Enabling Technologies Research Articles

Technology Enabled Remote Monitoring in Schools(TERMS): A Case Study Series Using Parallel Testing in Clinical Settings and School Workshops

Technology Enabled Remote Monitoring in Schools(TERMS): A Case Study Series Using Parallel Testing in Clinical Settings and School Workshops

Editorial — Special Issue on Advanced Air Mobility: Enabling Technologies and Applications

Editorial — Special Issue on Advanced Air Mobility: Enabling Technologies and Applications

A Framework for FDM-based DFAM: Key Enabling Technologies for Knowledge-based Design

The booming and evolution of additive manufacturing (AM) technologies call for robust key enabling technologies and solutions to the ongoing advancement of AM. However, there are limitations to the fused deposition modeling-based design for AM (FDM-based DFAM), including an inadequate understanding of the process activities and the progressive industrialization, which make the concept generation operations unreliable, inconsistent, and of limited influence. This paper proposes a principle knowledge-based framework for enabling technologies in FDM-based DFAM to provide solutions to the abovementioned engineering problems to increase the viability of industrial applications. Consequently, a case study application is used to verify the feasibility and effectiveness of our approach.

Power allocation scheme for sum rate and fairness trade-off in downlink NOMA networks

Non-orthogonal multiple access (NOMA) is an essential enabler technology that is expected to help satisfy the key requirements of increased system throughput in future wireless networks. However, another equally important aspect that should go hand-in-hand with system throughput is user fairness for any network. But, to the best of our knowledge, even though there have been works that look at system throughput or user fairness maximization for NOMA-based networks, they looked at these as a single objective optimization problem, where one is the objective and the other is one of the constraints. However, quite often, joint optimization of both system throughput and user fairness is required to make optimized decisions in the face of trade-offs between these two equally important but conflicting objectives. In this regard, this paper formulates a multi-objective optimization problem to jointly maximize the sum rate and user fairness in a downlink transmission NOMA system, through optimize power allocation (PA), under system-imposed constraints. A weighted sum approach is used to turn the multi-objective optimization problem into a single-objective optimization problem to make it analytically tractable. The optimized PA is then obtained using Lagrange dual decomposition method and Karush–Kuhn–Tucker (KKT) conditions. Using our derived expressions, we propose an iterative PA algorithm that converges fast enough to be employed in practical NOMA networks. We also present simulation results to highlight the effectiveness of the proposed solution. Further, the performance of the proposed method is compared with that of the benchmark methods.

Internet of Things (IoT) Its Applications and Enabling Technologies in Healthcare: A Review

Internet of Things (IoT) Its Applications and Enabling Technologies in Healthcare: A Review

Analysis of Hydrogen Combustion in a Spark Ignition Research Engine with a Barrier Discharge Igniter

Hydrogen fuel is gaining particular attention in internal combustion engines. In addition to zero-carbon emissions, major advantages relate to its combustion characteristics, which allow a significant increase in thermal efficiency under ultra-lean operation and with very low NOx levels. The ignition system is one of the main technology enablers, as it determines the capability to control ultra-lean operations, avoid backfire phenomena, and/or reduce the risks of abnormal combustions. The latter results from hydrogen’s low ignition energy and it is associated with factors like high-temperature residuals, hot spots, and irregular spark plug discharge. The ACIS gen 2-Barrier Discharge Igniter excels in accelerating the initial flame growth speed by the generation of non-equilibrium low-temperature plasma, a strong ignition promoter for the combined action of kinetic and thermal effects. Moreover, its volumetric discharge facilitates combustion initiation on a wide region, in contrast to the localized ignition of traditional spark systems. In this work we present for the first time, to the best of our knowledge, experimental results showing the performance of a hydrogen engine with a low-temperature plasma discharge. Tests were conducted on a single-cylinder research engine, achieving ultra-lean conditions with cycle-to-cycle variability results below 2.5%. The analysis indicates that the H2-BDI combined solution is capable of accelerating the evolution of the flame front compared to traditional spark plugs, leading to a significant reduction in the cycle-to-cycle variability. A meticulous adjustment of the BDI control parameters further enhances igniter performance and contributes to a deeper understanding of the innovative approach proposed in this study.

Renewable Methanol as a Fuel for Heavy-Duty Engines: A Review of Technologies Enabling Single-Fuel Solutions

To meet climate targets, a global shift away from fossil fuels is essential. For sectors where electrification is impractical, it is crucial to find sustainable energy carriers. Renewable methanol is widely considered a promising fuel for powering heavy-duty applications like shipping, freight transport, agriculture, and industrial machines due to its various sustainable production methods. While current technological efforts focus mainly on dual-fuel engines in shipping, future progress hinges on single-fuel solutions using renewable methanol to achieve net-zero goals in the heavy-duty sector. This review examines the research status of technologies enabling methanol as the sole fuel for heavy-duty applications. Three main categories emerged from the literature: spark-ignition, compression-ignition, and pre-chamber systems. Each concept’s operational principles and characteristics regarding efficiency, stability, and emissions were analyzed. Spark-ignition concepts are a proven and cost-effective solution with high maturity. However, they face limitations due to knock issues, restricting power output with larger bore sizes. Compression-ignition concepts inherently do not suffer from end-gas autoignition, but encounter challenges related to ignitability due to the low cetane number of methanol. Nonetheless, various methods for achieving autoignition of methanol exist. To obtain stable combustion at all load points, a combination of techniques will be required. Pre-chamber technology, despite its lower maturity, holds promise for extending the knock limit and enhancing efficiency by acting as a distributed ignition source. Furthermore, mixing-controlled pre-chamber concepts show potential for eliminating knock and the associated size and power limitations. The review concludes by comparing each technology and identifying research gaps for future work.

Towards a Human-Centric Digital Twin for Human-Machine Collaboration: A Review on Enabling Technologies and Methods.

With the intent to further increase production efficiency while making human the centre of the processes, human-centric manufacturing focuses on concepts such as digital twins and human-machine collaboration. This paper presents enabling technologies and methods to facilitate the creation of human-centric applications powered by digital twins, also from the perspective of Industry 5.0. It analyses and reviews the state of relevant information resources about digital twins for human-machine applications with an emphasis on the human perspective, but also on their collaborated relationship and the possibilities of their applications. Finally, it presents the results of the review and expected future works of research in this area.

A Topical Review on Enabling Technologies for the Internet of Medical Things: Sensors, Devices, Platforms, and Applications.

The Internet of Things (IoT) is still a relatively new field of research, and its potential to be used in the healthcare and medical sectors is enormous. In the last five years, IoT has been a go-to option for various applications such as using sensors for different features, machine-to-machine communication, etc., but precisely in the medical sector, it is still lagging far behind compared to other sectors. Hence, this study emphasises IoT applications in medical fields, Medical IoT sensors and devices, IoT platforms for data visualisation, and artificial intelligence in medical applications. A systematic review considering PRISMA guidelines on research articles as well as the websites on IoMT sensors and devices has been carried out. After the year 2001, an integrated outcome of 986 articles was initially selected, and by applying the inclusion-exclusion criterion, a total of 597 articles were identified. 23 new studies have been finally found, including records from websites and citations. This review then analyses different sensor monitoring circuits in detail, considering an Intensive Care Unit (ICU) scenario, device applications, and the data management system, including IoT platforms for the patients. Lastly, detailed discussion and challenges have been outlined, and possible prospects have been presented.

Multi-Layered Satellite Communications Systems for Ultra-High Availability and Resilience

Satellite communications systems provide a means to connect people and devices in hard-to-reach locations. Traditional geostationary orbit (GEO) satellite systems and low Earth orbit (LEO) constellations, having their own strengths and weaknesses, have been used as separate systems serving different markets and customers. In this article, we analyze how satellite systems in different orbits could be integrated together and used as a multi-layer satellite system (MLSS) to improve communication services. The optimization concerns combining the strengths of different layers that include a larger coverage area as one moves up by each layer of altitude and a shorter delay as one moves down by each layer of altitude. We review the current literature and market estimates and use the information to provide a thorough assessment of the economic, regulatory, and technological enablers of the MLSS. We define the MLSS concept and the architecture and describe our testbed and the simulation tools used as a comprehensive engineering proof-of-concept. The validation results confirm that the MLSS approach can intelligently exploit the smaller jitter of GEO and shorter delay of LEO connections, and it can increase the availability and resilience of communication services. As a main conclusion, we can say that multi-layered networks and the integration of satellite and terrestrial segments seem very promising candidates for future 6G systems.

Industry 4.0 Enabling Technologies Contribution to the Sustainable Development Goals Achieving: A Content Analysis

The aim of the paper consists in the monitoring of Industry 4.0 enabling technologies (ET) adopting by the most innovative companies ranked by BCG classification, for Sustainable Development Goals (SDG) reaching. The development of Industry 4.0 ET has been considerably studied in the literature and its relationship to sustainability in its three pillars has been much investigated in recent years. The results show the three-years temporary dynamics of Industry 4.0 ET application in sustainability practices based on the communication process in the firms’ Sustainability Reports (SR) with the proven prevalence of IoT technology.

Improving care for patients with multiple long-term conditions admitted to hospital: challenges and potential solutions.

Increasing numbers of people live with multiple long-term conditions. These people are more likely to be admitted to hospital, experience adverse outcomes and receive poorer quality care than those with a single condition. Hospitals remain organised around a model of single-organ, disease-specific care which is not equipped to meet the needs of people living with multiple long-term conditions. This article considers these challenges and explores potential solutions. These include different service models to provide holistic, multidisciplinary inpatient and outpatient care across specialty boundaries, training a workforce to deliver high-quality hospital care for people living with multiple long-term conditions, and developing technological, financial and cultural enablers of change. Considerably more research is required to fully appreciate the shared risk factors, underlying mechanisms, patterns and consequences of multiple long-term conditions. This is essential to design and deliver better structures and processes of hospital care for people living with multiple long-term conditions.

Maximum likelihood localization of a network of moving agents from ranges, bearings and velocity measurements

Localization is a fundamental enabler technology for many applications, like vehicular networks, IoT, and even medicine. While Global Navigation Satellite Systems solutions offer great performance, they are unavailable in scenarios like indoor or underwater environments, and, for large networks, the instrumentation cost is prohibitive. We develop a localization algorithm from ranges and bearings, suitable for generic mobile networks. Our algorithm is built on a tight convex relaxation of the Maximum Likelihood position estimator. To serve positioning to mobile agents, a horizon-based version is developed accounting for velocity measurements at each agent. To solve the convex problem, a distributed gradient-based method is provided. This constitutes an advantage over centralized approaches, which usually exhibit high latency for large networks and present a single point of failure. Additionally, the algorithm estimates all required parameters and effectively becomes parameter-free. Our solution to the dynamic network localization problem is theoretically well-founded and still easy to understand. We obtain a parameter-free, outlier-robust and trajectory-agnostic algorithm, with nearly constant positioning error regardless of the trajectories of agents and anchors, achieving better or comparable performance to state-of-the-art methods, as our simulations show. Furthermore, the method is distributed, convex and does not require any particular anchor configuration.

Do Digital Technologies Enable Firms that Prioritize Sustainability Goals to Innovate? Empirical Evidence from Established UK Micro‐businesses

AbstractThis paper examines the importance of sustainability within firms’ strategic goals and its links with innovation in the context of micro‐businesses. Micro‐businesses provide an appropriate context for investigating this relationship because, while they tend to prioritize social and environmental goals, they are also more likely to confront resource constraints that can restrict their capability to innovate. Building on goal‐setting theory and the resource‐based view (RBV) of the firm, we explore under what conditions established micro‐businesses that prioritize sustainability goals are more likely to innovate. Using novel survey data on 4649 established micro‐businesses in the UK, we examine the enabling role of digital technologies. Our results suggest that owner‐managers who prioritize sustainability goals are significantly more likely to generate new product and process innovations. Moreover, we find that this effect is stronger when micro‐businesses adopt digital technologies. Digital technologies enhance the capabilities of micro‐businesses, strengthening the connection between sustainability goals and product and process innovation.

Enzyme-Assisted Circular Additive Manufacturing as an Enabling Technology for a Circular Bioeconomy—A Conceptual Review

Additive manufacturing (AM) is a decisive element in the sustainable transformation of technologies. And yet its inherent potential has not been fully utilized. In particular, the use of biological materials represents a comparatively new dimension that is still in the early stages of deployment. In order to be considered sustainable and contribute to the circular economy, various challenges need to be overcome. Here, the literature focusing on sustainable, circular approaches is reviewed. It appears that existing processes are not yet capable of being used as circular economy technologies as they are neither able to process residual and waste materials, nor are the produced products easily biodegradable. Enzymatic approaches, however, appear promising. Based on this, a novel concept called enzyme-assisted circular additive manufacturing was developed. Various process combinations using enzymes along the process chain, starting with the preparation of side streams, through the functionalization of biopolymers to the actual printing process and post-processing, are outlined. Future aspects are discussed, stressing the necessity for AM processes to minimize or avoid the use of chemicals such as solvents or binding agents, the need to save energy through lower process temperatures and thereby reduce CO2 consumption, and the necessity for complete biodegradability of the materials used.

Mobility-as-a-Service and unsustainable travel behaviour: Exploring the car ownership and public transport trip replacement side-effects of the MaaS paradigm

Car-centred development adds significantly to the climate change threat our planet faces. Mobility-as-a-Service (MaaS) is a concept looking to generate modal shift via the digital and physical integration of alternative on-demand transport services. Recent research raises concerns, however, that contrary to the hype, MaaS may result in unsustainable travel behaviour. On the one hand, future MaaS users that are now primarily drivers may not be ready to shift away from their cars, while, on the other hand, people regularly using public transport may substitute some of these journeys with MaaS-enabled car-sharing, ride-sharing and ride-hailing services. Herein, we study the effects of MaaS on intentions to own a car and to substitute public transport trips with car-centric services, via a UK-based quantitative survey. We use Principal Component Analysis and Ordinal Regression Modelling to see how MaaS-related perceptions referring to Added Value, Car Use Convenience and Enjoyment, Human Element Externalities, Trust in Functionality, Cost Incentives, Car Use Morality, Trust in Enabling Technology and Car Ownership Necessity affect usage intentions. Our results highlight some, typically less discussed, grey areas of MaaS and inform the design of policies, including car service disincentivitisation, responsible user benefits, MaaS rebranding and public transport investment prioritisation.

Synergy in Future Avionics: An Overview of Multiple Technologies for Small Air Traffic Segment in the COAST project

The paper describes research and development activities under Clean Sky 2 Cost optimized Avionic System (COAST) program. The main goal of this development was to deliver technology enablers at TRL 5 for affordable cockpit and avionics. The target segment for the technology enablers is aircraft with 1 to 19 passengers and small cargo aircraft belonging to CS-23 category. The main aim is to provide overall summer during the whole COAST program development per individual technology. Sections are divided per each technology with their results and overall contribution to the program. The Clean Sky 2 COAST program covered the development of following technologies: Cockpit Architecture SAT avionic system architecture, Flight Management Tactical Separation System (TSS), Advanced Weather Awareness System (AWAS), Flight Reconfiguration System (FRS), Navigation and Surveillance Dual Frequency Multi-Constellation GNSS Receiver (GNSS), Low-cost Integrated Navigation System (NAV), Affordable Integrated Surveillance System (SURV), Platform technologies Compact Computing Platform (CCP), High Integrity Electronics for health monitoring (HIE), Integrated Mission Management System Integrated Mission Management System (IMMS). These technologies were part of several flight test campaigns which took place in the Czech Republic with Evektor company using EV-55 aircraft.

Technology Enable Language Learning: Mediating Role of Collaborative Learning

Technology Enable Language Learning: Mediating Role of Collaborative Learning

The predictive robustness of organizational and technological enablers towards blockchain technology adoption and financial performance

PurposeBlockchain technology has brought about significant transformation among organizations worldwide. This study aimed to explore the effects of organizational and technological factors on blockchain technology adoption (BTA) and financial performance (FP) in Pakistan.Design/methodology/approachThis is a co-relational study which used the cross-sectional data. We gathered the data from the managers of Pakistan’s small and medium-sized enterprises (SMEs), which functioned their industries with blockchain technology. We applied convenience sampling to identify the respondents. Finally, we based this study’s findings on 274 valid cases.FindingsWe used structural equation modeling (SEM) in this study, to exert a positive and significant impact on organizational factors such as organizational innovativeness (OI), organizational learning capability (OLC), top management support (TMS) and organizational work climate (OWC) on BTA. In addition, the technological factors, such as complexity (CTY), technology readiness (TR), compatibility (CBTY) and technology capability (TC), have a positive and significant effect on BTA. Finally, this study’s findings show that BTA positively and significantly impacts FP.Practical implicationsThis study’s findings will help policymakers and planners to design policies to adopt other blockchain technologies to improve SMEs’ operations. Moreover, this study’s findings will inspire policymakers and planners to actively seek new ideas, knowledge and skills through acquiring new knowledge to assist with their IT-related decisions.Originality/valueThis study empirically confirms the role of organizational and technology factors toward BTA and FP among Pakistan's SME managers.

On the performance of power-sensing RIS-SM: Effects of improper Gaussian noise and Nakagami-m fading channel

The innovative idea of data transmission through a reconfigurable intelligent surface (RIS) is a promising and exciting solution to the ever-present problems in wireless communications, such as energy consumption and hardware cost. The soft-controlled dynamic shaping of the electro-magnetic waves, which enables utilizing the randomness of the propagation medium to achieve more efficacious wireless channels, makes RIS a key enabler of 6G technology. Lately, space modulation techniques (SMTs) have often been discussed within the realm of the RIS-aided technologies due to their unique transmission characteristics. However, RIS-SMTs require more generalized and in-depth investigations to fully understand their potential in future generations. Accordingly, in this study, a recently proposed RIS-based SMT is generalized to inherently increase the spectral efficiency by utilizing spatial modulation (SM) procedure instead of space shift keying (SSK). The novel system called power-sensing RIS-SM is analyzed in the presence of improper Gaussian noise (IGN) to discover system behavior in the case of being corrupted by an improper interfering signal over Nakagami-m channels, which adapt closely to the most of measured fading channels. The success of the proposed RIS-aided SMT is assessed in terms of the average bit error rate (ABER), which is both calculated by analytical derivations and verified by computer simulations.