A survey of automatic contact tracing approaches using bluetooth low energy

To combat the ongoing Covid-19 pandemic, many new ways have been proposed on how to automate the process of finding infected people, also called contact tracing. A special focus was put on preserving the privacy of users. Bluetooth Low Energy as base technology has the most promising properties, so this survey focuses on automated contact tracing techniques using Bluetooth Low Energy. We define multiple classes of methods and identify two major groups: systems that rely on a server for finding new infections and systems that distribute this process. Existing approaches are systematically classified regarding security and privacy criteria.Copyright © 2021 ACM.

Joystick Controlled Autonomous Robotic Arm Using Inverse Kinematics with Object Detection

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.

Design and Implementation of a Microstrip Array for WiFi External Antenna

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.

A novel transfer learning model on complex fuzzy inference system

Transfer learning (TL) is further investigated in computer intelligence and artificial intelligence. Many TL methodologies have been suggested and applied to figure out the problem of practical applications, such as in natural language processing, classification models for COVID-19 disease, Alzheimer's disease detection, etc. FTL (fuzzy transfer learning) is an extension of TL that uses a fuzzy system to pertain to the vagueness and uncertainty parameters in TL, allowing the discovery of predicates and their evaluation of unclear data. Because of the system's increasing complexity, FTL is often utilized to further infer proper results without constructing the knowledge base and environment from scratch. Further, the uncertainty and vagueness in the daily data can arise and modify the process. It has been of great interest to design an FTL model that can handle the periodicity data with fast processing time and reasonable accuracy. This paper proposes a novel model to capture data related to periodical phenomena and enhance the quality of the existing inference process. The model performs knowledge transfer in the absence of reference or predictive information. An experimental stage on the UCI and real-life dataset compares our proposed model against the related methods regarding the number of rules, computing time, and accuracy. The experimental results validated the advantages and suitability of the proposed FTL model.

A new federated learning-based wireless communication and client scheduling solution for combating COVID-19.

Federated learning is a machine learning method that can break the data island. Its inherent privacy-preserving property has an important role in training medical image models. However, federated learning requires frequent communication, which incur high communication costs. Moreover, the data is heterogeneous due to different users' preferences, which may degrade the performance of models. To address the problem of statistical heterogeneity, we propose FedUC, an algorithm to control the uploaded updates for federated learning, where a client scheduling method is made on the basis of weight divergence, update increment, and loss. We also balance the local data of the clients by image augmentation to mitigate the impact of the non-independently identically distribution. The server assigns compression thresholds to the clients based on the weight divergence and update increment of the models for gradient compression to reduce the wireless communication costs. Finally, based on the weight divergence, update increment and accuracy, the server dynamically assigns weights to the model parameters for the aggregation. Simulation and analysis utilizing a publicly available chest disease dataset containing COVID-19 are compared with existing federated learning methods. Experimental results show that our proposed strategy has better training performance in improving model accuracy and reducing wireless communication costs.

Concept renovation: a new perspective of minimally invasive surgery. TT -:.

The development and innovation of laparoscopic vision platform has promoted the innovation of surgical concept and technology from laparotomy to minimally invasive surgery. From the initial use of reflector device with candlelight to observe the interior of the human body cavity, to the high-definition and ultra-high-definition laparoscopic vision system, from laparoscopic cholecystectomy, to the popularization and promotion of various laparoscopic surgery for malignant tumor, surgery has undergone great changes due to minimally invasive technology. In the new era, the application of three-dimensional and 4K laparoscope brings a new perspective to minimally invasive surgery, so as to promote the development of surgery in the direction of accurate anatomy and functional protection. In the future, stimulated by concept renovation in post-epidemic era of COVID-19, virtual reality technology and robotic surgery supported by the fifth generation wireless systems, as well as tele-surgery and distance training and teaching based on it, will become a new perspective for the development of minimally invasive surgery.Copyright © 2020 by the Chinese Medical Association.

Federal learning edge network based sentiment analysis combating global COVID-19.

As one of the important research topics in the field of natural language processing, sentiment analysis aims to analyze web data related to COVID-19, e.g., supporting China government agencies combating COVID-19. There are popular sentiment analysis models based on deep learning techniques, but their performance is limited by the size and distribution of the dataset. In this study, we propose a model based on a federal learning framework with Bert and multi-scale convolutional neural network (Fed_BERT_MSCNN), which contains a Bidirectional Encoder Representations from Transformer modules and a multi-scale convolution layer. The federal learning framework contains a central server and local deep learning machines that train local datasets. Parameter communications were processed through edge networks. The weighted average of each participant's model parameters was communicated in the edge network for final utilization. The proposed federal network not only solves the problem of insufficient data, but also ensures the data privacy of the social platform during the training process and improve the communication efficiency. In the experiment, we used datasets of six social platforms, and used accuracy and F1-score as evaluation criteria to conduct comparative studies. The performance of the proposed Fed_BERT_MSCNN model was generally superior than the existing models in the literature.

Development of Pandemic Monitoring System Based on Constellation of Nanosatellites

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.

Internet of Medical Things - The Future of Healthcare

Background: The Internet of Medical Things (IoMT) is now being connected to medical equipment to make patients more comfortable, offer better and more affordable health care options, and make it easier for people to get good care in the comfort of their own homes. Objective(s): The primary purpose of this study is to highlight the architecture and use of IoMT (Internet of Medical Things) technology in the healthcare system. Method(s): Several sources were used to acquire the material, including review articles published in various journals that had keywords such as, Internet of Medical Things, Wireless Fidelity, Remote Healthcare Monitoring (RHM), Point-of-care testing (POCT), and Sensors. Result(s): IoMT has succeeded in lowering both the cost of digital healthcare systems and the amount of energy they use. Sensors are used to measure a wide range of things, from physiological to emotional responses. They can be used to predict illness before it happens. Conclusion(s): The term "Internet of Medical Things" refers to the broad adoption of healthcare solutions that may be provided in the home. Making such systems intelligent and efficient for timely prediction of important illnesses has the potential to save millions of lives while decreasing the burden on conventional healthcare institutions, such as hospitals. patients and physicians may now access real-time data due to advancements in IoM. Copyright © 2022 Wal et al.

An Autonomous IoT-based Contact Tracing Platform in a COVID-19 Patient Ward

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

Practicing Telemedicines in India

The great use of telecommunication technology propels new healthcare system of telemedicine through which diagnosis as well as treatment can be done in the remote areas. The ancient Greek language explain the terminology of telemedicine in the phrase of distance healing. As per WHO, Telemedicine is the delivery of health-care services, where distance is a critical factor, by all health-care professionals using information and communications technologies for the exchange of valid information for diagnosis, treatment and prevention of disease and injuries, research and evaluation, and the continuing education of health-care workers, with the aim of advancing the health of individuals and communities. Historically the concept of teleconsultation was evolved in the first half of twentieth century when the data of ECG was communicated through telephone lines, this can be traced as first evidence of this unique healthcare system. Further the introduction of electrical system of telegraph as well as evolution of telephone revolutionized this system of healthcare. when the Technology of telemedicine help both patients as well as service providers in multiple ways involving physicians, surgeons, pharmacists, paramedical staff, IT and electronics engineers, government, hospitals and end user public Location is now a days no problem and therefore there is no limitation of the availability of healthcare facilities to such location or remote location. The biggest role in such development is played by the communication technology which may provide healthcare services to every nook and corner of the location. It can decrease the health staff pressure because in India WHO guidelines ask to maintain the ratio 1:1000 of doctor and Indian public compared to present 0.62:1000 ratio of doctor and public. The great advantage of this system is that in case of epidemic or pandemic like COVID 19 Telemedicine can keep the health staff are well general public free from contagious infection (COVID-19). There are a number of networking communication modes that can be applied, which may improve the patient compliance,dosage regimen can be managed in better fashion thus increase the longevity of person life. Disasters management during pandemics present unique challenges which can be addressed effectively as happened during the lockdown. This technology-based practice can break the infectivity chain of the transmission of communicable diseases This chapter incorporates basic concept of telemedicine, its origin and types, communication technologies, services by telemedicine, types of telemedicine, tools of telemedicine, telemedicine software's and guidelines related to practicingtelemedicine in reference to Indian context. Copyright © RJPT All right reserved.

Cost-Effective Solution of Remote Photoplethysmography Capable of Real-Time, Multi-Subject Monitoring with Social Distancing.

Recent advances in remote-photoplethysmography (rPPG) have enabled the measurement of heart rate (HR), oxygen saturation (SpO2), and blood pressure (BP) in a fully contactless manner. These techniques are increasingly applied clinically given a desire to minimize exposure to individuals with infectious symptoms. However, accurate rPPG estimation often leads to heavy loading in computation that either limits its real-time capacity or results in a costly setup. Additionally, acquiring rPPG while maintaining protective distance would require high resolution cameras to ensure adequate pixels coverage for the region of interest, increasing computational burden. Here, we propose a cost-effective platform capable of the real-time, continuous, multi-subject monitoring while maintaining social distancing. The platform is composed of a centralized computing unit and multiple low-cost wireless cameras. We demonstrate that the central computing unit is able to simultaneously handle continuous rPPG monitoring of five subjects with social distancing without compromising the frame rate and rPPG accuracy.

Performance Measures on IoMT Enabled Sensor based Respiratory Monitoring System for Measurement of Vital Parameters: A Descriptive Study

Currently, COVID-19 causes a variety of irregular respiratory symptoms that need to be tracked and assessed in order to deliver prompt medical aid. Wearable sensors and various patient tracking systems provide enhanced health services. IoT based monitoring system using various wearable sensors can be implemented to provide immediate medical support to the patients which will reduce human errors and also can eliminate delays in decision making. This paper provides a systematic approach for measuring respiration rate through sensor-based measurement system with integration of IoMT (Internet of Medical Things) wireless communication protocol. This paper also provides a descriptive study on breathing signal extraction and monitoring. The wide range of scientific articles have been collected and reviewed for developing a smart respiratory monitoring system. The development of IoMT enabled piezo sensor based respiratory rate monitoring system is designed and tested with software and hardware programming environment for accurate measurement of respiration rate. © 2022 IEEE.

On-chip coronavirus shape antenna for wide band applications in terahertz band

In this paper, a novel compact planar coronavirus antenna is proposed for wide band applications. In the design of this antenna, the idea of the radiating part has been taken from the 3-D model of the coronavirus, which is fed by a 50 omega coplanar waveguide. The patch structure and the feed line of the proposed antenna, which have been made of gold, are located on a polyamide substrate with a thickness and dielectric constant of 45 mu m and 3.5, respectively, and the antenna has compact physical dimensions of 300 x 300 mu m(2). The simulation results of the antenna have been analyzed in terms of S-11, VSWR, radiation pattern, gain and surface current distribution. The designed antenna covers the frequency band from 0.3627 to 0.5918 THz for S-11 <= - 0 dB with a fractional bandwidth of > 47.98% and with a bandwidth ratio of 1.63:1. This extended bandwidth coverage allows the antenna to be suitable for a wide range of applications including wireless communications, internet of things, wearable devices, on-chip antennas and multiple-input multiple-output systems. Also, the results of the far-field show an omnidirectional radiation pattern with an average gain and efficiency of 4 dBi and 93% throughout the frequency band, respectively.

Passive and Privacy-Preserving Human Localization: A Social Distancing Approach Using Commercial Millimeter-Wave Access Points

The pandemic outbreak has profoundly changed our life, especially our social habits and communication behaviors. While this dramatic shock has heavily impacted human interaction rules, novel localization techniques are emerging to help society in complying with new policies, such as social distancing. Wireless sensing and machine learning are well suited to alleviate virus propagation in a privacy-preserving manner. However, their wide deployment requires cost-effective installation and operational solutions.

Wireless Communication System and Its Application in Big Data Remote Monitoring and Decision-Making

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.

Research on collecting microbial samples of infectious diseases using aviation UAV network

Objective: Some infectious diseases spread very fast, viruses such as COVID-19, once infected, do great harm to human body. In order to control the spread of infectious diseases, it is necessary to collect microbial samples of infectious diseases for research, understand the nature of infectious diseases and take reasonable measures to prevent them. However, in some places where infectious diseases with great transmission power have occurred, such as hospitals, sending personnel to collect microbial samples is in danger of being infected. In order to reduce this risk, UAV (unmanned aerial vehicle) can be used to collect microbial samples of infectious diseases. Low altitude UAV has the advantages of low cost, high flexibility and easy rapid deployment. Methods: Using wireless communication technology to control the UAV cluster network is a common method of UAV wireless remote control. With its flexible flight characteristics and good channel characteristics, UAV can stay in the air for a long time, and can also be used as an air base station to provide various communication services. If an infectious disease occurs in an area, then use the aviation UAV to enter the highly dangerous infectious disease area. The UAV is equipped with corresponding sensors to identify the specific situation of the disease, and then use special tools to collect microbial samples of infectious diseases, Including exudates, secretions, tissues, various disease body fluids, etc., for researchers to analyze the nature of infectious disease samples. Results: Various infectious diseases with high infectivity, such as COVID-19, are easy to spread. For this highly infectious virus, even if people use appropriate equipment and preventive measures, they may still be infected. The collection of microbial samples of infectious diseases by aviation UAV can prevent the staff from directly contacting with the virus of infectious diseases. This way improves the safety of the staff, which is a very effective way to prevent infectious diseases. Conclusion: Taking advantage of the flexibility of aerial UAV, some microbial samples with highly infectious diseases are collected, which is not only suitable for areas with infectious diseases, but also suitable for hospital wards and other places. Infectious diseases always have certain transmission routes and conditions, infectious diseases can be transmitted in many ways. The same infectious disease can be transmitted in many different ways. Respiratory infectious diseases, such as COVID-19, are mainly transmitted through the respiratory tract. Pathogens exist in the air or form aerosols, forming an air transmission characteristic. Once inhaled into the body, healthy people may be infected. However, as long as we master the mode of transmission of diseases and pay due attention to prevention, we can eliminate the occurrence of infectious diseases. In some areas with poor sanitary conditions and poor hygiene habits, there are more cases of infectious diseases. Therefore, for the prevention of various infectious diseases, especially COVID-19 viruses, we must strengthen personal disinfection, strictly isolate the source of infection, and make reasonable arrangements in management measures to reduce the occurrence of infectious cases.

Dual-Factor WBAN Enhanced Authentication System Based on Iris and ECG Descriptors

At present, COVID-19 is still spreading and affecting millions of people worldwide. Minimizing the need for travel can significantly reduce the probability of infection and improve patients’quality of life. The wireless body area network (WBAN) transmits the patients’physiological data to the doctor remotely through the sensors in a way that minimizes physical contact with others. However, existing WBAN security authentication schemes have core limitation that includes weak authentication performance and over-consumption of resources that precludes their widespread adoption in practical applications. Therefore, in this paper, an enhanced dual-factor authentication system that address the mentioned drawbacks is proposed for securing WBAN resources. By combining iris and electrocardiogram (ECG) features, users would be required to pass the first-level iris authentication before performing the second-level ECG authentication, thus enhancing the overall security scheme of a WBAN system. Furthermore, we examined the existing Inter-Pulse-Intervals (IPI) encoding methods and propose a more efficient ECG IPI encoding algorithm which can effectively shorten the encoding time without affecting the overall encoding performance. Finally, extensive experiments were performed to verify the performance of the proposed dual-factor iris and ECG based WBAN authentication system using public iris and ECG databases. The experimental results show that the false acceptance rate (FAR) is close to 0.0% and the false rejection rate (FRR) is close to 3.2%. Findings from this study suggest that the proposed dual-factor authentication scheme could aid adequate deployment of security schemes to protect WBAN resources in practical applications. IEEE

Design of medical robot control system based on single-chip microcomputer

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.

Contactless COVID-19 vaccine verification system

The novel Corona virus has created maximum impact to the society with growing challenges as a result of its new evaluation. The development of new strategic plans or initiated to safeguard the people from global pandemic were wearing Mask in public places sanitization or employed to have maximum protection. Various modifications or derived in public places to avoid contact with each other physically. The proposed studies focus on the driving a Roberts to model for contact us communication is established. The proposed approach utilised Embedded Technology enabled vaccinated people verification is done. Proposed design is identified as an advance people identification system using advance to computing techniques with Raspberry Pi 4. The benefit of reconfigurable embedded technology offers low cost and reliable hardware used to make customized consumer products. The proposed system can be placed in public places to validate the people entry. Automated systems are highly reliable in long term accessibility. The system can be installed anywhere easily using a small camera object and display insertion. © 2022 International Journal of Health Sciences.