Technical Architecture Research Articles

Predictive Health Monitoring of Palm Trees: Techniques and Applications for Enhanced Processing

This paper presents new framework for predictive health monitoring in palm trees using advanced deep learning methods. The system then selects the YOLOv8 method for the detection of the health of palm trees and further divides them into their real-time classification. Here, the model will, after training on its dataset, classify the palm tree as healthy, diseased, and stressed trees, keeping all the influential factors of the growth of the palm tree in consideration. It makes provision for the profiling of health status by way of early intervention, reducing risks and preventing diseases with a view to optimizing crop yields within palm plantations. The proposed model leverages state-of-the-art methodologies in object detection to process images of the palm tree with identification of key indicators of health issues. This approach has great implications for agricultural productivity in view of the maintenance of plant health through early detection. Further, the paper discusses challenges presented during the training and validation of the model, their strategies for overcoming such obstacles, and goes further into relating details to the technical architecture of the model. Further details on the works related to plant disease detection, image-based classification, and further applications of deep learning in agriculture have inspired the research work. Based on the obtained results, it can be observed that the proposed system provides a scalable and efficient solution for continuous monitoring and assessment of the health conditions of palm trees, hence enabling sustainable agricultural practices.

An enterprise technical architecture for the implementation of the South African National Health Insurance

AbstractThe South African National Health Insurance (NHI) faces challenges due to a lack of an enterprise technical architecture (ETA) solution, for the implementation. This study aims to propose an ETA, to enable and support the implementation of the South African ETA. The qualitative method was employed in the data collection. Actor‐network theory (ANT) was applied as a lens to examine the data. The findings reveal several critical influencing factors, including readiness assessment, geographical locations of stakeholders; diversity of healthcare facilities; flexibility of technology solutions; and synchronization of processes and patients' data. The study highlights the need to provide governance for the technologies that influence the implementation of NHI. Based on the influencing factors, a framework was developed. The framework is intended to provide architectural governance (principles, standards, and policies), to efficiently and effectively, facilitate, support, and enable the implementation of the South African NHI.

Federated machine learning in finance: A systematic review on technical architecture and financial applications

Abstract. With the advancement of technology, an increasing amount of data is stored online, including substantial amounts of personal information. Especially in the financial industry, where large sums of money are often involved, protecting personal privacy is crucial. Federated learning, as a privacy-preserving distributed machine learning method, offers a solution to these challenges by enabling data privacy while addressing the difficulties of data sharing in the financial sectorissues that frequently impede innovation, risk management, and fraud detection. This paper delves into the principles of federated learning algorithms, exploring their mechanisms in detail. Besides, applications and case studies in applications such as financial fraud detection, supply chain financing prediction, and other financial services are examined. Furthermore, sample dataset will be introduced. Moreover, the potential benefits and challenges of implementing federated learning within financial contexts are also assessed. Finally, promising research directions for the application of federated learning in the financial industry are outlined.

The platformisation of party politics?

Political parties have gone digital. Political scientists in countries around the world have diagnosed the rise of the digital party and traced parties’ adoption of digital technology. Existing attempts to understand parties’ digital practices have focused on the adoption of different tools, with scholars empirically studying and theorizing how and why digital technology is used. What has received less attention is the technical architecture and origins of these tools, questions that have been more directly examined by political communication scholarship. In this paper we entwine insights from these two disciplines, interrogating the idea of ‘platformization’ in the context of political technology. Presenting a unique, longitudinal dataset that captures the technological development of political party websites in 66 parties in 16 countries, we provide unprecedented insight into the evolution of party websites and show evidence of increasing platform dependency. Our findings have important implications for our understanding of parties’ relationship with technology, showing how technological developments and monopolies can lead to increasingly homogenized practice internationally.

The Role of Sentiment Analysis in Machine Translation- A Review on the Example of ChatGPT

In today’s globalization, machine translation technology has become an indispensable bridge for cross-lingual communication. The integration of sentiment analysis makes machine translation not only able to convey information, but also able to accurately express and understand the emotional color of the original text, which is of great significance in the fields of cross-cultural communication, customer service, and social media interaction. This study overviews the development of machine translation technology, from early rule-based models to modern statistical models to Transformer-based neural network models, with a special focus on the integrated application of ChatGPT in sentiment analysis and machine translation. First, this study introduces the background and research significance of machine translation, and discusses the role of sentiment analysis in improving translation quality and user satisfaction. Subsequently, the historical development of machine translation technology is reviewed in detail, and the basic concepts and methodologies of sentiment analysis and its applications in different fields are elaborated. On this basis, this study analyzes in depth the technical architecture, language model and interaction capability of ChatGPT, as well as its specific application and performance in sentiment analysis. Further, this study explores the importance of sentiment analysis in machine translation, including sentiment recognition, translation strategies for sentiment expression, and the impact of sentiment analysis on improving translation quality and cultural adaptability. Meanwhile, the advantages and limitations of ChatGPT in sentiment analysis are assessed, and future research directions are proposed, including technology convergence, construction of datasets and evaluation criteria, and ethical and bias issues. Finally, this study summarizes the practical application value of sentiment analysis in machine translation and looks forward to the potential areas of future research, aiming to provide reference and inspiration for the further development of machine translation and sentiment analysis.

The Application of Near Field Communication (NFC) in Public Transportation: Current Practices, Challenges, and Future Prospects

In the field of public transportation, the introduction of NFC technology can realize contactless payment and automatic ticket checking functions, significantly improving system efficiency and passenger experience. The article first reviews the development history of the public transportation system and the basic principles of NFC technology, and then analyzes the technical architecture and working principle of the NFC payment system. Through the cases of public transportation systems in many cities around the world, the practical application and effect of NFC technology are demonstrated. This article also verifies the transaction speed, stability and user satisfaction of NFC technology in the public transportation system through a series of experimental evaluations. The results show that NFC technology has excellent performance in terms of processing speed, system stability and user satisfaction, especially during peak hours, its advantages are more obvious. At the same time, the research also pointed out the limitations of current NFC technology applications and the challenges faced in practical applications. In the future, NFC technology will become more complete and is expected to provide passengers with a more personalized and intelligent service experience.

A socio-cognitive perspective of knowledge integration in digital innovation networks

Digital innovation is a complex process in which actors seek to create new value pathways by combining digital resources in a layered modular architecture. While IS scholarship has a rich tradition of research on developing and implementing digital artefacts within intra-organisational contexts, our understanding of knowledge integration across distributed innovation networks is nascent and under-theorised. This is an important area of research given the rising importance of digital innovation networks and the challenges faced in integrating specialised knowledge, especially given the greater diversity, speed, reach, and scope made possible by digital technologies. Drawing on in-depth case study findings from a health IoT project involving multiple organisations and disciplines, we explore how knowledge is integrated across boundaries during the initiation stage of a digital innovation network. Our findings point to boundaries related to the digital platform’s organising vision, resource allocation, delivery roadmap, technical architecture, and intellectual property, to name but a few challenges. We then reveal five socio-cognitive modes of knowledge integration which actors strategically enact to cross syntactic, semantic, and pragmatic boundaries: Signalling, Assembling, Contesting, Discounting, and Finalising. The choice of mode depends on the perceived knowledge status (‘what they know’) and social status (‘who they are’) of network actors, which highlight the salience of both social and cognitive dependencies for knowledge integration. We further discuss the contribution of design objects for overcoming differences and distinctions between specialist actors in a digital innovation network.

Towards the design of a smart warehouse management system for spare parts management in the oil and gas sector

IntroductionThe oil and gas production industry requires rapid changing. As oil and gas companies around the world are called upon to decarbonize, several sectors within the industry are attempting to find new ways of working to achieve decarbonization. One of those sectors is spare parts warehousing. During the past decades of oil and gas production, spare parts warehousing has not been prioritized in optimization measures. Warehouses have been filled with material, all activities have been performed manually, and financial expenditure has been high. Now, a large oil and gas production company in Norway is looking to optimize its spare parts warehousing to streamline its logistics activities and increase sustainability.MethodThis study addresses the optimization ambitions of the company and proposes key design elements of a smart warehouse management system using Industry 4.0 technology implementation. The study is conducted by performing a review of relevant literature and company ambitions, before embarking on a qualitative design measure to contribute to the company’s innovative success.ResultsThe study proposes optimization of the warehouse activities goods receipt, issuing of stocked goods, and inventory count. Additionally, the digital supply chain of tomorrow and the technical architecture of a track and trace system in the warehouse is suggested.DiscussionThe study’s results can be used in practical implications and provide a foundation for future research. Future research is suggested to include extensive visual simulations, practical implementation studies, and studies on long-term effects of implementation.

Promoting Sustainable Household Engagement in Recycling via Blockchain-Based Loyalty Program

Recycling plays a crucial role in impacting national GDP and environmental sustainability. Given the complexities inherent in recycling processes, technology serves as a driving force for advancing and optimizing these practices. In the Kingdom of Saudi Arabia, substantial initiatives are underway to foster a green environment and promote a circular economy. However, at the time of writing this paper, existing regulations mandate recycling primarily for business sectors, with no corresponding requirements for household waste collection or segregation. As a result, a significant portion of recyclable waste remains unprocessed. This paper expands upon earlier studies carried out in Jeddah, analyzing the obstacles and variables impacting sustainable recycling solutions, along with the essential conditions to boost household involvement in recycling. This study explores the potential of blockchain technology to improve household engagement by developing a blockchain-based loyalty program. The proposed system leverages the decentralized, immutable, and transparent features of blockchain technology to reward individuals with tokens for the recycling waste they produce, thereby facilitating token tracking across the recycling value chain and enhancing transparency in the circular economy. This article delves into the technical architecture of the loyalty program, aligning its domain model elements with blockchain design heuristics and integrating it with a mobile application that aims to boost recycling engagement by applying social economy principles. This innovative approach promises to overcome the current regulatory and motivational barriers, as well as promote sustainable recycling habits at the household level.

The Impact of the Issuance of e-CNY on the Business Strategy of Commercial Banks

This article comprehensively analyzes the issuance background, main features, technical architecture, and the impact on commercial banking operations and regulatory systems of China's Digital Currency Electronic Payment (DCEP or e-CNY). E-CNY is a legal digital currency that has the essential functions of money and a centralized two-tier operating system, making it compatible and stable with the current financial system. The article first outlines the main characteristics of e-CNY, reviews in detail the research and development process and pilot situations since 2014, and demonstrates its application progress in various scenarios. Furthermore, the article delves into the profound impact of e-CNY on commercial banks' deposits, loans, and international operations, suggesting that e-CNY may reduce the deposit base of commercial banks while providing Chinas small and medium-sized enterprises (SMEs) with a lower-cost financing channel, thereby promoting the development of the real economy. On the international front, promoting e-CNY is expected to enhance cross-border payments' efficiency and strengthen CNY's international competitiveness. Subsequent analysis of the practice of China Construction Bank (CCB) in the field of e-CNY showcases how commercial banks adapt to the era of digital currency. It also points out the need for further clarification and improvement of the regulatory framework to ensure the sustainable development of e-CNY. Finally, particular attention is given to the regulatory challenges e-CNY poses, especially regarding anonymity management, personal information protection, and delineating regulatory responsibilities.

A Survey of Joint Security-Safety for Function, Information and Human in Industry 5.0

Industry 5.0 blows the whistle on a new industrial revolution, aiming to refocus industrial development by reintegrating the human factor into the technological equation. On the eve of the revolution, the comprehensive surveys for Industry 5.0 would provide important support for future development. However, current surveys for Industry 5.0 are still in their infancy and some gaps remain. (i) Current work lacks a comprehensive technical architecture for Industry 5.0 and an in-depth analysis of the enabling technologies that will drive Industry 5.0; (ii) There is no comprehensive survey on security issues of Industry 5.0, which will directly hinder its development; (iii) As Industry 5.0 introduces people into the technological equation, then it will also further consider the broader human interests in its security equation. It is an open issue that traditional security classifications cannot summarize these new security threats in Industry 5.0. Therefore, this survey starts by reviewing the latest key enabling technologies and proposing an overall technology hierarchical structure for Industry 5.0. Second, we investigate the triad of security issues in Industry 5.0, which includes threats and countermeasures for functional safety, information security, and humanized security. Among them, we define the third security issue in Industry 5.0, humanized security, which includes safeguarding the broader interests and rights of individuals, machines, and society. Finally, we summarize future challenges and research trends. To the best of our knowledge, this is the first comprehensive overview of security in Industry 5.0, in which humanized security is defined for the first time.

Application and practice of industrial IoT cloud platform in oilfield intelligent transformation

Abstract Under the context of global energy transformation and low-carbon development, the traditional petroleum industry is facing a series of challenges such as technological innovation, market competition, environment protection, etc. Therefore, there is an urgent demand to realize green, safe, economical, and efficient development of oil and gas through oilfield intelligent transformation. This study develops a novel cloud platform covering the whole business based on the technical architecture of the industrial Internet of Things (IoT) for assisting the intelligent transformation of oilfields. Since the application of the IoT-based cloud platform in Qingcheng Oilfield, functions such as automatic collection of whole-domain data, remote monitoring, early warning, as well as intelligent analysis and decision-making have been realized. Furthermore, compared with the traditional platform, the new platform has improved eight indicators, such as data processing efficiency and sharing capacity, by more than 20%. Consequently, the developed IoT-based cloud platform can significantly improve the production and management level of the oilfield, and efficiently support oilfield intelligent transformation.

Application of Real-Time Data Service Technology in Smart oilfield

Abstract Real time data services play an important role in the construction of Smart oilfields, which can help oilfield production managers better understand the production situation and make more accurate decisions. Real time data services based on the Data Lake platform will bring more efficient and safer production methods to oil and gas fields, promoting the upgrading and sustainable development of the Smart oilfield industry. The technical architecture of Smart oilfield real-time data service mainly includes data lake platform, big data processing, edge computing and other core technologies. The data lake platform provides infrastructure, platform services and application services for Smart oilfield. Big data processing technology is responsible for rapid and accurate analysis of massive data. edge computing refers to computing at the data source to reduce data transmission and improve computing efficiency. The key technologies include data collection, transmission, storage, analysis, etc. Among them, data collection mainly uses sensors, PLCs and other equipment to collect production data. Data transmission uses technologies such as the Internet of Things and industrial Ethernet to transmit data to the data lake platform. Data storage adopts distributed storage technology to ensure the safety and reliability of data. Data analysis uses machine learning, deep learning and other technologies to analyze data, Provide decision support.

Construction and Practice of an Interactive Virtual English Learning Community on Campus Information Platforms

In the context of the information age, campus information platforms have gradually become essential tools for enhancing educational quality. This paper explores the construction and practice pathways of an interactive virtual English learning community based on a campus information platform, aiming to provide students with a more flexible and efficient English learning environment. By analyzing the current development of campus information platforms and interactive learning theories, this paper proposes the design principles and functional modules of the virtual learning community and elaborates on the technical architecture and practical construction pathways of the community. The research results indicate that the interactive virtual English learning community not only effectively enhances students' learning motivation and outcomes but also strongly supports the innovative practice of English education. In the future, with the development of artificial intelligence and big data technologies, virtual learning communities are expected to achieve greater breakthroughs in personalized learning recommendations and intelligent interaction.

Low-Cost IoT Air Quality Monitoring Station Using Cloud Platform and Blockchain Technology

Air pollution is a growing concern due to severe threats to public health and the environment. The need for reliable air quality monitoring solutions has never been more critical. This research paper introduces an innovative approach to addressing this challenge by deploying a low-cost Internet of Things (IoT) air monitoring station and providing a blockchain technology solution to enhance environmental data transparency, reliability, and accessibility. Our paper adopts a concept of merging IoT and blockchain technologies and collecting some parameters that help to assess air quality by using three sensors, DHT11, MQ7, and MQ135, to collect temperature, humidity, carbon monoxide, and carbon dioxide parameters, respectively, to measure the gases and thus indicate the air quality within the surrounding area. Collecting and sharing these types of valuable data will be very important for various stakeholders, such as governmental bodies, researchers, and the public. This approach is consistent with the principles of sustainable development, facilitating informed decision-making and promoting eco-friendly policies. This research explores the technical architecture of the IoT air monitoring stations, offering a promising solution for addressing air pollution concerns while promoting sustainable development goals. The proposed system is a model for leveraging emerging technologies to advance environmental monitoring and create smarter, livable cities. This approach aligns with the principles of sustainable development and eco-friendly initiatives. This research offers a promising model for enhancing environmental monitoring efforts and advancing the creation of smarter, more sustainable urban environments. The proposed IoT, cloud platform and blockchain-based system not only addresses pressing air pollution challenges but also sets a benchmark for leveraging emerging technologies in environmental science.

Using Hypotheses to Manage Technical Uncertainty and Architecture Evolution in a Software Start-up

Using Hypotheses to Manage Technical Uncertainty and Architecture Evolution in a Software Start-up

Creating and Evaluating School Exams with Marks Obtained

Abstract— This research paper explores the development of an educational management system leveraging modern web technologies such as React.js for frontend development, Node.js for backend implementation, and MongoDB for database management. The system comprises two main modules: exam creation and result display. The primary focus is on designing a user-friendly interface for teachers to create exams and for students to access their results. Additionally, a leaderboard feature is integrated to showcase students’ rankings based on their performance. This paper discusses the technical architecture, research objectives, and the significance of this system in enhancing educational administration. The module is developed using the MERN stack technology. The ultimate goal of this module is to make the educational system more efficient for both teachers and students. Keywords – Educational Management System, Modern Web Technologies, Exam Creation, Technical Architecture, MERN Stack.

The concept, technical architecture, applications and impacts of satellite internet: A systematic literature review

To conduct a comprehensive review of international publications, this study focuses on discussing the development status and future trends of Satellite Internet. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, all peer-reviewed publications in English from journals indexed with the SSCI and SCIE categories of the Web of Science are reviewed, with an emphasis on studies that focused only on the architecture, functions, technologies, and applications of Satellite Internet across the entire period. A total of 2085 records were identified, of which 69 met the inclusion criteria. Through a systematic literature review, the results show that three main research perspectives were summarised and a unified Satellite Internet definition and technical architecture were innovatively provided. Additionally, Satellite Internet application industries and scenarios were comprehensively sorted, and four types of potential impacts were categorised and discussed. This study provides an insightful analysis of recent trends in Satellite Internet research, which may provide guidance for planning and supporting the forthcoming wave of information infrastructure growth. Future research should broaden the scope of theoretical studies when assessing the strategic importance of Satellite Internet. Further quantitative research is needed to provide a more scientific and comprehensive perspective.

Research on the Innovative Practices of Tourism Platform in Web3.0 - Taking Ctrip Trekki NFT Project as an Example

Against the background of the rapid evolution of the current Web3.0 technology paradigm, blockchain technology is gradually penetrating into the core of the tourism industry, heralding a disruptive industry transformation. This paper focuses on the Trekki NFT project launched by Ctrip as a reference to explore in depth the innovative application of Web3.0 technology in tourism service platforms and the deep-rooted value it implies. This paper firstly elaborates the core concept and key technical architecture of Web3.0, as well as the theoretical connotation and practical boundaries of non-homogenized tokens (NFT). Through a panoramic analysis of the Trekki NFT project, the paper reveals how Web 3.0 technology can stimulate the restructuring of business models of travel platforms, optimize the quality of user experience, and explore new opportunities for industry growth. In particular, the study demonstrates the strategic significance of Web 3.0 technologies in promoting the innovative development and industrial upgrading of the tourism industry. The discussion section of the study has refined a set of strategic frameworks and action recommendations for the deep integration of tourism platforms and Web 3.0 technologies, aiming at guiding and accelerating the technology adoption and progress of the tourism industry in the wave of the digital economy in the future.

NiMo 4.0 – Enabling advanced data analytics with AI for environmental governance in the water domain

Abstract In the realm of environmental governance, civil servants confront a plethora of diverse datasets, including time series, geospatial vector data, and raster data. However, unlocking the transformative potential of Artificial Intelligence (AI) models to analyze this data poses the challenge of a widening technical proficiency gap in public administration. This paper explores the intersection of expanding environmental datasets and advanced analytics. Through a real-world project lens, our work aims to guide public administration entities, fostering seamless integration of AI-driven analytics and data-driven decision-making. We present a modular technical architecture that proposes pragmatic solutions that have the potential to empower civil servants. This approach contributes to accelerating environmental governance into an era of more informed and efficient, data-driven practices.