Real-time Communication Research Articles

MARIC: an efficient multi-agent real-time intention-based communication model for team cooperation

MARIC: an efficient multi-agent real-time intention-based communication model for team cooperation

Experimental Demonstration and Practical Application of a Real-Time Full-Duplex Underwater Wireless Optical Communication Transceiver

Experimental Demonstration and Practical Application of a Real-Time Full-Duplex Underwater Wireless Optical Communication Transceiver

Parameters Optimization of Decoy-State Phase-Matching Quantum Key Distribution Based on the Nature-inspired Algorithms

Abstract Phase-Matching quantum key distribution (PM-QKD) has achieved significant results in practical applications; however, real-time communication necessitates the dynamic adjustment and optimization of key parameters during the communication process. In this paper, we predict the parameters of PM-QKD using Nature-inspired Algorithms (NIAs), with results obtained from an Exhaustive Traversal Algorithm (ETA) serving as the benchmark. We mainly study the parameter optimization effects of the two NIAs which are Ant Colony Optimization (ACO) and Genetic Algorithm (GA). Meanwhile the configuration of the inherent parameters of these algorithms in decoy-state PM-QKD is discussed. The simulation results indicate that the parameters obtained by ACO exhibits superior convergence and stability, while the results of the GA are relatively scattered. Nevertheless, over 97% of the key rates predicted by both algorithms are highly consistent with the optimal key rate, with the relative error of key rates remaining below 10%. Furthermore, NIAs not only keep power consumption below 8W, but also require three orders of magnitude less computing time than ETA.

How Government Organizations Can Sustain Remote Work Post COVID-19

Government organizations are unprepared to sustain remote work post-COVID-19. Even though COVID-19 seems to be under control, organizations are still struggling with the aftermath of the pandemic and the need to sustain remote work. Challenges include lack of necessary information technology tools, software, technological skills, strategies for remote work, leadership skills, real-time communication, activity planning and program implementation, scheduling meetings, organizing childcare, managing caseloads, fostering team work, and effective supervision. A conceptual framework based on organizational adaptation theory guided this qualitative case study. Since the study was to ascertain how government organizations can sustain remote work post-COVID-19, semi-structured interviews were used to collect data from 12 government employees in Dallas Texas who worked remotely during COVID-19. Thematic analysis was conducted and. nine themes morphed from the study. The results highlighted the need for employee training and continuous organizational adaptation to the changing business environment.

Research and Simulation Application of Automatic Generation of Judging Curves for IoT Mobile Devices in Train Driving Operations Incorporating Hybrid Genetic Algorithms

A control system for automatically generating a train operation evaluation curve based on a hybrid genetic algorithm has been proposed in order to improve the safety of automatic train operation. The system is based on Internet of Things (IoT) mobile devices and utilizes various sensors such as accelerometers, gyroscopes, barometers, and GPS to collect real-time data on the driver’s acceleration, angular velocity, air pressure, and position, among other parameters. 5G wireless communication technology is used to achieve high-speed data transmission and real-time communication with the cloud. Based on cloud data, a spatial grid area planning model is constructed to automatically generate the train operation evaluation curve. Using a spatial dynamic programming method, the entire network of Electric Multiple Unit (EMU) trains is treated as a whole, and a dynamic model of the EMU train is constructed. The spatial area parameters of the EMU train’s automatic driving operation evaluation curve are combined with the dynamic model analysis method. By identifying and analyzing environmental parameters such as train speed and distance, the EMU train’s automatic driving operation evaluation curve is optimized. A hybrid genetic evolution learning optimization algorithm is used to fit the motion spatial parameters of the EMU train’s automatically generated driving operation evaluation curve, and a spatial behavior analysis simulation is created for the EMU train’s automatically generated control driving operation curve. Through the use of hybrid genetic evolution learning optimization technology, adaptive control and automatic driving operation curve simulation planning for the automatically generated driving operation evaluation curve of the maglev train are achieved, as well as simulation and algorithm optimization design for the automatically generated driving operation evaluation curve of the maglev train. The simulation results show that the method has good adaptability and strong automatic control capability. The experimental results demonstrate the control effect of the proposed method on energy consumption and train stopping error, indicating that the proposed method can effectively improve the parameter adjustment and offset correction ability of the evaluation curve generated by the high-speed train driving operation.

Automated Transport Management System: Route Optimization and Attendance Tracking for Institutions

Educational institutions face significant challenges in managing student transportation, such as inefficient route planning, manual attendance tracking, and the lack of real-time communication. These issues contribute to delays, operational inefficiencies, and safety concerns, leaving students, parents, and administrators with limited access to critical information about transportation logistics. Existing literature highlights advancements in transportation management through IoT, RFID, GPS, and AI, revealing both the potential of these technologies and their limitations in addressing hardware dependencies, network constraints, and manual interventions. Notable research includes IoT-based systems for bus tracking and attendance, Wi-Fi-enabled attendance solutions, and multiagent routing optimization algorithms, which underscore the effectiveness of real-time tracking and automation but reveal gaps in scalability, cost-effectiveness, and hardware reliability. To bridge these gaps, this project introduces the Automated Transport Management System (ATMS), a comprehensive platform designed to enhance efficiency, safety, and communication in student transportation. ATMS integrates GPS for real-time route visualization, barcode-based automated attendance logging, and proactive notifications accessible through a user-friendly web interface. This approach minimizes manual errors, reduces wait times, and ensures reliable service even in areas with variable connectivity, providing an efficient and flexible solution for educational institutions. By continuously evolving its features, ATMS aims to establish a new standard in transportation management, promoting student safety and operational effectiveness.

Analyzing real-time communication: Arduino-based Controller Area Network (CAN) in electric vehicle

The increasing complexity of electric vehicles (EVs) and the growing demand for propulsion and driver assistance have strengthened the need for CAN networks. This necessitates a detailed analysis of communication and CAN bus utilization. A low bus load does not guarantee a valid design if response times are insufficient. This paper presents a response time analysis (RTA) of a distributed real-time control system that uses an Arduino-based CAN network and an MCP2515 interface to check if the system can be scheduled. The RTA is based on calculating the worst-case response time of the message (WCRT), which is its longest response time. The prototype EV houses a system consisting of four (4) real-time embedded CAN nodes. We have implemented a PID controller within the motor speed control node. Based on existing literature, we proposed an algorithm to calculate the WCRT of the control system messages and another to address the priority inversion issue in network communication. The experimental results for the PID controller are satisfactory. The controller reaches the target speed with minimal oscillations with values 478ms, 31.81s, 0.62%, and 2.57%, corresponding to time rise, settling time, steady-state error, and overshoot at 90 rpm, demonstrating its robust performance. Experimental results confirm the scheduling analysis of the system with a low bus load (0.9% at 500 kbps). The tests conducted on the experimental and SAE benchmark data show that validity depends on message schedulability, bus load, and bandwidth. A system may be schedulable at 500 kbps but not at 125 kbps with the same traffic.

The Role of the Metaverse in Emergency Medicine and Its Legal Implications: A Systematic Review

Abstract: Introduction: The Metaverse, a virtual reality space fostering real-time interaction, captivates diverse sectors, including healthcare. This paper explores the Metaverse's role in emergency medicine, probing its implications on patient care and training. Amidst the fusion of virtual and physical realities, we scrutinize the legal landscape, unravelling promises and challenges in this transformative domain. This research aims to review metaverse applications in emergency medicine, analyze legal and ethical implications, and provide insights for future integration from a legal perspective. Methods: A comprehensive review of the literature was conducted to examine the current applications of the metaverse in emergency medicine. Legal frameworks, regulations, and ethical considerations relevant to utilizing the metaverse in healthcare were also analyzed. Results: The metaverse in emergency medicine presents opportunities and challenges. Real-time communication enhances response times, while simulated training refines skills. Telemedicine integration boosts accessibility, but data security and privacy concerns require legal adaptations. The evolving metaverse demands comprehensive regulatory structures to govern emergency medical services. Addressing liability and accountability issues, especially in emergencies, necessitates a nuanced legal approach. Balancing transformative potential with legal and ethical considerations is crucial for responsible implementation. Conclusion: In conclusion, integrating metaverse technologies in emergency medicine holds great potential for improving workflows, enhancing patient care, and expanding healthcare accessibility. However, addressing legal and ethical challenges is crucial for responsible and ethical application. Collaboration among policymakers, healthcare providers, and legal authorities is essential to establish robust frameworks protecting patient rights, securing sensitive health information, and ensuring accountability in virtual healthcare. Standardizing regulations and guidelines is crucial for clarity in metaverse technology utilization. Keywords: Metaverse, Emergency Medicine, Virtual Reality, Legal Implications, Healthcare Technology.

Efficiency of Police Cooperation in Criminal Investigations

Police cooperation is essential not only to investigate crime, but also to prevent it. Sharing information and best practices between law enforcement agencies allows early identification of threats, which can lead to prompt and effective interventions. At the same time, working together can reduce legislative or procedural disparities between states, which helps to strengthen joint efforts to fight crime. In addition to legal and operational challenges, police cooperation also raises ethical, privacy and data protection issues. In the digital age, the exchange of information between police agencies must comply with strict data protection standards in line with national and international legislation, such as the General Data Protection Regulation (GDPR) in the European Union. Thus, police cooperation is an indispensable tool in criminal investigations, offering the possibility to go beyond the geographical and legal limits imposed by national borders. However, its effectiveness depends on a clear legislative framework, mutual trust between partners and the adoption of modern technologies to facilitate real-time communication and information exchange. Police cooperation is an essential element in the fight against contemporary crime, but its effectiveness depends on resolving the legislative and operational problems that sometimes prevent effective inter-agency cooperation. Technological development and adaptation to new forms of crime also remain major challenges in this area.

Opportunities for Telemedicine to Improve Parents' Well-Being During the Neonatal Care Journey: Scoping Review.

Neonatal intensive care unit admissions of newborns are emotional and stressful for parents, influencing their mental and physical well-being and resulting in high rates of psychological morbidities. Significant research has been undertaken to understand and quantify the burden of a newborn's medical journey on parents' well-being. Simultaneously, an increase has been observed in the development and implementation of telemedicine interventions, defined as the remote delivery of health care. Telemedicine is used as an overarching term for different technological interventions grouped as real-time audio-visual communication, remote patient monitoring, and asynchronous communication. Various telemedicine interventions have been proposed and developed but scarcely with the primary goal of improving parental well-being during their newborn's medical journey. This study aims to identify telemedicine interventions with the potential to improve parents' well-being and to present the methods used to measure their experience. A scoping review was conducted, including empirical studies evaluating telemedicine in neonatal care that either measured parental well-being or included parents in the evaluation. Abstract and title screening, full-text screening, and data extraction were performed by three researchers. Two researchers were needed to reach decisions on both the inclusion and extraction of articles. The review included 50 out of 737 screened articles. Telemedicine interventions focused mainly on daily visits at the neonatal intensive care unit and discharge preparedness for parents. Surveys were the primary tool used for outcome measurement (36/50, 72%). Aspects of parents' well-being were evaluated in 62% (31/50) of studies. Telemedicine interventions developed to provide education and support showed a potential to improve self-efficacy and discharge preparedness and decrease anxiety and stress when they included a real-time telemedicine component. This scoping review identified specific telemedicine interventions, such as real-time audio-visual communication and eHealth apps, that have the potential to improve parental well-being by enhancing self-efficacy and discharge preparedness, and reducing anxiety and stress. However, more insights are needed to understand how these interventions affect well-being. Parents should be included in future research in both the development and evaluation stages. It is important to not only measure parents' perceptions but also focus on the impact of a telemedicine intervention on their well-being.

Improving Communication with Financial Consumers: Insights from a Study of Phone Call Phobia

A phone call phobia is a symptom of avoiding real-time communication that ranges from mild nervousness to a debilitating fear of making or receiving phone calls. The situation of avoidance of real-time communication, including phone call phobia, can potentially influence personal finance, particularly if it limits an individual's ability to communicate effectively with not only family, friends, and employers but also financial service providers. As the COVID-19 pandemic has affected ways of socializing and communicating, it is important to understand the situation and related factors of phone call phobia. This study, therefore, examined factors related to three types of phone call phobia (employer, family, and friends) and six types of communication preferences (face-to-face, phone calls, letters, email, text messaging, and online messaging apps). Using data from an online survey conducted in 2021, this study considered a list of comprehensive factors, including psychological factors, financial-psychological factors, financial status, job-related factors, health-related behavior, and demographic factors, in ordered logistic regression and seemingly unrelated regression estimation models. The findings provide insights to improve communication between financial consumers and financial services providers.

Students’ Perceptions of Their Speaking Practice with Foreign Interlocutors via Online Platforms

As online platforms become more widely accessible, English learners have greater opportunities to practice speaking with foreign interlocutors, though many remain hesitant due to a lack of confidence in their speaking abilities. This study examines the perceptions of 107 first-semester English learners at a private university who were assigned to use SCMC platforms like Free4Talk, InterPals, and HelloTalk to engage in English conversations with foreign interlocutors. The aim was to understand how these platforms supported speaking practice and identify any challenges faced. Data were collected through a questionnaire that included Likert-scale items and open-ended questions. The results revealed that 78% of students had positive perceptions, indicating that the platforms facilitated their English-speaking practice through real-time communication. However, they also reported technical issues, such as poor internet connectivity, and challenges with engagement, including difficulty finding consistent conversation partners. The study recommends further research into long-term language learner experiences and an exploration of platform features that could enhance English-speaking practice.

Autonomous vehicle diagnostics and support: a framework for API-Driven microservices

The rapid evolution of autonomous vehicles (AVs) demands robust and scalable diagnostic and support systems to ensure seamless operations, safety, and performance. This paper presents a framework for API-driven microservices tailored to address the unique diagnostic and support requirements of AVs. Traditional monolithic systems are insufficient for managing the complex, real-time data generated by AVs, necessitating a shift toward microservices architecture. By leveraging API-driven microservices, the proposed framework ensures modularity, scalability, and real-time communication between various vehicle components and external support systems. The framework is designed to support continuous vehicle monitoring, predictive maintenance, fault detection, and real-time decision-making, all while minimizing latency. APIs play a critical role in enabling interaction between different microservices, allowing for seamless data exchange across diverse platforms. This interoperability facilitates integration with third-party services, such as cloud-based diagnostics, real-time traffic information, and software updates. Additionally, the microservices architecture ensures fault isolation, meaning that failures in one service do not compromise the entire system. The framework also emphasizes the importance of cybersecurity and data privacy. Given the sensitive nature of AV data, API security protocols such as OAuth2 and TLS encryption are incorporated to safeguard communication between microservices and external systems. Furthermore, the design is scalable, allowing for the integration of future AV technologies and third-party service enhancements without disrupting existing functionalities. In conclusion, API-driven microservices provide an efficient, flexible, and secure solution for autonomous vehicle diagnostics and support. This framework has the potential to improve AV reliability, reduce downtime, and enhance safety by enabling real-time, data-driven decision-making and proactive maintenance. Future work may explore the integration of machine learning algorithms to further optimize diagnostics and predictive maintenance capabilities.

AI-Powered Conflict Resolution: Transforming Virtual Team Dynamics in Real-Time

This paper explores the transformative role of Artificial Intelligence (AI) in conflict resolution within virtual team dynamics. As remote work becomes increasingly prevalent, traditional conflict resolution strategies often fall short in addressing challenges like communication barriers, cultural differences, and workload imbalances. Leveraging AI-powered tools offers novel solutions by providing real-time communication clarity, data-driven insights, and objective mediation. The study emphasizes the potential of AI in fostering team cohesion through enhanced emotional intelligence, sentiment analysis, and automated conflict identification. Furthermore, it examines the ethical considerations, challenges, and future trends of AI integration, highlighting its ability to facilitate personalized, scalable, and proactive conflict resolution strategies. This research underscores AI's capacity to revolutionize virtual team management, enabling productive collaboration in an increasingly digital and globalized work environment.

Efficient Pruned-DFT FBMC-OQAM for Performance Enhancement of MIMO Channel Equalization Techniques

A The next generation of wireless systems, like 5G/6G, ought to accommodate a wide range of potential use cases like massive real-time and machine-type communications. Accordingly, such systems need to provide high throughput, low latency, and a low peak to average power ratio (PAPR). It is not feasible to fulfil each of these needs with a single 5G/6G technique. On one hand, MIMO technique can potentially improve spectral efficiency and hence support more date rates. On the other hand, the utilization of multi-carriers’ techniques like FBMC/OQAM, or offset quadrature amplitude modulation, offers a compelling substitute for the traditional cyclic prefix-based orthogonal frequency division multiplexing (CP-OFDM) because of its excellent spectral efficiency and extremely low out-of-band radiation. However, the FBMC/OQAM orthogonality constraint is loosened, confined to the real field alone, resulting in intrinsic interference. This interference causes incompatibilities between FBMC/OQAM and certain MIMO schemes. Also, equalizing the time-varying MIMO channel is even more difficult when the complex valued symbol—which includes both real and imaginary FBMC/OQAM task, primarily due to the general non-flatness of the subchannels. From this perspective, we first suggest in this paper an efficient pruned-DFT-based implementation of MIMO to restoring the complex orthogonality and also reduce the complexity of the whole system. Then, we optimize MIMO channel equalization by efficiently separating and equalizing multiple parallel channels using various equalization techniques. The numerical results, presented as MSE versus subcarrier index, show that Pruned DFT technique consistently achieves lower MSE values compared to the standard MIMO FBMC-OQAM across various configurations, which indicates better error performance and its robustness in dynamic channel conditions.

A systematic review on WebRTC for potential applications and challenges beyond audio video streaming

AbstractVideo conferencing and live streaming are being used in various industries, such as healthcare, gaming, telecommunication, manufacturing and others. As technology progresses, the need for real-time data transmission with minimal latency has increased. Web Real-Time Communication () addresses this need effectively. WebRTC is a technology designed to provide real-time communication through web and mobile browsers. Its low latency and P2P communication capabilities make it a convenient technology for secure, efficient communication in real-time applications. This paper reviews the key features of WebRTC, discusses its strengths and weaknesses and investigates a detailed analysis of 83 existing studies. Moreover, It evaluates all use cases that can be adopted by WebRTC by examining their descriptions, problem statements, and research gaps based on literature to date. Finally, It highlights the open research directions for the emerging technologies and enhancements of WebRTC. to identify their potential applications.

Combining quantum processors with real-time classical communication

Quantum computers process information with the laws of quantum mechanics. Current quantum hardware is noisy, can only store information for a short time and is limited to a few quantum bits, that is, qubits, typically arranged in a planar connectivity1. However, many applications of quantum computing require more connectivity than the planar lattice offered by the hardware on more qubits than is available on a single quantum processing unit (QPU). The community hopes to tackle these limitations by connecting QPUs using classical communication, which has not yet been proven experimentally. Here we experimentally realize error-mitigated dynamic circuits and circuit cutting to create quantum states requiring periodic connectivity using up to 142 qubits spanning two QPUs with 127 qubits each connected in real time with a classical link. In a dynamic circuit, quantum gates can be classically controlled by the outcomes of mid-circuit measurements within run-time, that is, within a fraction of the coherence time of the qubits. Our real-time classical link enables us to apply a quantum gate on one QPU conditioned on the outcome of a measurement on another QPU. Furthermore, the error-mitigated control flow enhances qubit connectivity and the instruction set of the hardware thus increasing the versatility of our quantum computers. Our work demonstrates that we can use several quantum processors as one with error-mitigated dynamic circuits enabled by a real-time classical link.

High-performance single SiC nanocable-based plasmonic photodetectors for ultraviolet communication systems

Silicon carbide (SiC) nanowires are the most promising candidate for developing high-performance single-nanowire-based UV photodetector (PD) with outstanding photoelectronic properties and low power consumption. However, SiC single-nanowire-based UV PDs commonly suffer from very low light current on the order of pA or nA, requiring precision equipment or an extra current amplification circuit, which greatly limit their practical application. To overcome this bottleneck, novel SiC single nanocable-based plasmonic PDs with the light current on the order of mA were successfully developed with the features of improving light absorption and reducing the dark current. The SiC/SiO2@Ag nanocables consisting of SiC nanowire core and uniform SiO2 shell encrusted with scattered and isolated Ag nanoparticles (NPs) were fabricated by a simple, low-cost, and space-confined vacuum-heating strategy using ultralong SiC nanowires and silver nitrate precursor followed by the annealing process. In such architecture, the in situ resulting SiO2 shell can effectively passivate the surface defects of the SiC nanowire core, restrain the photo-excited carrier's losses, and effectively block the hot electron injection, leading to a great reduction in the dark current and enhancement in the light current. The encrusted Ag NPs on the nanocable surface exhibited a strong LSPR effect with significantly increased optical absorption. Benefiting from the synergistic effect of SiO2 passivation and Ag nanoparticle LSPR effect, the device current increased dramatically by several orders of magnitude to reach 0.37 mA at a bias voltage of 3 V. Moreover, the developed SiC/SiO2@Ag PDs had faster response speed (0.27 s), lower dark current at the nA level, and high stability, which can be competent for the development of real-time, accurate, and cost-effective communication systems and flame detection with impressive switching ratio as high as 66012.

Enhancing Subsurface CO₂ Storage Monitoring and Sensing: A Novel Long-Term, Real-Time Wireless Communication System

Enhancing Subsurface CO₂ Storage Monitoring and Sensing: A Novel Long-Term, Real-Time Wireless Communication System

Multidisciplinary Approaches in General Medical Practice: Enhancing Collaboration for Better Patient Care

Multidisciplinary approaches in general medical practice have become integral to providing comprehensive, patient-centered care, as the complexity of modern health issues often requires a diverse range of expertise. This review explores the role and benefits of multidisciplinary teams in enhancing patient outcomes, improving resource efficiency, and increasing patient satisfaction in general medical settings. By examining the contributions of various healthcare professionals—including primary care physicians, specialists, allied health professionals, and behavioral health specialists—this review emphasizes how collaborative efforts address complex health needs more effectively than traditional, siloed approaches. Key case studies illustrate successful multidisciplinary practices in managing chronic diseases and complex conditions, highlighting the advantages of coordinated care models. The review also addresses challenges, such as communication barriers, hierarchical dynamics, and logistical constraints, that can hinder effective collaboration. Furthermore, it discusses technological supports, such as electronic health records (EHR) and telemedicine, which facilitate real-time communication and care coordination. The article concludes with recommendations for expanding multidisciplinary teams in primary care, promoting educational initiatives for team-based care skills, and advocating for policy support to institutionalize multidisciplinary approaches in general medicine. These findings suggest that well-coordinated multidisciplinary teams can transform patient care, making it more holistic, efficient, and responsive to individual needs.