Convergence Of Technologies Research Articles

REVIEWING THE ROLE OF AI IN DRONE TECHNOLOGY AND APPLICATIONS

This comprehensive review delves into the transformative impact of artificial intelligence (AI) on drone technology, examining its pivotal role in revolutionizing various applications. As drones continue to evolve from recreational gadgets to indispensable tools across industries, the integration of AI enhances their capabilities, enabling advanced functionalities and expanding their potential use cases. The convergence of AI and drone technology has given rise to a myriad of applications, transforming industries ranging from agriculture to surveillance. Machine learning algorithms empower drones with autonomous navigation capabilities, allowing them to navigate complex environments and adapt to dynamic scenarios. Computer vision technologies enable drones to perceive and analyze visual information, facilitating tasks such as object recognition, tracking, and environmental monitoring. These advancements significantly contribute to enhanced aerial surveying, precision agriculture, and disaster response efforts. In the realm of precision agriculture, AI-equipped drones aid in crop monitoring, disease detection, and yield estimation, optimizing resource allocation and boosting agricultural productivity. Drones with AI-driven capabilities are increasingly employed in environmental monitoring, wildlife conservation, and disaster response, providing real-time data for efficient decision-making. Recent trends in AI-infused drone technology highlight its dynamic evolution. Edge computing solutions empower drones to process data locally, reducing latency and enhancing real-time responsiveness. Reinforcement learning algorithms enable drones to learn from their experiences, adapting and optimizing their performance over time. Swarm intelligence, an emerging field in drone technology, leverages AI to enable coordinated and synchronized actions among multiple drones, expanding their capabilities for collaborative tasks. In conclusion, this review sheds light on the pivotal role of AI in transforming drone technology and expanding its applications. The synergy between AI and drones has unlocked new possibilities across various industries, ranging from agriculture to disaster response. As technology continues to advance, the collaborative integration of AI and drones promises to redefine the future of aerial technology, introducing unprecedented efficiencies and capabilities across diverse sectors.
 Keywords: Role, AI, Drone, Applications, Technology.

Using Ensemble Learning for Anomaly Detection in Cyber–Physical Systems

The swift embrace of Industry 4.0 paradigms has led to the growing convergence of Information Technology (IT) networks and Operational Technology (OT) networks. Traditionally isolated on air-gapped and fully trusted networks, OT networks are now becoming more interconnected with IT networks due to the advancement and applications of IoT. This expanded attack surface has led to vulnerabilities in Cyber–Physical Systems (CPSs), resulting in increasingly frequent compromises with substantial economic and life safety repercussions. The existing methods for the anomaly detection of security threats typically use simple threshold-based strategies or apply Machine Learning (ML) algorithms to historical data for the prediction of future anomalies. However, due to the high levels of heterogeneity across different CPS environments, minimizing the opportunities for transfer learning, and the scarcity of real-world data for training, the existing ML-based anomaly detection techniques suffer from a poor predictive performance. This paper introduces a hybrid anomaly detection approach designed to identify threats to CPSs by combining the signature-based anomaly detection typically utilized in IT networks, the threshold-based anomaly detection typically utilized in OT networks, and behavioural-based anomaly detection using Ensemble Learning (EL), which leverages the strengths of multiple ML algorithms against the same dataset to increase the accuracy. Multiple public research datasets were used to validate the proposed approach, with the hybrid methodology employing a divide-and-conquer strategy to offload the detection of certain cyber threats to computationally inexpensive signature-based and threshold-based methods using domain knowledge to minimize the size of the behavioural-based data needed for ML model training, thus achieving a higher accuracy over a reduced timeframe. The experimental results showed accuracy improvements of 4–7% over those of the conventional ML classifiers in performing anomaly detection across multiple datasets, which is particularly important to the operators of CPS environments due to the high financial and life safety costs associated with interruptions to system availability.

How do technology convergence and expansibility affect information technology diffusion? Evidence from the internet of things technology in China

Information technology diffusion (ITD) is essential for promoting the sustainable development of technologies and helping technology owners gain a competitive advantage. The web-based development of technology and the digital transformation needs of multidisciplinary markets simultaneously drive the increasing convergence and expansibility of information technology (IT). However, whether these two technological characteristics can contribute to the diffusion of early-stage IT and how they influence the further diffusion of IT that has already diffused on a large scale are yet to be thoroughly investigated. We argue that the impact of technology convergence on ITD is heterogeneous when distinguishing between low- and high-ITD scenarios, as is technology expansibility. Our quantile regression estimates use a dataset about Internet of Things (IoT) patents authorized by the Chinese Patent Office from 2009 to 2019. The results show that increased technology convergence benefits ITD in high-ITD scenarios but does not affect ITD in low-ITD scenarios. Technology expansibility negatively impacts ITD in high-ITD scenarios and positively impacts ITD in low-ITD scenarios. This study broadens the theoretical paradigm of “technological characteristics and ITD” from the domain perspective. It inspires information technology owners to formulate sustainable strategies related to ITD according to technology convergence and expansibility.

Hybrid disease prediction approach leveraging digital twin and metaverse technologies for health consumer

Emerging from the convergence of digital twin technology and the metaverse, consumer health (MCH) is witnessing a transformative shift. The amalgamation of bioinformatics with healthcare Big Data has ushered in a new era of disease prediction models that harness comprehensive medical data, enabling the anticipation of illnesses even before the onset of symptoms. In this model, deep neural networks stand out because they improve accuracy remarkably by increasing network depth and making weight changes using gradient descent. Nonetheless, traditional methods face their own set of challenges, including the issues of gradient instability and slow training. In this case, the Broad Learning System (BLS) stands out as a good alternative. It gets around the problems with gradient descent and lets you quickly rebuild a model through incremental learning. One problem with BLS is that it has trouble extracting complex features from complex medical data. This makes it less useful in a wide range of healthcare situations. In response to these challenges, we introduce DAE-BLS, a novel hybrid model that marries Denoising AutoEncoder (DAE) noise reduction with the efficiency of BLS. This hybrid approach excels in robust feature extraction, particularly within the intricate and multifaceted world of medical data. Validation using diverse datasets yields impressive results, with accuracies reaching as high as 98.50%. DAE-BLS’s ability to rapidly adapt through incremental learning holds great promise for accurate and agile disease prediction, especially within the complex and dynamic healthcare scenarios of today.

Analysis of the Current Status of Sensors and HBIM Integration: A Review Based on Bibliometric Analysis

This article presents a bibliometric analysis conducted on the implementation of sensor-extracted data in the context of Historical Building Information Modeling (HBIM) with a focus on the conservation of heritage buildings. The study utilized recognized databases, namely, Web of Science (WoS) and Scopus. A bibliometric analysis methodology was applied, employing the VOSviewer 1.6.19 software. The results obtained provide a robust overview of the current state and trends in HBIM and sensor research and enabled the identification of emerging trends in the field of preventive conservation. Three promising trends were identified, establishing connections between this field and 4D spatial data management, energy performance, and artificial intelligence. Additionally, relations with climate change were also detected. These trends underscore a significant convergence of technologies and methodologies in the realm of heritage building conservation. The conclusions serve as a valuable contribution to guiding future research in the field of built heritage conservation.

Knowledge spectrum explored: Understanding source-recipient interactions and their influence on technology convergence

In a rapidly evolving technological landscape, firms are strategically diversifying into multiple tech sectors, blurring traditional industry lines through ‘industry convergence’. To comprehend the inception of technology convergence from the roots of knowledge, this study bridges knowledge flow framework with the dynamic capabilities theory, considering the dual roles of firms in knowledge flow and whether they engage in pioneering or follower-type technological innovations. Through this integrated approach, this study classifies technology convergence into four distinct patterns. An analysis of USPTO data spanning 1976–2019 underscores that as knowledge matures, its application in convergence processes intensifies. Pioneers exhibit faster knowledge advancement and maintain focused partnerships, whereas followers diversify across disciplines and pursue extensive collaborations. These results highlight the strategic importance for firms to coordinate their knowledge-based attributes with their technological progression pace. Firms should strategically harmonize their innovation approaches with their market stance to fully leverage the advantages of technology convergence.

Developing a supervised learning model for anticipating potential technology convergence between technology topics

Recognized as essential for firms, a systematic methodology for identifying potential technology convergence opportunities has been the focus of many studies attempting to predict the emergence of new convergences between technology classes. However, because technology classes cover a fairly broad range of technology properties, the practical implications of the identified opportunities are not clearly articulated. Motivated to address this problem, this study develops supervised learning models to predict potential technology convergence between semantically coherent technology topics using cluster likelihood, link possibility, and technological similarity as input features. Patent data is utilized to generate technology topics and explore technology convergence between them, and a case analysis on wearables is conducted. Wearables, at the forefront of innovation, offer a dynamic environment converging disciplines like electronics and health sciences, making them an ideal subject for validating the proposed approach practically. The case analysis leads to the development of six individual models and one voting classifier that ensembles them together. The models perform favorably based on traditional metrics and indicate feasible and rational opportunities across various technologies, affirming the validity of our approach. This study's primary contribution lies in enhancing firms' R&D planning capabilities, enabling them to seize opportunities within specific technology topics.

The Nexus: Augmented Thinking for a Complex World—The New Convergence of Art, Technology and Science

The Nexus: Augmented Thinking for a Complex World—The New Convergence of Art, Technology and Science

Complex Systems in Interdisciplinary Interaction

Complex systems consist of many components that interact with each other, and nonlinearity is fundamental in the dynamics that arise as a result of the interaction of these components and cannot be studied by observing only a small part of the system. A large number of them make fluctuations an integral part of their dynamics. Through interdisciplinary research, we integrate different disciplines and methodological approaches. We study complexity from different angles through topics that include neuroscience, artificial intelligence, and quantum physics. We have sought to explore these topics that have gained progressive interest in scientific circles as well as outside academic circles, influencing many areas outside academic research. Two goals connect our research. First, theoretical insights from neuroscience, artificial intelligence and quantum physics of the financial stock market. “Financial stock markets are sophisticated machines intertwined with scientific networks” (Ana Negovanović, 2024). They are the core of a system of different blocks that interact on the financial market in an interdisciplinary interaction of the most complex structures, neural networks with interconnected nodes. Second, new technologies- convergence of technologies, new industries, space industry through chaos theory. Investigating the attributes of complex systems is structure. Systems are structured in such a way that some parts of the system are specialized, and systems can naturally be divided into different levels of organization, which should be modeled at different levels of detail. An important component of systems understanding is the ability to break down a system model into its component parts and levels to see how the parts behave and how to connect the parts and levels to understand the overall dynamics and structure of the system. Perhaps one of the most transparent examples of the importance of structure in thinking about complex systems is the space program, where one must equally consider the behavior of individual components and the dynamics of how those components interact with each other.

Redefining Architecture Through Posthuman Principles: Bridging Cybernetic Concepts and XR Technologies

The integration of cybernetic principles into architectural discourse has led to a profound transformation in the conceptualization of architectural entities. Cybernetics redefines architecture as a dynamic and responsive entity, capable of communication, interaction, and adaptation. This paradigm shift is exemplified by the Fun Palace project, which envisioned architecture as a living organism dynamically responding to its environment. Marcos Novak's concept of liquid architecture further elucidates this transformative paradigm, emphasizing architecture's fluid adaptability in digital realms. Realizing these transformative qualities requires architecture's integration into digital space. Extended Reality (XR) technologies serve as a conduit for this integration, enabling architects to transcend traditional limitations and reshape spatial environments. Through a rigorous inquiry into the convergence of cybernetic principles and XR technologies, this research redefines architecture in the digital age. Two workshops serve as case studies, demonstrating the transformative potential of this symbiotic relationship. In conclusion, this research sheds light on the symbiotic relationship between cybernetic principles, XR technologies, and architectural design, offering insights into transformative possibilities. By redefining architecture in the digital age, this study paves the way for a new era of architectural innovation, where creativity transcends boundaries, and the built environment becomes a dynamic expression of human imagination.

EU, 미국, 중국시장에서 한국 신재생에너지 산업의 품목별 수출 품질경쟁력과 시장점유율 변화 요인 분석

This study applied product and market segment analysis (PMSA) and intra-industry trade (IIT) indices to capture the quality and price competitiveness and high- and low-quality IIT of new renewable energy (NRE) items in Korea’s trade with major economic powers (i.e., European Union [EU], United States, and China) for the period 2012-2022. Additionally, this study used the constant market share (CMS) technique to divide the causes of fluctuations in Korea's market share in large economies’ import markets into demand side, supply side, and adaptation side. The empirical results can be summarized in the following three points. First, PMSA of quality and price competitiveness confirmed Korea’s weakness in securing price and quality competitiveness in trade with the EU and the United States and Korea’s inability to secure price competitiveness in trade with China. Additionally, analysis of high- and low quality IIT showed that in trade with the EU, low-quality vertical IIT and horizontal IIT were mixed, whereas in trade with the United States and China, the majority of items showed low-quality vertical IIT and high-quality vertical IIT patterns, respectively. More importantly, the CMS results by item in the NRE industry based on the 2017/2022 period showed that in the EU and US import markets, supply factors caused most of the market share changes for the majority of items, and in the Chinese import market, the main causes were a mixture of supply and demand factors. In conclusion, policy and institutional support for research and development of independent and convergence technologies are needed to strengthen the NRE industry’s quality competitiveness, and market expansion of the NRE industry can be accomplished by expanding direct investment in the United States and the EU, as well as through government financial support.

Digital methods in architectural and environmental renovation of buildings for a public function

This article explores advanced digital methods for comprehensive renovation of industrial buildings into public spaces. Four different approaches are described in detail: 1. Digital mapping and modeling: allows accurate spatial analysis to be performed for optimizing design solutions before physical renovation; combines virtual and augmented reality to create an immersive experience. 2. Integration of augmented and virtual reality: facilitates joint decision-making by visualizing proposed projects and thus increasing public engagement. Historical and cultural narratives are overlapped, strengthening the connection between the past and the present. 3. Smart building systems: include IoT devices and sensors to optimize energy efficiency, comfort, and overall functionality; solve unique challenges related to the conversion of industrial buildings. 4. Digital twin technology: creates a dynamic virtual copy for continuous real-time monitoring; uses machine learning for predictive analysis, increasing operational efficiency and sustainability. The convergence of technologies and architectural innovations presents a transformative force in the context of architectural and environmental renovation of industrial buildings, representing a change of the paradigm in the renovation of industrial facilities for re-use as a public function.

Scope extension of the metaverse tourism concept: Proposing a research agenda

Given the growing significance of the metaverse in research, it is crucial to understand its scope, relevance in the tourism industry, and the human-computer interaction it involves. The emerging field of metaverse tourism has a noticeable research gap, limiting a comprehensive understanding of the concept. This article addresses this gap by conducting a hybrid systematic review, including a variable-oriented literature review, to assess the extent and scope of metaverse tourism. A scrutiny on Scopus identified a reduced number of relevant documents. The analysis exposes theoretical and empirical gaps, along with promising opportunities in the metaverse and tourism intersection. These insights contribute to shaping a contemporary research agenda, emphasizing metaverse tourism. While this study offers an overview of current research in metaverse tourism, it is essential to recognize that this field is still in its early stages, marked by the convergence of technology and transformations in tourism. This exploration underscores the challenges and opportunities arising from the evolving narrative of metaverse tourism.

Design of prehospital spectral CT with a rotation-free rectangular gantry and deep learning reconstruction

Treatment of stroke depends on a narrow therapeutic time window and requires urgent intervention to be emergently pursued. Despite recent “fast” initiatives that have underscored “time is brain,” many patients still fail to present within the narrow time window to receive maximum treatment benefit from advanced stroke therapies. The convergence of emergency medical services, telemedicine, and mobile technology, including transportable computed tomography scanners, has presented a unique opportunity to advance patient stroke care in the prehospital field by shortening the time to hyperacute stroke treatment with a mobile stroke unit. However, in order to facilitate the integration of computed tomography (CT) scanners into small ambulances, their geometry should be streamlined and made compact. Additionally, it is imperative that radiation exposure from prehospital CT scans comply with established radiation protection guidelines to safeguard both patients and healthcare workers. In this study, we propose a newly designed CT system for a rotation-free rectangular gantry with a photon-counting detector (PCD) and a deep-learning reconstruction approach for undersampled projections. Undersampled projections obtained using the designed CT system were implemented using a deep learning method. The deep learning approach showed superior image quality without distortion compared to state-of-the-art reconstruction methods. Finally, we implemented imaging of brain microhemorrhages using low- and high-energy images obtained from the PCD. Our results indicate that the proposed scanner effectively shows potential for acute stroke detection in prehospital ambulances. Its effectiveness was validated by comparing its image performance with those of other methods such as FBP and compressed sensing.

The Impact of Fintech on Traditional Financial Banking in West Africa

Fintech, the convergence of finance and technology, has emerged as a transformative force reshaping the global financial landscape. While its influence is evident across the world, its impact on traditional financial systems in less developed countries remains a subject of exploration and analysis. This paper aims to investigate the multifaceted effects of fintech on traditional financial systems in less developed countries, examining both the opportunities and challenges it presents. Through an examination of various case studies and empirical evidence, this paper seeks to provide insights into the evolving dynamics of financial inclusion, innovation, regulation, and economic growth spurred by fintech in less developed countries.

A Bibliometric Analysis of the Challenges and Opportunities of Fintech in Promoting Access to Sharia Finance

The convergence of financial technology (fintech) and Sharia finance has garnered significant attention in recent years, promising enhanced accessibility and inclusivity in Islamic financial practices. This bibliometric analysis delves into the challenges and opportunities presented by fintech in promoting access to Sharia finance. Spanning from 2017 to 2024, the analysis encompasses 991 papers, revealing a high level of collaboration and a diverse thematic landscape. Key findings highlight the centrality of regulatory frameworks, regional dynamics, and the compatibility of fintech innovations with Sharia principles. Emerging trends, such as the exploration of innovative lending practices and regulatory oversight, underscore the evolving nature of research in this domain. The insights derived from this analysis provide valuable guidance for stakeholders invested in advancing Islamic finance and fintech innovation.

Cybernetic governance: implications of technology convergence on governance convergence

Governance theory in political science and international relations has to adapt to the onset of an increasingly digital society. However, until now, technological advancements and the increasing convergence of technologies outpace regulatory efforts and frustrate any efforts to apply ethical and legal frameworks to these domains. This is due to the convergence of multiple, sometimes incompatible governance frameworks that accompany the integration of technologies on different platforms. This theoretical claim will be illustrated by examples such as the integration of technologies on the “human platform” as it is referred to in the case of enhanced soldiers. Hence, successful governance might require new approaches borrowed from a distant relative, namely cybernetics. Insights gained from cybernetics for governance theories might be able to give guidance for a more efficient and adaptive governance approach that is able to deal with increasing complexity caused by technology and governance convergence. While cybernetics itself might be considered a governance approach, it has had surprisingly little reception in the wider field of governance within the area of social and political sciences. This article will develop cybernetic governance as a set of expandable governance principles that are applicable to an increasingly complex digital and smart society. It thereby tries to further galvanise what could be termed cybernetic governance theory as a subject of worthwhile insights from the combination of otherwise largely the disjoined fields of cybernetics and governance.

Emerging Perspectives on the Application of Recommender Systems in Smart Cities

Smart cities represent the convergence of information and communication technologies (ICT) with urban management to improve the quality of life of city dwellers. In this context, recommender systems, tools that offer personalised suggestions to city dwellers, have emerged as key contributors to this convergence. Their successful application in various areas of city life and their ability to process massive amounts of data generated in urban environments has expedited their status as a crucial technology in the evolution of city planning. Our methodology included reviewing the Web of Science database, resulting in 130 articles that, filtered for relevancy, were reduced to 86. The first stage consisted of carrying out a bibliometric analysis with the objective of analysing structural aspects with the SciMAT tool. Secondly, a systematic literature review was undertaken using the PRISMA 2020 statement. The results illustrated the different processes by which recommendations are filtered in areas such as tourism, health, mobility, and transport. This research is seen as a significant breakthrough that can drive the evolution and efficiency of smart cities, establishing a solid framework for future research in this dynamic field.

Technological convergence for ethernet networks in railways process control systems

The tests carried out in the proposed implementation of an Ethernet network for railway signalling indicate that the topology in sections, with rings interconnected by optical fibre, offers an efficient solution in terms of throughput, latency and availability. Although a challenge was identified in the convergence time in Layer 3, exceeding one second, this is considered a calculated risk due to its occurrence being restricted to specific points in the network and the robustness of the equipment with high MTBF. The positive results in the bandwidth, latency and no frame loss tests in different scenarios reinforce the viability of the proposal to meet the demands of railway signalling. Careful implementation of the suggested topology, combined with redundancy strategies and proactive maintenance, emerges as a promising solution to meet the emerging challenges in railway traffic control automation, providing safety and operational efficiency. Continuous monitoring and preventive maintenance are key to ensuring the system's lasting and reliable performance.

Peminat Radio dan Podcast Kalangan Generasi Z Saat Berkendara

This research explores the change in interest in listening to Radio rather than Podcasts and assesses what factors support the change in interest in listening. The research was conducted to understand how technological developments such as digital audio platforms, and the integration of social media platforms affect the distribution of audio content such as podcasts. The researchers analyzed how these platforms affect audience, user engagement and monetization of audio content. Explored consumer behavior, listening habits, and audience preferences especially within Generation Z in relation to radio and podcasts. Researchers studied how factors such as content type, delivery style, and speed of access influence interest in listening to podcasts and online radio stations. Explore the extent to which the availability of digital audio content such as podcasts and online radio affects listener satisfaction. Researchers studied the factors that influence content selection, suitability to audience interests and listeners' response to the content presented. The trend of commodities with different purposes coming together to produce a single, multipurpose good or service is known as technological convergence, and it is a growing phenomenon that is changing the commercial landscape. Recent technological advancements have come to the attention of all human beings. The pursuit of convergence is accelerating market transformation and the creation of innovative products and services for increasingly perceptive and discerning customers. It is from this Media Convergence that research was conducted to investigate the impact of recent technologies such as on-demand audio, streaming platforms, and podcast monetization on the radio and podcast industry as a whole.