon gains. As the Metaverse persists in evolving and gaining momentum, it will be necessary for companies to prioritize sustainability and explore new ways to balance technological advancements with environmental stewardship. However, recent studies have conjectured that the Metaverse holds the potential to reduce carbon emissions, as digital replacements for physical goods become more prevalent and physical activities like mobility and construction are reduced. Moreover, the specific extent to which this substitution can alleviate environmental concerns remains an open issue, presenting a knowledge gap in understanding the real-world impact of digital replacements. Thus, the objective of this paper is to provide a comprehensive review of the Industrial Metaverse, as well as explore the environmental impact of the Industrial Metaverse. The integrative literature review design and methodological approach involved multiple sources from the Web of Science and databases such as the ACM library, IEEE Library, and Google Scholar, which were analyzed to provide a comprehensive understanding of the developments in the Industrial Metaverse. Firstly, by considering the Industrial Metaverse’s architecture, we elucidate the Industrial Metaverse concept and the associated enabling technologies. Secondly, we performed an exploration through a discussion of the prevalent use cases and the deployment of the emerging Industrial Metaverse. Thirdly, we explored the impact of the Industrial Metaverse on the environment. Lastly, we address novel security and privacy risks, as well as upcoming research challenges, keeping in mind that the Industrial Metaverse is based on a strong data fabric. The results point to the Industrial Metaverse as having both positive and negative environmental effects in terms of energy consumption, e-waste, and pollution. Research, however, indicates that most Industrial Metaverse applications have a positive environmental impact and subsequently trend toward sustainability. Finally, for sustainability in the Industrial Metaverse, enterprises may consider utilizing renewable energy sources and cloud services. Furthermore, we examined the effects of products on the environment, as well as in the creation of a circular economy.

The exponential growth in wireless communication demands intelligent and adaptive spectrum-sharing solutions, especially within dynamic and densely populated 6G Cognitive Radio Networks (CRNs). This paper introduces a novel hybrid framework combing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) with Proximal Policy Optimisation (PPO) for multi-objective optimisation in spectrum management. The proposed model balances spectrum efficiency, interference mitigation, energy conservation, collision rate reduction, and QoS maintenance. Evaluation on synthetic and ns-3 datasets shows that the NSGA-II and PPO hybrid consistently outperforms the random, greedy, and stand-alone PPO strategies, achieving higher cumulative reward, perfect fairness (Jain’s Fairness Index = 1.0), robust hypervolume convergence (65.1%), up to 12% reduction in PU collision rate, 20% lower interference, and approximately 40% improvement in energy efficiency. These findings validate the framework’s effectiveness in promoting fairness, reliability, and efficiency in 6G wireless communication systems.

The industrial metaverse paradigm is generally a virtual environment that integrates various technologies such as augmented reality (AR) and mixed reality (MR) to enhance business operations and processes. It aims to streamline workflows, reduce error rates, improve efficiency, and provide a more engaging experience for employees. The promise of the industrial Metaverse to drive sustainability and resource efficiency is compelling. Utilizing advanced technologies like the Industrial Metaverse is essential for staying competitive in today’s rapidly evolving business environment. However, the environmental impact of the technologies underpinning the industrial metaverse, like data centres and network infrastructure, should not be overlooked. The ecological footprint of these technologies must be considered in the sustainability equation. Researchers have warned that by 2025, without sustainable AI practices, AI will consume more energy than the human workforce, significantly offsetting carbon-zero gains. As the metaverse persists in evolving and gaining momentum, it will be necessary for companies to prioritize sustainability and explore new ways to balance technological advancements with environmental stewardship. However, recent studies have conjectured that the Metaverse holds the potential to reduce carbon emissions, as digital replacements for physical goods become more prevalent and physical activities like mobility and construction are reduced. However, the specific extent to which this substitution can alleviate environmental concerns remains understudied, presenting a knowledge gap in understanding the real-world impact of digital replacements. Thus, the objective of this paper is to provide a comprehensive review of the industrial metaverse as well as explore the environmental impact of the industrial metaverse. The methodological approach is that of integrative literature review design wherein multiple sources from web science and databases such as ACM library, IEEE Library, and Google Scholar, were analysed to provide a comprehensive understanding of the developments in the industrial metaverse. Specifically, firstly by considering the Industrial metaverse architecture we elucidate the concept of the "industrial metaverse" and the associated enabling technologies. Secondly, an exploration through discussion, of the prevalent use cases and deployment of the emerging industrial metaverse. Thirdly, exploration of the impact of the industrial metaverse on the environment. In the fourth instance, we address novel security and privacy risks as well as upcoming research challenges, keeping in mind that the industrial metaverse is based on a strong data fabric. Results point to the Industrial Metaverse as having both positive and negative environmental effects by energy consumption, e-waste, and pollution. Overall research, however, indicates that most industrial metaverse applications have a positive environmental impact and subsequently trend toward sustainability. Ultimately for sustainability in the industrial metaverse, enterprises may consider utilizing renewable energy sources and cloud services. Furthermore, examining the effects of products on the environment as well as creating a circular economy.

Wireless network generations are defined by advancements in transmission technology and the utilization of different frequency bands over time. During the development of numerous wireless network generations, they have significantly impacted society by influencing how people live, learn, work and communicate. In the different phases of wireless network generations, from the first generation (1G) to the current fifth generation (5G), some serious challenges have affected the operation and efficiency of networks. This chapter traces the evolution of wireless networks from their inception to the advent of 5G and beyond. It examines the key technological advancements that have driven this evolution, including the shift from analog to digital, the emergence of mobile broadband, and the increasing reliance on higher frequencies and advanced signal processing techniques. Furthermore, the chapter analyzes the societal and economic impacts of each generation of wireless technology, highlighting the transformative effects on communication, commerce, and daily life. Finally, the chapter delves into the potential of 6G and beyond, discussing emerging technologies like terahertz communication, holographic beamforming, and AI-powered network management, and their potential to revolutionize industries such as healthcare, transportation, and manufacturing. The chapter concludes by discussing the challenges and opportunities associated with this rapid technological advancement.

Our global food system faces growing challenges such as population growth, climate change, resource constraints, and food loss. This set of threats has begun to erode the stability of food security efforts and challenge the long-term sustainability goals outlined by global organizations. To respond effectively, the sector needs concrete and forward-looking innovations that reflect the objectives of the Sustainable Development Goals (SDGs) of the United Nations (UN), especially the commitment in Goal 2 to eliminate hunger. In this study, we examine how agricultural robotics can support the shift toward more resilient and sustainable food systems, particularly in areas where classical methods are under strain. It brings together perspectives from technology, sustainability, and policy, aiming to bridge broad global priorities with everyday realities faced in local contexts. To structure the discussion in a concise way, our analysis is framed around five different, yet interrelated, dimensions. First, we use a crisis-framing perspective to explain why food system reform has become urgent and to show how these pressures align with key SDG priorities. The second dimension outlines a simple taxonomy that groups agricultural robots according to their domain and intended function while also highlighting ongoing technical issues such as interoperability. The next dimension examines how robotics is being amalgamated with precision farming tools, Internet of Things (IoT) platforms, artificial intelligence (AI), and big data systems. Collectively, these technologies facilitate more autonomous field operations and support faster, data-driven decision making. The sustainability dimension evaluates how these technologies affect environmental, economic, and social outcomes in the agricultural sector. This comprehensive review highlights several potential advantages, such as reduced chemical inputs, improved water efficiency, improvements in soil quality, more efficient use of labor, and new employment opportunities in rural and remote areas. In the final dimension, this study turns to global case studies, drawing comparative insights between developed nations such as Australia and the United States, and emerging economies including Brazil, India, and China. Across these diverse contexts, agricultural robotics consistently demonstrate the capacity to boost productivity, reduce waste, and make more efficient use of resources. It is apparent that these gains extend beyond the farm, contributing to environmental stewardship and broader socio-economic development. Yet, the path to widespread adoption is far from straightforward. Farmers and policymakers alike confront persistent barriers: the high upfront costs of robotic systems, gaps in technical expertise, difficulties in ensuring interoperability across platforms, and pressing ethical questions around data governance and automation. Overcoming these challenges is not simply a technical exercise; it is a prerequisite for realizing the full promise of robotics in reshaping global food systems for a more sustainable future.

This study addressed the transmission of traditional culture through digital technology gap in Zimbabwe using the descriptive design. Purposive sampling was used to select the headman and the chief and residents from the Chundu Village who were interviewed as they are the custodians of the traditions. Documented information revealed how values and norms had been transmitted. The study used a questionnaire and an interview schedule to collect data from the field. In addition, observational data was gathered through visits to virtual museums and digital archives. This involved watching how individuals interacted with social networking sites. Data was analyzed through the thematic approach. The study concludes that digital technology played an important role in the transmission and preservation of the Zimbabwean traditional culture. Therefore, there is a need to improve internet accessibility in the country so that people may manage to access the cultural heritage through digital technologies. While digital experts have the knowledge of how to use current technology from the information super high way to the hardware information communication technologies, traditional practitioners are the curators the tradition as they know what is vital and what has value in terms of their traditional norms and values. By combining traditional practitioners and digital experts, it makes it very easy to reach the goal of preserving the traditional culture through digital technology.