ABSTRACT
In 2019, the Novel Coronavirus Disease (COVID-19) was categorized as a pandemic. This disease can be transmitted via droplets on items or surfaces within several hours. Therefore, the researchers aimed to develop a wirelessly controlled robot arm and platform capable of picking up objects detected via object detection. Robot arm movements are done via the use of inverse kinematics. Meanwhile, a custom object detection model that can detect objects of interest will be trained and implemented in this project. To achieve this, the researchers utilize various open-source libraries, microcontrollers, and readily available materials to construct and program the entire system. At the end of this research, the prototype could reliably detect objects of interest, along with a grab-and-dispose success rate of 88%. Instruction data can be properly sent and received, and dual web cam image transfer reaches up to 1.72 frames per second. © 2023 IEEE.
ABSTRACT
The wireless communication system very essential technology and have significant use after corona virus effect the world very badly. The Wi-Fi technology exhibits good wireless communication to provide internet facility but suffers with low antenna gain. This novel array proposed method with different dielectric material properties is used to enhancement the gain of the Wi-Fi antenna. The operating frequency of the proposed antenna is at 2. 5GHZ. This proposed method consist of Teflon dielectric material with dielectric constant of 2.02 has the gain of 8.4dbi, return loss of -30db and VSWR is 1.85, with loss tangent 0.0002. This proposed method compares with different dielectric material like kapton and fr-4 substrate but Teflon exhibit the good results. This proposed method work good for PCB antennas and flexible and wearable antennas with kapton substrate. © 2022 IEEE.
ABSTRACT
The emergence of the COVID-19 pandemic has increased research outputs in telemedicine over the last couple of years. One solution to the COVID-19 pandemic as revealed in literature is to leverage telemedicine for accessing health care remotely. In this survey paper, we review several articles on eHealth and Telemedicine with emphasis on the articles' focus area, including wireless technologies and architectures in eHealth, communications protocols, Quality of Service, and Experience Standards, among other considerations. In addition, we provide an overview of telemedicine for new readers. This survey reviews several telecommunications technologies currently being proposed along with their standards and challenges. In general, an encompassing survey on the developments in telemedicine technology, standards, and protocols is presented while acquainting researchers with several open issues. Special mention of the state-of-the-art specialist application areas are presented. We conclude the survey paper by presenting important research challenges and potential future directions as they pertain to telemedicine technology.
ABSTRACT
Post-COVID-19, there are frequent manpower shortages across industries. Many factories pursuing future technologies are actively developing smart factories and introducing automation equipment to improve factory manufacturing efficiency. However, the delay and unreliability of existing wireless communication make it difficult to meet the needs of AGV navigation. Selecting the right sensor, reliable communication, and navigation control technology remains a challenging issue for system integrators. Most of today's unmanned vehicles use expensive sensors or require new infrastructure to be deployed, impeding their widespread adoption. In this paper, we have developed a self-learning and efficient image recognition algorithm. We developed an unmanned vehicle system that can navigate without adding any specialized infrastructure, and tested it in the factory to verify its usability. The novelties of this system are that we have developed an unmanned vehicle system without any additional infrastructure, and we developed a rapid image recognition algorithm for unmanned vehicle systems to improve navigation safety. The core contribution of this system is that the system can navigate smoothly without expensive sensors and without any additional infrastructure. It can simultaneously support a large number of unmanned vehicle systems in a factory.
ABSTRACT
Mobile broadband (MBB) penetration has deepened globally over the last twenty years. This is largely due to the adoption of smart devices, improved mobile communications network coverage, and the perpetual drive to develop ever faster mobile and wireless communication technologies. However, information on the quality of service (QoS) delivered by MBB operators to the end users remains an issue of concern. This has driven independent researchers and mobile communication industry regulators to develop methodologies for independent and unbiased evaluation of the QoS offered by MBB networks. This paper provides a detailed review of MBB adoption and penetration across several regions of the world. It also includes the existing methodologies for evaluating the performance of MBB systems as experienced by the end user. Specifically, methodologies such as the drive and walk tests, crowd-sourced mobile device-based methods and the software applications they employ, and the dedicated measurement testbeds are reviewed. Based on this, the challenges of adopting each of the methods are discussed in order to make a case for the development of more robust, partially autonomous and scalable MBB measurement platforms for the future.
ABSTRACT
Mobile computing is one of the significant opportunities that can be used for various practical applications in numerous fields in real life. Due to inherent characteristics of ubiquitous computing, devices can gather numerous types of data that led to innovative applications in many fields with a unique emerging prototype known as Crowd sensing. Here, the involvement of people is one of the important features and their mobility provides an exclusive opportunity to collect and transmit the data over a substantial geographical area. Thus, we put forward novel idea about Quality of Information (QOI) with unique parameters with opportunistic uniqueness of people's mobility in terms of sensing and transmission. Additionally, we propose some of the viable improved ideas about the competent opportunistic data collection through efficient techniques. This work also considered some of the open issues mentioned by previous related works.
ABSTRACT
The Metaverse allows the integration of physical and digital versions of users, processes, and environments where entities communicate, transact, and socialize. With the shift towards Extended Reality (XR) technologies, the Metaverse is envisioned to support a wide range of applicative verticals. It will support a seamless mix of physical and virtual worlds (realities) and, thus, will be a game changer for the Future Internet, built on the Semantic Web framework. The Metaverse will be ably assisted by the convergence of emerging wireless communication networks (such as Fifth-Generation and Beyond networks) or Sixth-Generation (6G) networks, Blockchain (BC), Web 3.0, Artificial Intelligence (AI), and Non-Fungible Tokens (NFTs). It has the potential for convergence in diverse industrial applications such as digital twins, telehealth care, connected vehicles, virtual education, social networks, and financial applications. Recent studies on the Metaverse have focused on explaining its key components, but a systematic study of the Metaverse in terms of industrial applications has not yet been performed. Owing to this gap, this survey presents the salient features and assistive Metaverse technologies. We discuss a high-level and generic Metaverse framework for modern industrial cyberspace and discuss the potential challenges and future directions of the Metaverse's realization. A case study on Metaverse-assisted Real Estate Management (REM) is presented, where the Metaverse governs a Buyer–Broker–Seller (BBS) architecture for land registrations. We discuss the performance evaluation of the current land registration ecosystem in terms of cost evaluation, trust probability, and mining cost on the BC network. The obtained results show the viability of the Metaverse in REM setups.
ABSTRACT
The paper proposes a compact-sized coronavirus-shaped Microstrip Patch Antenna (MPA) for wireless communication. A 15-20 GHz band of frequency is employed to analyze the effect of the shape on antenna's performance and characteristics. A low-cost FR4 dielectric substrate is used in the design and implementation of the coronavirus-shaped antenna, with suitable dimensions. The proposed antenna has six patterns depending upon the band of frequencies, and the same have been analyzed. The results show that the realized gain is better than -15 dB when using frequencies around 17 GHz, and total efficiency is about 70%. CST microwave software is used for designing and analysis.
ABSTRACT
The emergence of the Industry 4.0 revolution to upgrade the Internet of Things (IoT) standards provides the prominence outcomes for the future wireless communication systems called 5G. The development of 5G green communication systems suffers from the various challenges to fulfill the requirement of higher user capacity, network speed, minimum cost, and reduced resource consumption. The use of 5G standards for Industry 4.0 applications will increase data rate performance and connected device's reliability. Since the arrival of novel Covid-19 disease, there is a higher demand for smart healthcare systems worldwide. However, designing the 5G communication systems has the research challenges like optimum resource utilization, mobility management, cost-efficiency, interference management, spectral efficiency, etc. The rapid development of Artificial Intelligence (AI) across the different formats brings performance enhancement compared to conventional techniques. Therefore, introducing the AI into 5G standards will optimize the performances further considering the various end-user applications. We first present the survey of the terms like 5G standard, Industry 4.0, and some recent works for future wireless communications. The purpose is to explore the current research problems using the 5G technology. We further propose the novel architecture for smart healthcare systems using the 5G and Industry 4.0 standards. We design and implement that proposed model using the Network Simulator (NS2) to investigate the current 5G methods. The simulation results show that current 5G methods for resource management and interference management suffer from the challenges like performance trade-offs.
ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been garnered increasing for its rapid worldwide spread. Each country had implemented city-wide lockdowns and immigration regulations to prevent the spread of the infection, resulting in severe economic consequences. Materials and technologies that monitor environmental conditions and wirelessly communicate such information to people are thus gaining considerable attention as a countermeasure. This study investigated the dynamic characteristics of batteryless magnetostrictive alloys for energy harvesting to detect human coronavirus 229E (HCoV-229E). Light and thin magnetostrictive Fe-Co/Ni clad plate with rectification, direct current (DC) voltage storage capacitor, and wireless information transmission circuits were developed for this purpose. The power consumption was reduced by improving the energy storage circuit, and the magnetostrictive clad plate under bending vibration stored a DC voltage of 1.9 V and wirelessly transmitted a signal to a personal computer once every 5 min and 10 s under bias magnetic fields of 0 and 10 mT, respectively. Then, on the clad plate surface, a novel CD13 biorecognition layer was immobilized using a self-assembled monolayer of -COOH groups, thus forming an amide bond with -NH2 groups for the detection of HCoV-229E. A bending vibration test demonstrated the resonance frequency changes because of HCoV-229E binding. The fluorescence signal demonstrated that HCoV-229E could be successfully detected. Thus, because HCoV-229E changed the dynamic characteristics of this plate, the CD13-modified magnetostrictive clad plate could detect HCoV-229E from the interval of wireless communication time. Therefore, a monitoring system that transmits/detects the presence of human coronavirus without batteries will be realized soon.
ABSTRACT
Covid-19 is a global crisis and the greatest challenge we have faced. It affects people in different ways. Most infected people develop a mild to moderate form of the disease and recover without hospitalization. This presents a problem in spreading the pandemic with unintentionally manner. Thus, this paper provides a new technique for COVID-19 monitoring remotely and in wide range. The system is based on satellite technology that provides a pivotal solution for wireless monitoring. This mission requires a data collection technique which can be based on drones' technology. Therefore, the main objective of our proposal is to develop a mission architecture around satellite technology in order to collect information in wide range, mostly, in areas suffer network coverage. A communication method was developed around a constellation of nanosatellites to cover Saudi Arabia region which is the area of interest in this paper. The new proposed architecture provided an efficient monitoring application discussing the gaps related to thermal imaging data. It reached 15.8 min as mean duration of visibility for the desired area. In total, the system can reach a coverage of 5.8 h/day, allowing to send about 21870 thermal images. © 2023 CRL Publishing. All rights reserved.
ABSTRACT
Since 2020, the coronavirus disease (COVID-19) pandemic has had a substantial impact on all community sectors worldwide, particularly the health care sector. Healthcare workers (HCWs) are at risk of COVID-19 infection due to occupational exposure to infectious patients, visitors, and staff. Contact tracing of close physical interaction is an essential control measure, especially in hospitals, to prevent onward transmission during an outbreak event. In this article, we propose an IoT-based contact tracing system for subject identification, interaction tracking and data transmission in hospital wards. The system, based on Bluetooth Low Energy (BLE) devices, tracks the duration of interactions between different HCWs, and the time each HCW spends within the patient rooms using additional information from proximity sensors in the hallway or on the door frame of the patient room. The collected data are transferred via Long Range (LoRa) wireless technology and further analyzed to inform infection prevention activities. The suggested system’s performance is evaluated in a COVID-19 patient ward with both standard and negative pressure isolation rooms, and the current system’s capabilities and future research prospects are briefly discussed. IEEE
ABSTRACT
We are surrounded by oxygen in the air we We cannot even exist without the ability to breathe. The need for oxygen has increased during the COVID19 pandemic, and although there is enough oxygen in our country, the main issue is getting it to hospitals or those in need on time. This is simply due to a significant communication gap between suppliers and hospitals, so we plan to implement an idea that will close this gap using real-time tracking as we can track the movement of oxygen tankers by gathering the requirements. We are using an ESP32 Wi-Fi module, a MEMS pressure sensor that enables the combination of precise sensors, potential processing, and wireless communication, such as Wi-Fi, Bluetooth, IFTTT, and MQTT protocols, to implement it successfully. The pressure sensor publishes the value of oxygen remaining from the location to the MQTT broker. © 2022 IEEE.
ABSTRACT
The COVID-19 pandemic has resulted in one of the major challenges for humanity in the 21st century. The impact of these challenges has led to a tremendous loss of life, impact on long-term health, well-being as well as personal psychology, and negative societal changes and not to mention its impact on the global economy. Since this is a health issue, similar to other forms of diseases and pandemics, society has largely relied on the fields of medical, virology, immunology, biotechnology, and pharmaceutical science to develop novel therapeutic solutions for treatments. This has resulted in vaccines that have been rolled out to elevate immunity levels that will hopefully allow the majority of the population to reach herd immunity. However, given the technological advancements that we have reached in the 21st century, questions have also risen as to how other disciplines can play a role in solving and obtaining new knowledge of communicable disease pandemics.
ABSTRACT
With the development of telecare medical information system (TMIS), doctors and patients are able to access useful medical services via 5G wireless communications without visiting the hospital in person. Unfortunately, TMIS should have the essential security properties, such as anonymity, mutual authentication, and privacy, since the patient’s data is transmitted via a public channel. Moreover, the sensing devices deployed in TMIS are resource-limited in terms of communication and computational costs. Thus, we design a physically secure privacy-preserving scheme using physical unclonable functions (PUF) in TMIS, called PUF-PSS to resolve the security requirements and efficiency of the existing related schemes. PUF-PSS prevents the security threats and also guarantees anonymity, key freshness, and authentication. We evaluate the security of PUF-PSS by performing formal and informal security analyses, including AVISPA implementation and ROR oracle model. We perform the test bed experiments utilizing well-known MIRACL based on a Raspberry PI 4 and compare the communication and computational costs of PUF-PSS with the previous schemes for TMIS. Consequently, PUF-PSS guarantees better efficiency and security than previous schemes and can be applied to TMIS environments.
ABSTRACT
The COVID-19 pandemic has impacted every aspect of health delivery and encouraged to replace in-person clinical visits with telecommunications. By providing wireless communication between embedded electronic devices and sensors, telerehabilitation enables constant monitoring of vital body functions, and tracking of physical activities of a person and aids physical therapy. In this paper, we designed and tested two remotely controlled versions of interactive bike (iBikE) systems which communicate through either Wi-Fi or BLE and give the clinical team the capability to monitor exercise progress in real time using simple graphical representation. We used the same hardware and user interface for both designs. The software uses either Wi-Fi or BLE protocol to connect the iBikE equipment and PC tablet. The bike can be used for upper or lower limb rehabilitation. A customized tablet app was developed to provide user interface between the app and the bike sensors. Both bikes were tested with a single group of nine individuals in two separate sessions. Each individual was asked to hand-cycle for three separate sub-sessions (1 minute each for slow, medium, and fast pace) with one-minute rest. During each sub-session, speed of the bikes was measured continuously using a tachometer, in addition to reading speed values from the iBikE app, to compare the functionality and accuracy of the measured data. Measured RPMs in each sub-session from iBikE and tachometer were further divided into 4 categories: 10-second bins (6 bins), 20-second bins (3 bins), 30-second bins (2 bins), and RPMs in each sub-session (1 minute, 1 bin). Then, the mean difference of each category (iBikE, tachometer) was calculated for each sub-session. Finally, mean and standard deviation (SD) of the calculated mean differences were reported for all individuals. We saw decreasing trend in both mean and SD from 10 second to 1 minute measurement. For BLE iBikE system, minimum mean RPM difference was 0.2 \pm 0.3 in one-minute sub-session with medium speed. This number was 0.21 \pm 0.21 in one-minute sub-session with slow speed for Wi-Fi iBikE system. Thus, testing confirmed high accuracy of our interfaces. © 2022 IEEE.
ABSTRACT
The development of computer technology has promoted the widespread application of unmanned technology. Remote monitoring of wireless devices is an application of unmanned technology. To improve the remote monitoring of wireless devices, this study establishes a remote monitoring and decision-making framework based on wireless communication systems. With the wireless communication system, signals that characterize the operating status of devices can be obtained in real-time. Based on the collected signals, the remote monitoring system can identify the current health status of wireless devices, thereby providing auxiliary decision-making for device operation. In the case study, the main engine of an unmanned surface vehicle is used as the study object. The results show that most of the relative errors corresponding to the state identification results of the established remote monitoring framework are within 5%. Moreover, the results present that the linear correlation coefficients between the predicted and real results are greater than 0.95. Therefore, the established remote monitoring framework based on the wireless communication system has good reliability in the state identification of wireless devices.
ABSTRACT
In order to save manpower, improve the management of COVID-19 prevention and prevent the spread of the epidemic, this paper proposes and designs a medical robot based on a one-chip computer. The single-chip STC89C52 is used as the main control core. Obstacles are detected by infrared sensors. And the robot uses the tracking module to determine the path. The working states of the two DC motors are then changed by the IO-port control L298N drive template, thereby changing the motion state of the robot through the speed difference between the motors on both sides. In the intelligent tracking module, the robot first uses a genetic algorithm to find the best path forward inspection and then enters the ward. After disinfection, the robot uses STM32F4 to drive the OV2640 camera to collect data and detect the mask using the yolov5s algorithm. Finally, it sends the collected information to the computer to realize the real-time monitoring of the patient's condition. The simulation results show that the medical robot can effectively and accurately realize the requirements of path planning, facial mask recognition, and wireless communication. This will significantly improve the efficiency and safety of medical staff. © 2022 IEEE.
ABSTRACT
As the World is still facing the COVID-19 pandemic, several researchers and industry players have proposed technological solutions to help fight the pandemic and pave the way for post-pandemic era precautions. In this matter, the potential benefits of remote health monitoring have been brought back to the spotlight. Indeed, with current advances in wireless communications, core network virtualization, and computing architectures as enablers, consistently guaranteeing the stringent quality-of-service (QoS) requirements of remote health monitoring, e.g., ultra-low latency, may be achievable. Notably, the fog computing (FC) paradigm has been advocated as a potential solution for remote health monitoring. However, the unreliability of fog nodes in FC networks is a critical aspect often overlooked despite its significant impact on vital latency requirements. This paper proposes a reliable fog-based remote health monitoring framework operating under uncertain fog computing conditions. Specifically, we formulate the problem of assigning tasks of remote sensors attached to patients to their adequate applications deployed in fog nodes aiming to maximize the number of satisfied tasks with respect to the fog nodes’availability and communication latency constraints. Due to the problem’s NP-hardness, we leverage a differential evolution-based algorithm enhanced by reinforcement learning to deploy applications in fog nodes. Numerical results demonstrate the superior reliability performance of our proposed solution, in terms of the average success ratio of tasks, compared to benchmarks. Specifically, our simulations show up to 60 % performance improvement compared to benchmarks in specific scenarios. Moreover, by investigating the impact of several key parameters, we identify a design trade-off between the number of fog nodes and the latter’s intrinsic failure rates. IEEE
ABSTRACT
The recent COVID-19 pandemic has driven researchers from different spectrum to develop novel solutions that can improve detection and understanding of SARS-CoV- 2 virus. In this article we propose the use of Intelligent Reflector Surface (IRS) and terahertz communication systems to detect violent expiratory aerosol cloud that are secreted from people. Our proposed approach makes use of future IRS infrastructure to extend beyond communication functionality by adding environmental scanning for aerosol clouds. Simulations have also been conducted to analyze the accuracy of aerosol cloud detection based on a signal scanning and path optimization algorithm. Utilizing IRS for detecting violent expiratory aerosol cloud can lead to new added value of telecommunication infrastructures for sensor monitoring data that can be used for public health. IEEE