Communication Technologies Research Articles

The communicative and educational aspect in the constructive transformation of the educational activities of the university

Introduction. The article reveals the role of the communicative and organizational aspect for the digital transformation of the educational activities of a university.Purpose setting. Digital transformation is understood as the systemic integration of digital tools, information and communication technologies for the purpose of collecting, processing, transforming and analyzing data to improve the efficiency of human activity. The relevance of the study of the digital transformation of the educational activities of a university is emphasized, since it is universities that are called upon to ensure the necessary increase in personnel with digital competencies for the development of the digital economy.Methodology and methods of the study. As a result of a specially prepared, author's questionnaire and the use of a survey method, we identified the essence of the communicative and educational structure.Results. The article discusses domestic and foreign research in the field of educational processes. A model of a new digital service is described, the use of which increases the efficiency of communication at a university and ensures improved quality of education, in the context of digitalization of its system-forming component.Conclusion. A solution to the problem of low efficiency of communication between subjects of educational activity at a university is proposed through the creation of digital services and a new six-component model of educational activity that supports its digital transformation.

Clean energy transition in rural Bangladesh: Challenges in adoption and impact

ABSTRACT At the household level, the solar photovoltaic (PV) system is an off-grid clean energy source with significant poverty reduction potential, thereby contributing to the attainment of several sustainable development goals. Nevertheless, there has been limited adoption of renewable or clean energy technologies in Bangladesh. At present, renewable energy sources account for only 3% of the country’s electricity generation. This study thus investigates the drivers of solar PV adoption and the impact of this on household income and poverty in Bangladesh. We present an econometric analysis of data from the International Food Policy Research Institute’s Bangladesh Integrated Household Survey, 2020. Our findings indicate that only 5.51% of the sample households adopted solar PV, with the likelihood of adoption 3.8% higher in households with a mobile phone, 1.7% higher in households with internet access, and 2.8% higher among homeowners. However, the government’s programs to expand the electricity grid made the delivery of solar PV by partner organizations less competitive. Our analysis reveals that the adoption of solar PV has a positive effect on household income of between 9.31% and 13.50%. The poverty gap is likely to decrease by around 20% to 26% due to adoption. These findings are pertinent to ongoing policy development efforts targeted at increasing the adoption of renewable energy to meet the sustainable development goals. Solar PV information could be potentially disseminated through mass media and modern communication technologies that require internet access. Furthermore, increasing the installation of solar PV systems in rented houses may promote the adoption of solar PV. It is imperative to implement policies that provide incentives for the installation and utilization of solar PV.

Jamming Attacks Detection Based on IGWO for Optimization of Fast Correlation-Based Feature extraction in Wireless Communication

Background: Wireless networks are essential communication technologies that prevent cable installation prices and burdens. Because of this technology's pervasive usage, wireless network safety is a significant problem. Owing to distributed and open wireless medium aspects, attackers might use different jamming methods to exploit physical and MAC layer protocol vulnerabilities. In addition, jamming attacks require to be accurately grouped so that suitable countermeasures can be considered. Given the potential severity of such attacks, precisely identifying and classifying them is critical for implementing effective responses. The motivation for this paper is the need to improve the detection and categorization of jamming signals using modern machine learning algorithms, consequently enhancing wireless network security and reliability. Objective: In this paper, we compare some machine learning models' efficiency for diagnosing jamming signals. Methods: Such algorithms refer to support vector machine (SVM) and k-nearest neighbors (KNN). We checked the signal features that recognize jamming signals. After the jamming attack model, the developed grey wolf optimizer version known as IGWO (improved grey wolf optimizer) has been discussed for feature extraction of software usability. Four separate metrics were employed as features to detect jamming attacks in order to evaluate the machine learning models. This novel feature extraction method is crucial for improving the accuracy of jamming detection. Results: The measurements of these parameters were gathered through a simulation of a real setting. And generated a large dataset using these parameters. Conclusion: The simulation results illustrate that the KNN algorithm based on jamming detection could diagnose jammers having a minimal likelihood of false alarms and a high level of accuracy.

Use of mobile communication technology to overcome vaccine skepticism

Despite significant advances in clinical medicine, infectious diseases and their prevention remain the leading problem of our time. Low literacy of the population reggarding immunization, combined with high activity of the anti-vaccination movement, creates unhealthy skepticism about immunoprophylaxis and the risks of epidemics. The work uses theoretical analysis of literature, methods of anonymous questionnaires of students of medical and non-medical specialties, methods of statistical and bioinformatics data processing, and modern internet technologies: the platform of the social network “Vkontakte” and the program for creating a chatbot “Senler”. The analysis of commitment to vaccination of medical and non-medical students showed that 65.8% to 96.2% of respondents have a positive attitude to preventive health measures. From 1.9% to 6% believe the disease is easier to treat than to prevent, and almost 30% of respondents do not think about prevention and diseases in general, considering themselves young. Almost 10% of non-medical students (1 group) consider vaccination useless, 8.4% dangerous for immunity, 18.3% know nothing about vaccinations and cannot compare the benefits of vaccination with the risk of infectious pathology. In order to form medical literacy of the population, including in strategic issues of preserving the health of the nation, the team of authors developed and implemented through the social network “Vkontakte” chatbot “Vaccine and point” containing up-to-date information about vaccines, methods multiplicity and age features of their use. People [n = 156] used the chatbot during the month of work, noting its high informational value, motivating to vaccination. Analysis of commitment to vaccination of students of medical and non-medical specialties showed an insufficient level of trust in domestic preventive medicine, which forms an unhealthy attitude to vaccine prevention. Insufficient vaccine coverage creates real threats to the spread of infectious diseases at the population level. Developed and implemented in real practice, the “Vaccine and point” chatbot is an effective tool for increasing the knowledge of compatriots about the real possibilities of protection against the main vaccine-controlled infections and an additional attempt to overcome anti-vaccination skepticism.

Advances in deep learning-based intelligent receivers

Abstract. This paper presents a summary of the progress of deep learning in the research of intelligent receivers and predicts its future development direction. First, the background of the era of intelligent receivers is introduced. With the rapid development of communication technology, intelligent receivers show insufficient flexibility, low accuracy, and spectral efficiency in detecting current radio signals. This is a challenge that is difficult to overcome in order to meet the needs of modern signal recovery. With the advent of artificial intelligence technologies such as deep learning, academia and industry began to explore the potential of applying these techniques to the field of communication receivers, leading to the emergence of intelligent receivers. This paper then introduces the fundamentals of wireless communication systems and deep learning neural networks, laying the groundwork for a deeper understanding of the subsequent content. Chapter 3 provides a comprehensive overview of the application of intelligent receivers in signal reception, including channel estimation, signal detection, modulation identification, demodulation and decoding. Finally, the paper considers the practical applications of intelligent receivers and speculates on their future development.

The impact of information and communication technologies on export diversification: Evidence from developing countries

As economies increasingly rely on digitalization, information and communication technologies (ICT) have become critical in shaping global economic transformations. This study explores the impact of ICT on export concentration and diversification in emerging markets and developing countries. Using a panel data set of 110 countries from 2000 to 2019, the Generalized Method of Moments (GMM) estimator has been employed to assess the short- and long-term effects of ICT on these economies. To summarize information on various ICT channels, an ICT index has been constructed through principal component analysis (PCA). Additionally, the study examines the combined influence of ICT and human capital on export concentration. Findings indicate that ICT development significantly accelerates export diversification in developing countries, aligning their export structures with global standards. The interaction between ICT and human capital positively impacts export concentration, suggesting that higher levels of human capital enhance ICT's effects. Overall, ICT not only boosts human capital but also equips developing countries with the skills needed to enter new markets, develop high-value products, and compete globally. Consequently, governments in developing countries should prioritize investments in ICT infrastructure to lower trade costs, diversify exports, and promote sustainable economic growth.

Analysis of intangible assets reporting standards and automation in KSA within an Islamic context – a case study

Purpose This paper aims to the significance of intangible assets in boosting financial credibility and accounting transparency in Saudi Arabia and other Islamic countries, aligning with Saudi Vision 2030. Moreover, it articulates the indispensable role of information and communication technology (ICT), including cutting-edge technologies such as artificial intelligence (AI) and blockchain, inefficaciously mitigating manual challenges while safeguarding the authenticity and reliability of financial information. Design/methodology/approach This study examines relevant literature on national and international standards to define the significance of intangible assets within conventional and Islamic Shari’ah principles in the Kingdom of Saudi Arabia (KSA). It delves into how automation technologies can improve accuracy and verifiability in reporting intangible assets while adhering to Islamic Shari’ah Compliance (ISC) principles, providing valuable insights into standardization and automation benefits. Findings The study highlights that ISC laws affect intangible asset reporting. Integrating conventional accounting principles with ISC is necessary to establish a unified international standard. Adopting ICT, AI and blockchain is crucial for automating and ensuring consistent, verifiable reporting of intangible assets. Research limitations/implications This case study highlights the importance of intangible assets in KSA, but its findings require validation through workshops with scholars, stakeholders and policymakers to ensure broader acceptance and applicability beyond the specific context. Practical implications This study provides guidance on using AI, blockchain and other ICT tools to ensure accurate financial reporting by validating and verifying intangible assets, benefiting stakeholders, policymakers, accountants, auditors and ISC professionals. Originality/value This study underscores the importance of reporting intangible assets according to Islamic principles in KSA, with relevance to other Islamic countries. Promoting International Financial Reporting Standards and Saudi Organization for Certified Public Accountants standards enhances accurate reporting and supports Saudi Vision 2030 goal of boosting global investment and trade.

Leveraging Trauma Informed Care for Digital Health Intervention Development in Opioid Use Disorder.

Digital health refers to the use of information and communication technologies in medicine (including smartphone apps, wearables, other non-invasive sensors, informatics and telehealth platforms) to prevent illness, deliver treatment, and promote wellness. This rapidly proliferating group of technologies has the potential to reduce harm for people with opioid use disorder (OUD) and facilitate the recovery process; however, development in this space for OUD has been slower compared to that for other medical conditions. Unique issues with OUD management surrounding patient provider relationships, interaction with the healthcare system, autonomy and trust sometimes hinder care approaches, including those in digital health. The trauma informed care framework (TIC), developed for use by organizations to support individuals who have experienced trauma, has particular applicability for digital health interventions in OUD care. This manuscript will serve as a review of TIC principles and how they can be applied to digital health interventions to increase access, equity, and empowerment for people with OUD. We will highlight representative current and pipeline digital technologies for OUD, challenges with these technologies, TIC models for OUD, and the integration of TIC principles into digital technology development to better serve people with OUD. Finally, we will posit strategies to incorporate the aforementioned principles into future research efforts. We ultimately aim to use TIC as a lens through which to develop digital technologies to help individuals with OUD while minimizing harm.

Perspectives on drone journalism in Turkiye: Journalists' views on the use of drones

The subject of this study is the role of drone journalism as a new field within journalism. Drone journalism has emerged due to the rapid development of new communication technologies, making it crucial to define the role of drone technology in journalism. This study aims to investigate journalists' perspectives on drone technology and its effects on their professional lives. The research examines how journalists use drone technology, its contributions to their journalistic processes, and the challenges they face in detail. A qualitative paradigm was adopted for this study, and data were collected through semi-structured interviews within a phenomenological design. The data obtained were analyzed using thematic analysis with MAXQDA qualitative data analysis software. Due to resource and time constraints, the study was limited to 11 journalists working in Türkiye. The findings indicate that the use of drones in journalism is perceived positively for facilitating access, providing bird's-eye view imagery, enhancing aesthetic visuals, reducing physical and material risks in the news-gathering process, increasing the attractiveness of news, promoting objective journalism, and creating new employment opportunities. However, the findings also reveal concerns regarding the violation of personal data protection, privacy, and the boundaries between public and private domains. As a result of these findings, it can be concluded that there are debates about the meaning and use of drone journalism in the industry and that theoretical, practical and legal advances are needed. This study has limitations in terms of research methodology, sampling technique and size. Future research could be improved with new studies that are larger in scale and focus specifically on female drone journalists.

Student Perceptions of Project-Based Learning When Studying ‘Information Systems’ in an ICT Engineering Program: Taking Advantage of Active Learning

This article presents a case study on the way of teaching and learning the subject ‘Information Systems’ to ICT (Information and Communication Technology) engineering students, which is based on an active learning strategy implemented through a Project-Based Learning (PjBL) method, a practice that facilitates knowledge acquisition in addition to enhancing diverse learning outcomes such as teamwork, critical thinking, and analysis, or communication skills. This study aims to present the students’ perceptions once they have undertaken the whole subject, to better understand the different positive and negative elements associated with PjBL implementation according to their opinions. Students’ perceptions of PjBL were obtained through a survey utilizing the Bipolar Laddering (BLA) technique, which allows them to identify their experiences in terms of both beneficial and challenging aspects, as well as potential improvements to their experiences. On one hand, the most relevant findings on their PjBL experience assessed as positive are presented as follows: to work by themselves on a real project related to the working world; to be able to apply the theoretical topics explained during the class sessions; to have highly talented instructors; to experience a very dynamic and effective way of learning; to give a final presentation to their classmates and the instructors; and to work in groups. On the other hand, when analyzing the core negative perceptions, the following ones were highlighted by the surveyed students: undertaking just a single project; having an overly theoretical context; and having too much freedom, which could lead to confusion.

Latency‐Sensitive Service Function Chains Intelligent Migration in Satellite Communication Driven by Deep Reinforcement Learning

ABSTRACTSatellite communication technology solves the problem that the traditional wired network infrastructure is difficult to achieve global communication coverage. However, factors such as satellite orbits introduce frequent changes to the network topology, and challenges like satellite failures and communication link interruptions are prevalent. In the face of these issues, service function chain (SFC) migration becomes a crucial method for swiftly adjusting SFCs during faults, maintaining service continuity and availability. This article proposes a latency‐sensitive SFC migration algorithm tailored to satellite networks. The algorithm first models the satellite network as a multi‐domain virtual network, capturing the constraints faced during SFC migration. Subsequently, a deep reinforcement learning algorithm integrated attention mechanism is designed to more accurately capture and understand the complex network environment and dynamic satellite network topology and derive optimal SFC migration strategies for superior performance. Finally, through experimentation and evaluation of the deep reinforcement learning‐driven latency‐sensitive service function chain intelligent migration algorithm (LS‐SFCM) in satellite communication, this study validates the effectiveness and superior performance of the algorithm in latency‐sensitive scenarios. It provides a new avenue for enhancing the service quality and efficiency of satellite communication networks.

Evolution of computing energy efficiency: Koomey's law revisited

For information and communication technology power consumption to be sustainable, the energy efficiency of computing systems must grow at least as fast as the demand for computing services. It is therefore crucial to understand how energy efficiency is evolving and how it will trend in the future, in order to take appropriate measures where possible. This article analyses the evolution of this parameter by analysing high-performance computers from 2008 to 2023, contrasting the results with those from Koomey's Law. It is concluded, after comparing the two that in the studied period and in the near future, energy efficiency continues to grow exponentially but at a slower rate than that established by Koomey's Law (maximum energy efficiency doubles every 2.29 years instead of every 1.57 years). Another interesting result is that energy efficiency grows at a slower rate (doubling every 2.29 years) than performance (doubling every 1.85 years).

Construction and Application of a Private 5G Standalone Medical Network in a Smart Health Environment: Exploratory Practice From China.

To date, the differentiated requirements for network performance in various health care service scenarios-within, outside, and between hospitals-remain a key challenge that restricts the development and implementation of digital medical services. This study aims to construct and implement a private 5G (the 5th generation mobile communication technology) standalone (SA) medical network in a smart health environment to meet the diverse needs of various medical services. Based on an analysis of network differentiation requirements in medical applications, the system architecture and functional positioning of the proposed private 5G SA medical network are designed and implemented. The system architecture includes the development of exclusive and preferential channels for medical use, as well as an ordinary user channel. A 3-layer network function architecture is designed, encompassing resource, control, and intelligent operation layers to facilitate management arrangements and provide network open services. Core technologies, including edge cloud collaboration; service awareness; and slicing of access, bearer, and core networks, are employed in the construction and application of the 5G SA network. The construction of the private 5G SA medical network primarily involves system architecture, standards, and security measures. The system, featuring exclusive, preferential, and common channels, supports a variety of medical applications. Relevant standards are adhered to in order to ensure the interaction and sharing of medical service information. Security is achieved through mechanisms such as authentication, abnormal behavior analysis, and dynamic access control. Three typical medical applications that rely on the 5G network in intrahospital, interhospital, and out-of-hospital scenarios-namely, mobile ward rounds, remote first aid, and remote ultrasound-were conducted. Testing of the 5G-enabled mobile ward rounds showed an average download rate of 790 Mbps and an average upload rate of 91 Mbps. Compared with 4G, the 5G network more effectively meets the diverse requirements of various business applications in prehospital emergency scenarios. For remote ultrasound, the average downlink rate of the 5G network is 4.82 Mbps, and the average uplink rate is 2 Mbps, with an average fluctuation of approximately 8 ms. The bandwidth, performance, and delay of the 5G SA network were also examined and confirmed to be effective. The proposed 5G SA medical network demonstrates strong performance in typical medical applications. Its construction and application could lead to the development of new medical service models and provide valuable references for the further advancement and implementation of 5G networks in other industries, both in China and globally.

A Decentralized Digital Watermarking Framework for Secure and Auditable Video Data in Smart Vehicular Networks

Thanks to the rapid advancements in Connected and Automated Vehicles (CAVs) and vehicular communication technologies, the concept of the Internet of Vehicles (IoVs) combined with Artificial Intelligence (AI) and big data promotes the vision of an Intelligent Transportation System (ITS). An ITS is critical in enhancing road safety, traffic efficiency, and the overall driving experience by enabling a comprehensive data exchange platform. However, the open and dynamic nature of IoV networks brings significant performance and security challenges to IoV data acquisition, storage, and usage. To comprehensively tackle these challenges, this paper proposes a Decentralized Digital Watermarking framework for smart Vehicular networks (D2WaVe). D2WaVe consists of two core components: FIAE-GAN, a novel feature-integrated and attention-enhanced robust image watermarking model based on a Generative Adversarial Network (GAN), and BloVA, a Blockchain-based Video frames Authentication scheme. By leveraging an encoder–noise–decoder framework, trained FIAE-GAN watermarking models can achieve the invisibility and robustness of watermarks that can be embedded in video frames to verify the authenticity of video data. BloVA ensures the integrity and auditability of IoV data in the storing and sharing stages. Experimental results based on a proof-of-concept prototype implementation validate the feasibility and effectiveness of our D2WaVe scheme for securing and auditing video data exchange in smart vehicular networks.

Digital signal detection and recognition in the communication field combining DAEN and CNN

In communication, the detection and recognition of digital signals have always faced problems such as low adaptability and high misclassification rate. To address these issues, this study innovatively fused the deep auto-encoder network with convolutional neural networks to construct a novel digital signal detection and recognition model. Firstly, this study utilized the powerful feature extraction capabilities of the deep auto-encoder network to extract key feature information from massive amounts of data. Then these features were combined with convolutional neural networks to construct a detection and recognition model. These results confirmed that the constructed digital signal detection and recognition model had values of 93.75% and 94.18% in data detection recognition rate and average classification accuracy, respectively. Meanwhile, this model also performed well in terms of data processing accuracy and recall. In the comparison of data processing, the accuracy and recall rates were 93.59% and 94.67%, respectively, and the performance of data detection and recognition was better than that of the comparison methods. This indicates that the constructed digital signal detection and recognition model can significantly improve the reliability and robustness of signal detection and recognition. This paper brings new breakthroughs to the development of digital signal detection and recognition technology in communication.

Electronic governance in advancing sustainable development goals through systematic literature review

E-governance has become a crucial element in transforming government institutions globally. In the digital era, governments are increasingly adopting information and communication technology (ICT) to improve efficiency, transparency, and public participation in decision-making processes. This article conducts a systematic literature review (SLR) of studies from 2018 to 2023, examining the intersection between e-governance and the Sustainable Development Goals (SDGs). Through a rigorous inclusion and exclusion process, 52 articles were identified, focusing on the relationship between e-governance and SDGs. This study aims to highlight critical trends and knowledge gaps in the current literature and offers insights into how e-governance can contribute to achieving SDGs. Additionally, it provides policy recommendations and suggests future research directions to enhance governance practices. While this research significantly advances understanding of e-governance’s role in sustainable development, it is limited by its reliance on a single database and narrow search terms, which may constrain the comprehensiveness of the findings. Expanding the scope of future research to include multiple databases and broader search terms is recommended to provide a more holistic view of the field.

Transforming respiratory diseases management: a CMO-based hospital pharmaceutical care model

IntroductionRespiratory diseases encompass a diverse range of conditions that significantly impact global morbidity and mortality. While common diseases like asthma and COPD exhibit moderate symptoms, less prevalent conditions such as pulmonary hypertension and cystic fibrosis profoundly affect quality of life and mortality. The prevalence of these diseases has surged by approximately 40% over the past 3 decades. Despite advancements in pharmacotherapy, challenges in drug administration, adherence, and adverse effects persist. This study aimed to develop and perform an interim validation of a Capacity-Motivation-Opportunity (CMO) model tailored for respiratory outpatients to enhance pharmaceutical care, which is the direct, responsible provision of medication-related care for the purpose of achieving definite outcomes that improve a patient’s quality of life, and overall wellbeing.MethodologyThis cross-sectional, multicenter study was conducted from March 2022 to March 2023. It comprised four phases: 1) forming an expert panel of 15 hospital pharmacists, 2) selecting respiratory pathologies based on prevalence and severity, 3) developing the CMO model’s pillars, and 4) integrating and conducting an interim validation of the model. The Capacity pillar focused on patient stratification and personalized care; the Motivation pillar aligned therapeutic goals through motivational interviewing; and the Opportunity pillar promoted the use of information and communication technologies (ICTs) for telemedicine.ResultsThe model included eight respiratory diseases based on expert assessment. For the Capacity pillar, 22 variables were defined for patient stratification, leading to three priority levels for personalized pharmaceutical care. In a preliminary test involving 201 patients across six hospitals, the stratification tool effectively classified patients according to their needs. The Motivation pillar adapted motivational interviewing techniques to support patient adherence and behavior change. The Opportunity pillar established teleconsultation protocols and ICT tools to enhance patient monitoring and care coordination.ConclusionThe CMO model, tailored for respiratory patients, provides a comprehensive framework for improving pharmaceutical care. By focusing on patient-centered care, aligning therapeutic goals, and leveraging technology, this model addresses the multifaceted needs of individuals with respiratory conditions. Future studies are necessary to validate this model in other healthcare systems and ensure its broad applicability.

Transitioning Perspectives in Digital Health Through Phenomenology Integration.

The evolution of digital health, from its early days as eHealth to its current expansive scope, reflects a significant transformation in health care delivery and management. This transition underscores the integration of digital technologies across the health continuum from prevention and diagnosis to treatment and rehabilitation. The emergence of digital health has introduced innovative solutions but also posed challenges, particularly in aligning technological advancements with health needs, human experiences, and ethical considerations. This position paper aims to explore the integration of phenomenology in digital health, advocating for a paradigm that emphasizes the centrality of human experience in the design and implementation of digital health solutions. It specifically seeks to address challenges related to relevance for individuals who "speak" different languages, ensuring long-term use, addressing digital and health literacy, coordinating various sources, and navigating ethical issues in the rapidly evolving digital health landscape. Drawing upon years of research and practical experience in communication technologies and health, this paper uses a reflective approach to examine the intersection of digital health and phenomenology. It reviews the historical development of digital health, identifies the challenges faced during its evolution, and discusses the potential of phenomenological methods to enhance user-centered design and ethical practices in digital health. The integration of phenomenology into digital health facilitates a deeper understanding of user experiences, enabling the development of more responsive and ethical digital health solutions. Participatory design models, informed by phenomenological perspectives, offer a pathway to bridge the gap between technological innovation and human-centric health care. The paper highlights successful practices in digital health development, including mobile apps for vaccination decision-making and platforms for managing chronic conditions, illustrating the benefits of a phenomenological approach. Transitioning perspectives in digital health through phenomenology integration represents a critical step toward realizing the full potential of digital technologies in health care.

Exploring the Landscape of Ubiquitous In-Home Health Monitoring: A Comprehensive Survey

Ubiquitous in-home health monitoring systems have become popular in recent years due to the rise of digital health technologies and the growing demand for remote health monitoring. These systems enable individuals to increase their independence by allowing them to monitor their health from the home and by allowing more control over their well-being. In this study, we perform a comprehensive survey on this topic by reviewing a large number of literature in the area. We investigate these systems from various aspects, namely sensing technologies, communication technologies, intelligent and computing systems, and application areas. Specifically, we provide an overview of in-home health monitoring systems and identify their main components. We then present each component and discuss its role within in-home health monitoring systems. In addition, we provide an overview of the practical use of ubiquitous technologies in the home for health monitoring. Finally, we identify the main challenges and limitations based on the existing literature and provide eight recommendations for potential future research directions toward the development of in-home health monitoring systems. We conclude that despite extensive research on various components needed for the development of effective in-home health monitoring systems, the development of effective in-home health monitoring systems still requires further investigation.

Jordan’s Regime Security Under the COVID-19 Pandemic: Securitisation Against Visible and Invisible Threats

The Jordanian authoritarian regime, headed by the Hashemite royal family, has developed a robust regime security system. Having defeated the Arab Nationalists and Palestinian militias, the most significant threats in the Kingdom’s history, and achieved peace with Israel, the monarchy appears to have legitimised its sovereignty and domestic rule. Meanwhile, nonterritorial threats represented by jihadists have continued intermittently despite a surveillance network and continuous securitisation by authorities. Worryingly, decades-long employment problems and inflationary risks are chronic security risks in Jordan in the 21st century. This study examines how Jordan’s regime is functioning against new and old internal security risks during an unprecedented emergency, the COVID-19 pandemic. Under several lockdowns, the government could securitise prominent social forces including Islamists and professional associations for regulation violations. However, it needed to be more effective against the grassroots movement that continued to criticise the government while using cyberspace as its main battleground. Most critical cases, such as the 2021 uproar over former Crown Prince Hamza, primarily became virtual movements. The battle without winners and losers, fought using information and communication technologies from the perspective of digital authoritarianism by the government and liberation technology by resistance forces, posed a new challenge for Jordan’s regime security.