Search Results (54)

This article presents a novel off-cloud anchor sharing framework designed to enable seamless device interoperability for Mixed Reality (MR) multi-user and multi-platform applications. The proposed framework enables local storage and synchronization of spatial anchors, offering a robust and autonomous alternative for real-time collaborative experiences. Such anchors are digital reference points tied to specific positions in the physical world that allow virtual content in MR applications to remain accurately aligned to the real environment, thus being an essential tool for building collaborative MR experiences. This anchor synchronization system takes advantage of the use of local anchor storage to optimize the sharing process and to exchange the anchors only when necessary. The framework integrates Unity, Mirror and Mixed Reality Toolkit (MRTK) to support seamless interoperability between Microsoft HoloLens 2 devices and desktop computers, with the addition of external IoT interaction. As a proof of concept, a collaborative multiplayer game was developed to illustrate the multi-platform and anchor sharing capabilities of the proposed system. The experiments were performed in Local Area Network (LAN) and Wide Area Network (WAN) environments, and they highlight the importance of efficient anchor management in large-scale MR environments and demonstrate the effectiveness of the system in handling anchor transmission across varying levels of spatial complexity. Specifically, the obtained results show that the developed framework is able to obtain anchor transmission times that start around 12.7 s for the tested LAN/WAN networks and for small anchor setups, and to roughly 86.02–87.18 s for complex physical scenarios where room-sized anchors are required. Full article

Traditional Extended Reality (XR) and Metaverse applications focus heavily on User Experience (UX) but often overlook the role of emotions in user interaction. This article addresses that gap by presenting an emotion-aware Metaverse application: a Virtual Reality (VR) fire drill simulator for shipboard emergency training. The simulator detects emotions in real time, assessing trainees’ responses under stress to improve learning outcomes. Its architecture incorporates eye-tracking and facial expression analysis via Meta Quest Pro headsets. Two experimental phases were conducted. The first revealed issues like poor navigation and lack of visual guidance. These insights led to an improved second version with a refined User Interface (UI), a real-time task tracker and clearer visual cues. The obtained results showed that the included design improvements can reduce task completion times between 14.18% and 32.72%. Emotional feedback varied, suggesting a need for more immersive elements. Overall, this article provides useful guidelines for creating the next generation of emotion-aware Metaverse applications. Full article

The educational system manages extensive documentation and paperwork, which can lead to human errors and sometimes abuse or fraud, such as the falsification of diplomas, certificates or other credentials. In fact, in recent years, multiple cases of fraud have been detected, representing a significant cost to society, since fraud harms the trustworthiness of certificates and academic institutions. To tackle such an issue, this article proposes a solution aimed at recording and verifying academic records through a decentralized application that is supported by a smart contract deployed in the Ethereum blockchain and by a decentralized storage system based on Inter-Planetary File System (IPFS). The proposed solution is evaluated in terms of performance and energy efficiency, comparing the results obtained with a traditional Proof-of-Work (PoW) consensus protocol and the new Proof-of-Authority (PoA) protocol. The results shown in this paper indicate that the latter is clearly greener and demands less CPU load. Moreover, this article compares the performance of a traditional computer and two Single-Board Computers (SBCs) (a Raspberry Pi 4 and an Orange Pi One), showing that is possible to make use of the latter low-power devices to implement blockchain nodes but at the cost of higher response latency. Furthermore, the impact of Ethereum gas limit is evaluated, demonstrating its significant influence on the blockchain network performance. Thus, this article provides guidelines, useful practical evaluations and key findings that will help the next generation of green blockchain developers and researchers. Full article

The increasing proliferation of Internet of Things (IoT) devices has created a growing need for more efficient communication networks, especially in areas where continuous connectivity is unstable or unavailable. Opportunistic networks have emerged as a possible solution in such scenarios, allowing for intermittent and decentralized data sharing. This article presents a novel communication protocol that uses Bluetooth 5 and the libp2p framework to enable decentralized and opportunistic communications among IoT devices. The protocol provides dynamic peer discovery and decentralized management, resulting in a more flexible and robust IoT network infrastructure. The performance of the proposed architecture was evaluated through experiments in both controlled and industrial scenarios, with a particular emphasis on latency and on the impact of the presence of obstacles. The obtained results show that the protocol has the ability to improve data transfer in environments with limited connectivity, making it adequate for both urban and rural areas, as well as for challenging environments such as shipyards. Moreover, the presented findings conclude that the protocol works well in situations with minimal signal obstruction and short distances, like homes, where average latency values of about 8 s have been achieved with no losses. Furthermore, the protocol can also be used in industrial scenarios, even when metal obstacles increase signal attenuation, and over long distances, where average latency values of about 8.5 s have been obtained together with packet losses of less than 5%. Full article

This paper presents a comprehensive study on enhancing Industrial Internet of Things (IIoT) and Industrial Metaverse applications through the integration of On-Device Automatic Speech Recognition (ASR) using Microsoft HoloLens 2 smart glasses. Specifically, this paper focuses on the utilization of the HoloLens 2 microphone array and sound capture APIs to benchmark the performance and accuracy of on-device ASR models. The evaluation of these models includes metrics such as Character Error Rate (CER), Word Error Rate (WER) and latency. In addition, this paper explores various optimization techniques, including quantization tools and model refinement strategies, aimed at minimizing latency while maintaining high accuracy. This study also emphasizes the importance of supporting low-resource languages, using Galician—a language spoken by less than 3 million people worldwide—as a case study. By benchmarking different variations of a Wav2Vec2.0-based ASR model fine-tuned for Galician, the most effective models are identified, as well as their optimal runtime configurations. This work underscores the critical role of low-latency on-device ASR systems in real-time IIoT and Industrial Metaverse applications, highlighting how these technologies can enhance operational efficiency, privacy and user experience in industrial environments. The findings demonstrate the significant potential of the on-device ASR system developed to enhance voice interactions in emerging Metaverse applications, specially for low-resource languages. Full article

Security presents significant challenges due to the exponential growth in the number of Internet of Things (IoT) devices that generate and collect data over the network. It is crucial to ensure the integrity and security of IoT devices, as well as to address issues such as interoperability and trust in data sources. In the proposed article, we present a novel architecture together with its implementation as a proof-of-concept of a traceability and auditing IoT system based on Distributed Ledger Technology (DLT). To demonstrate the applicability of the proposed solution, a smart contract-based system for occupational risk prevention (ORP) has been developed to monitor oxygen concentration in confined spaces that exist in ships and shipyards. The system has been devised for the operators that weld inside the ships of the Spanish shipbuilding company Navantia, which is one of the largest shipbuilders in the world. Specifically, the IOTA network has been used, which benefits the system through its decentralized, secure, and scalable data structure. In addition, the integration of smart contracts allows for establishing predefined rules and conditions, ensuring the execution of logic in a reliable and automated manner. To demonstrate the viability of the system, it has been tested locally and in the IOTA testing environment. Despite the challenges in deploying smart contracts with IOTA, the developed system is considered useful for the traceability and auditing of the oxygen concentrations without the need for any human intervention. Furthermore, it establishes the groundwork for future advancements in IoT traceability and auditing in industrial ORP scenarios. Full article

While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to leverage operator capabilities in order to meet the goals of complex manufacturing systems towards human-centricity, resilience and sustainability. This article first describes the essential concepts for the development of Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main design requirements and key implementation components. Moreover, the major challenges for the development of such CPHSs are outlined. Next, to illustrate the previously described concepts, a real-world Industry 5.0 CPHS is presented. Such a CPHS enables increased operator safety and operation tracking in manufacturing processes that rely on collaborative robots and heavy machinery. Specifically, the proposed use case consists of a workshop where a smarter use of resources is required, and human proximity detection determines when machinery should be working or not in order to avoid incidents or accidents involving such machinery. The proposed CPHS makes use of a hybrid edge computing architecture with smart mist computing nodes that processes thermal images and reacts to prevent industrial safety issues. The performed experiments show that, in the selected real-world scenario, the developed CPHS algorithms are able to detect human presence with low-power devices (with a Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04% accuracy), thus being an effective solution (e.g., a good trade-off between cost, accuracy, resilience and computational efficiency) that can be integrated into many Industry 5.0 applications. Finally, this article provides specific guidelines that will help future developers and managers to overcome the challenges that will arise when deploying the next generation of CPHSs for smart and sustainable manufacturing. Full article

The limitations of many IoT devices in terms of storage, computing power and energy consumption require them to be connected to other devices when performing computationally intensive tasks, as happens with IoT systems based on edge computing architectures. However, the lack of wireless connectivity in the places where IoT nodes are deployed or through which they move is still a problem. One of the solutions to mitigate this problem involves using opportunistic networks, which provide connectivity and processing resources efficiently while reducing the communications traffic with remote clouds. Thus, opportunistic networks are helpful in situations when wireless communication coverage is not available, as occurs in certain rural areas, during natural disasters, in wars or when other factors cause network disruptions, as well as in other IoT scenarios in which the cloud becomes saturated (for example, due to an excessive amount of concurrent communications or when denial-of-service (DoS) attacks occur). This article presents the design and initial validation of a novel opportunistic edge computing (OEC) system based on Bluetooth 5 and the use of low-cost single-board computers (SBCs). After describing the proposed OEC system, experimental results are presented for a real opportunistic vehicular IoT scenario. Specifically, the latency and packet loss are measured thanks to the use of an experimental testbed made of two separate IoT networks (each conformed by an IoT node and an OEC gateway): one located in a remote office and another one inside a moving vehicle, which was driven at different vehicular speeds. The obtained results show average latencies ranging from 716 to 955 ms with packet losses between 7% and 27%. As a result, the developed system is useful for providing opportunistic services to moving IoT nodes with relatively low latency requirements. Full article

IoT devices can be deployed almost anywhere, but they usually need to be connected to other IoT devices, either through the Internet or local area networks. For such communications, many IoT devices make use of wireless communications, whose coverage is key: if no coverage is available, an IoT device becomes isolated. This can happen both indoors (e.g., large buildings, industrial warehouses) or outdoors (e.g., rural areas, cities). To tackle such an issue, opportunistic networks can be useful, since they use gateways to provide services to IoT devices when they are in range (i.e., IoT devices take the opportunity of having a nearby gateway to exchange data or to use a computing service). Moreover, opportunistic networks can provide Edge Computing capabilities, thus creating Opportunistic Edge Computing (OEC) systems, which deploy smart gateways able to perform certain tasks faster than a remote Cloud. This article presents a novel decentralized OEC system based on Bluetooth 5 IoT nodes whose latency is evaluated to determine the feasibility of using it in practical applications. The obtained results indicate that, for the selected scenario, the average end-to-end latency is relatively low (736 ms), but it is impacted by factors such as the location of the bootstrap node, the smart gateway hardware or the use of high-security mechanisms. Full article

The progress of LPWAN technologies in recent years has increased their use in various types of environments as well as increased the applications in which they are used. However, due to the duty cycle limitations of license-free based technologies, they have a considerable limitation for applications with frequent data transmission or real-time data. In this regard, technologies working in the 2.4 GHz band are a compelling option to consider but their main problem concerns their limited range. Fortunately, the new Bluetooth 5 standard has a new feature (Long Range mode) that is especially useful in long distance or large indoor environments. This paper describes a practical study on this new technology for indoor environments. The performed experiments evaluate reception range, communications quality, channel occupancy, response times, and power consumption. The obtained results indicate that a three-floor building of more than 4200 m${}^2$ may be covered with a stable signal with only two Bluetooth 5 nodes. Full article

Large companies use a lot of resources on workshop operator training and industrial machinery maintenance since the lack of this practice or its poor implementation increases the cost and risks of operating and handling sensitive and/or hazardous machinery. Industrial Augmented Reality (IAR), a major technology in the Industry 4.0 paradigm that may enhance worker performance, minimize hazards and improve manufacturing processes, could be beneficial in this situation. This paper presents an IAR solution that allows for visualizing and interacting with the digital twin of a critical system. Specifically, the augmented digital twin of an industrial cooler was developed. The proposed IAR system provides a dynamic way to perform operator training with a full-size model of the actual equipment and to provide step-by-step guidance so that maintenance processes can be performed more safely and efficiently. The proposed system also allows several users to use devices at the same time, creating a new type of collaborative interaction by viewing the model in the same place and state. Performance tests with many simultaneous users have been conducted, with response latency being measured as the number of connected users grows. Furthermore, the suggested IAR system has been thoroughly tested in a real-world industrial environment. Full article

The emergence of the current pandemic has led to a new reality in which bureaucratic formalities have been affected in terms of health security, procedures, resource management, among others. Specifically, in the electoral processes, where the difficulty of fulfilling the social distance and the mobility restrictions reopen the debate on the implementation of other more advanced and modern alternatives, such as electronic voting (e-voting). This article presents the design and implementation of a decentralized e-voting system that has the potential to provide a higher level of transparency, security, and cost-efficiency. Hyperledger Fabric blockchain and smart contracts are used to cast votes, which are then recorded in an immutable way, giving voters anonymity and trust in the fairness of the election process. In addition, promising results of the performance of the e-voting system in terms of latency and transaction load are presented. Full article

Internet of Things (IoT) can help to pave the way to the circular economy and to a more sustainable world by enabling the digitalization of many operations and processes, such as water distribution, preventive maintenance, or smart manufacturing. Paradoxically, IoT technologies and paradigms such as edge computing, although they have a huge potential for the digital transition towards sustainability, they are not yet contributing to the sustainable development of the IoT sector itself. In fact, such a sector has a significant carbon footprint due to the use of scarce raw materials and its energy consumption in manufacturing, operating, and recycling processes. To tackle these issues, the Green IoT (G-IoT) paradigm has emerged as a research area to reduce such carbon footprint; however, its sustainable vision collides directly with the advent of Edge Artificial Intelligence (Edge AI), which imposes the consumption of additional energy. This article deals with this problem by exploring the different aspects that impact the design and development of Edge-AI G-IoT systems. Moreover, it presents a practical Industry 5.0 use case that illustrates the different concepts analyzed throughout the article. Specifically, the proposed scenario consists in an Industry 5.0 smart workshop that looks for improving operator safety and operation tracking. Such an application case makes use of a mist computing architecture composed of AI-enabled IoT nodes. After describing the application case, it is evaluated its energy consumption and it is analyzed the impact on the carbon footprint that it may have on different countries. Overall, this article provides guidelines that will help future developers to face the challenges that will arise when creating the next generation of Edge-AI G-IoT systems. Full article