Methodological Approaches for Monitoring Five Major Food Safety Hazards Affecting Food Production in the Galicia–Northern Portugal Euroregion

The agri-food industry has historically determined the socioeconomic characteristics of Galicia and Northern Portugal, and it was recently identified as an area for collaboration in the Euroregion. In particular, there is a need for action to help to ensure the provision of safe and healthy foods by taking advantage of key enabling technologies. The goals of the FOODSENS project are aligned with this major objective, specifically with the development of biosensors able to monitor hazards relevant to the safety of food produced in the Euroregion. The present review addresses the state of the art of analytical methodologies and techniques—whether commercially available or in various stages of development—for monitoring food hazards, such as harmful algal blooms, mycotoxins, Listeria monocytogenes, allergens, and polycyclic aromatic hydrocarbons. We discuss the pros and cons of these methodologies and techniques and address lines of research for point-of-care detection. Accordingly, the development of miniaturized automated monitoring strategies is considered a priority in terms of health and economic interest, with a significant impact in several areas, such as food safety, water quality, pollution control, and public health. Finally, we present potential market opportunities that could result from the availability of rapid and reliable commercial methodologies.

Smart Manufacturing and Tactile Internet Based on 5G in Industry 4.0: Challenges, Applications and New Trends

For many applications deployed in manufacturing networks, communication latency has been a significant barrier. Despite the constant development of improved communication protocols and standards during Industry 4.0, the latency problem persists, lowering quality of services (QoS) and quality of experience (QoE). Tactile internet (TI), with its high availability, security, and ultra-low latency, will add a new dimension to human-machine interaction (HMI) by enabling haptic and tactile sensations. The tactile internet (TI) is a cutting-edge technology that uses 5G and beyond (B5G) communications to enable real-time interaction of haptic data over the internet between tactile ends. This emerging TI technology is regarded as the next evolutionary step for the Internet of Things (IoT) and is expected to bring about massive changes towards Society 5.0 and to address complex issues in current society. To that end, the 5G mobile communication systems will support the TI at the wireless edge. As a result, TI can be used as a backbone for delay mitigation in conjunction with 5G networks, allowing for ultra-reliable low latency applications like Smart Manufacturing, virtual reality, and augmented reality. Consequently, the purpose of this paper is to present the current state of 5G and TI, as well as the challenges and future trends for 5G networks beyond 2021, as well as a conceptual framework for integrating 5G and TI into existing industrial case studies, with a focus on the design aspects and layers of TI, such as the master, network, and slave layers. Finally, the key publications focused on the key enabling technologies of TI are summarized and the beyond 5G era towards Society 5.0 based on cyber-physical systems is discussed.

Twin Transition through the Implementation of Industry 4.0 Technologies: Desk-Research Analysis and Practical Use Cases in Europe

Key Enabling Technologies (KET) support the adoption of Industry 4.0 (I4.0) and are also considered the main drivers of the Circular Economy (CE) transition. In this respect, the guidelines and real use cases to inspire enterprises and industry to lead the twin digital and green transition are still poor. This work is aimed at contributing to this matter, with twofold goals: on the one hand, to show a depth desk-research analysis of the key existing policies at European level that foster this twin digital and green transition; on the other hand, to review practical use cases and international projects where CE practices are boosted through the implementation of KET. From the analysis, a set of recommendations are suggested as a guide for policymakers, researchers, and industry managers on how to foster the CE through the implementation of I4.0 technologies.

Beyond private 5G networks: applications, architectures, operator models and technological enablers

Private networks will play a key role in 5G and beyond to enable smart factories with the required better deployment, operation and flexible usage of available resource and infrastructure. 5G private networks will offer a lean and agile solution to effectively deploy and operate services with stringent and heterogeneous constraints in terms of reliability, latency, re-configurability and re-deployment of resources as well as issues related to governance and ownership of 5G components, and elements. In this paper, we present a novel approach to operator models, specifically targeting 5G and beyond private networks. We apply the proposed operator models to different network architecture options and to a selection of relevant use cases offering mixed private–public network operator governance and ownership. Moreover, several key enabling technologies have been identified for 5G private networks. Before the deployment, stakeholders should consider spectrum allocation and on-site channel measurements in order to fully understand the propagation characteristic of a given environment and to set up end-to-end system parameters. During the deployment, a monitoring tools will support to validate the deployment and to make sure that the end-to-end system meet the target KPI. Finally, some optimization can be made individually for service placement, network slicing and orchestration or jointly at radio access, multi-access edge computing or core network level.

Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions

The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mechanisms to improve industrial processes and applications. In large industrial networks, smart devices generate large amounts of data, and thus IIoT frameworks require intelligent, robust techniques for big data analysis. Artificial intelligence (AI) and deep learning (DL) techniques produce promising results in IIoT networks due to their intelligent learning and processing capabilities. This survey article assesses the potential of DL in IIoT applications and presents a brief architecture of IIoT with key enabling technologies. Several well-known DL algorithms are then discussed along with their theoretical backgrounds and several software and hardware frameworks for DL implementations. Potential deployments of DL techniques in IIoT applications are briefly discussed. Finally, this survey highlights significant challenges and future directions for future research endeavors.

Customising Tourism Experiences with Use of Advanced Technologies, Example of Collaboration Impact Token and Digital Online Tourist Identity

Nowadays, data on tourist profiles are created by large platforms that exchange and trade the collected data with each other without sharing it with service providers (hotels, restaurants, etc.). Providers are thus increasingly becoming mere "executors" and cannot devote themselves to the guest as they once did. Using the example of Collaboration Impact Token and Digital Online Tourist Identity, the article suggests the development of a sys-tem with use of key enabling technologies from Industry 4.0 that will offer guests a personalised service, re-ward them for positive behavior if they are contributing to the positive effects of tourism and redirect them on less burdened areas with the aim to offer a significantly better tourist experience and the development of more balanced sustainable development.

New Results on Diffusion in Graphene Nanostructures for Sensoristics

Graphene has particularly interesting chemical and physical properties, including high chemical and mechanical resistance, excellent thermal and electric transport, high transparency. It combines the peculiarity of being an extremely light material with exceptional mechanical strength properties. Micro/nanoelectronics represents one of the key enabling technologies (KETs) of the future; it is the basis of innovation and competitiveness of almost all scientific and applicative sectors. Activities involving it are aimed at the development of new materials, processes, devices and technologies in a wide range of sectors, involving quantum information manipulation, multi-functional platforms, advanced materials, devices on flexible substrates. In the field of sensoristics, it is possible to create devices for applications in most sectors of global interest, such as punctual sensors, biosensors, specific transducers, multisensoristic systems, flexible sensoristic systems, multifunctional systems, advanced MEMS/MOEMS technologies for sensoristics, micro/nanoactuators, devices for energy convertion, gravimetric-electrochemical sensors. The paper provides an interesting overview of the possible applications of graphene in relation to its mechanical, thermal and optical properties, and relatively to the gas and biological sensoristic aspects, so as interesting informations for the increase in nanobio-devices performance by last efforts in theoretical nanophysics.

Digital twin data: methods and key technologies

As a promising technology to converge the traditional industry with the digital economy, digital twin (DT) is being investigated by researchers and practitioners across many different fields. The importance of data to DT cannot be overstated. Data plays critical roles in constructing virtual models, building cyber-physical connections, and executing intelligent operations. The unique characteristics of DT put forward a set of new requirements on data. Against this background, this paper discusses the emerging requirements on DT-related data with respect to data gathering, mining, fusion, interaction, iterative optimization, universality, and on-demand usage. A new notion, namely digital twin data (DTD), is introduced. This paper explores some basic principles and methods for DTD gathering, storage, interaction, association, fusion, evolution and servitization, as well as the key enabling technologies. Based on the theoretical underpinning provided in this paper, it is expected that more DT researchers and practitioners can incorporate DTD into their DT development process.

Wearable Movement Sensors in Osteoarthritis: Narrative Review (Preprint)

BACKGROUND The objective of this study is to review and summarize recent developments in wearable technology detailing the key enabling technologies (i.e., sensor components) and applications of wearable technology as they relate to lower extremity osteoarthritis. OBJECTIVE The objective of this study is to review and summarize recent developments in wearable technology detailing the key enabling technologies (i.e., sensor components) and applications of wearable technology as they relate to lower extremity osteoarthritis. METHODS A literature search was performed in March 2021 using the PubMed and EMBASE databases for publications on wearable movement technologies in lower-limb OA. Papers published within the previous 5 years were identified. The search was limited to original research studies published in English. Duplicate studies, systematic reviews, conference abstracts, and study protocols were removed. Sample keywords and their combinations included: (osteoarthritis OR TKA OR total knee arthroplasty OR total knee replacement) AND (wearable* OR sensor). RESULTS From the literature, 72 studies were determined relevant and subsequently included in this review. Wearable technology has successfully been implemented for gait assessment, movement pattern training using feedback, assessment of intervention outcomes, and physical activity monitoring. Additionally, some studies demonstrated algorithms or measurement systems that could be used for movement pattern training with feedback in future implementations. Study participants identified appearance and comfort during use as key aspects for the acceptance of wearable technology, and enjoyed seeing both quantitative sensor data as well as qualitative patient-reported outcomes. CONCLUSIONS Advancements in wearable sensor technology allow for data collection and analysis in both accurate and unobtrusive ways. The technology can be used to passively collect data, implement exercise interventions, or actively retrain movement patterns. Future opportunities remain to have more efficient, smaller systems and provide biofeedback for new, previously unused metrics.

The Use of Key Enabling Technologies in the Nearly Zero Energy Buildings Monitoring, Control and Intelligent Management

The 2018 revision of the European Performance Building Directive (EPBD) requires that from the year 2020 onwards, all new buildings will have to be “nearly zero energy buildings”. It also further promotes smart building technologies, raising awareness amongst building owners and occupants of the value behind building automation. The European Commission also identified, in 2011, Key Enabling Technologies (KETs), which provide the basis for innovation in the EU. In the frame of the SUDOKET project, the Solar XXI building was used as a pilot case, as innovative integrated solutions and technologies are monitored and controlled. The objective of this paper is to validate a simulation of the laboratorial test room in EnergyPlus with data obtained experimentally and determine the impact of the control systems on energy needs and on thermal comfort. Two systems, in particular, were studied: the Building-Integrated Photovoltaic (BIPV) and the earth tubes. Once validated, the simulation of the test room without the systems was created, allowing their impact to be determined. The results show that, for the analysed periods, BIPVs reduced the heating consumption by 22% while also increasing thermal comfort, and the earth tube system would reduce the cooling needs by 97%.