Integration of digital technologies and public health (or digital healthcare) helps us to fight the Coronavirus Disease 2019 (COVID-19) pandemic, which is the biggest public health crisis humanity has faced since the 1918 Influenza Pandemic. In order to better understand the digital healthcare, this work conducted a systematic and comprehensive review of digital healthcare, with the purpose of helping us combat the COVID-19 pandemic. This paper covers the background information and research overview of digital healthcare, summarizes its applications and challenges in the COVID-19 pandemic, and finally puts forward the prospects of digital healthcare. First, main concepts, key development processes, and common application scenarios of integrating digital technologies and digital healthcare were offered in the part of background information. Second, the bibliometric techniques were used to analyze the research output, geographic distribution, discipline distribution, collaboration network, and hot topics of digital healthcare before and after COVID-19 pandemic. We found that the COVID-19 pandemic has greatly accelerated research on the integration of digital technologies and healthcare. Third, application cases of China, EU and U.S using digital technologies to fight the COVID-19 pandemic were collected and analyzed. Among these digital technologies, big data, artificial intelligence, cloud computing, 5G are most effective weapons to combat the COVID-19 pandemic. Applications cases show that these technologies play an irreplaceable role in controlling the spread of the COVID-19. By comparing the application cases in these three regions, we contend that the key to China's success in avoiding the second wave of COVID-19 pandemic is to integrate digital technologies and public health on a large scale without hesitation. Fourth, the application challenges of digital technologies in the public health field are summarized. These challenges mainly come from four aspects: data delays, data fragmentation, privacy security, and data security vulnerabilities. Finally, this study provides the future application prospects of digital healthcare. In addition, we also provide policy recommendations for other countries that use digital technology to combat COVID-19.

Integrating Digital Technologies and Public Health to Fight Covid-19 Pandemic: Key Technologies, Applications, Challenges and Outlook of Digital Healthcare.

The capacity of machine objects to communicate autonomously is seen as the future of the Internet of Things (IoT), but machine-to-machine communication (M2M) is also gaining traction. In everyday life, security, transportation, industry, and healthcare all employ this paradigm. Smart devices have the ability to detect, handle, store, and analyze data, resulting in major network issues such as security and reliability. There are numerous vulnerabilities linked with IoT devices, according to security experts. Prior to performing any activities, it is necessary to identify and classify the device. Device identification and classification in M2M for secure telerobotic surgery are presented in this study. Telerobotics is an important aspect of the telemedicine industry. The major purpose is to provide remote medical care, which eliminates the requirement for both doctors and patients to be in the same location. This paper aims to propose a security and energy-efficient protocol for telerobotic surgeries, which is the primary concern at present. For secure telerobotic surgery, the author presents an Efficient Device type Detection and Classification (EDDC) protocol for device identification and classification in M2M communication. The periodic trust score is calculated using three factors from each sensor node. It demonstrates that the EDDC protocol is more effective and secure in detecting and categorizing rogue devices.

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Machine-to-Machine Communication for Device Identification and Classification in Secure Telerobotics Surgery

The Tactile Internet (TI) is an emerging area of research involving 5G and beyond (B5G) communications to enable real-time interaction of haptic data over the Internet between tactile ends, with audio-visual data as feedback. This emerging TI technology is viewed as the next evolutionary step for the Internet of Things (IoT) and is expected to bring about a massive change in Healthcare 4.0, Industry 4.0 and autonomous vehicles to resolve complicated issues in modern society. This vision of TI makes a dream into a reality. This article aims to provide a comprehensive survey of TI, focussing on design architecture, key application areas, potential enabling technologies, current issues, and challenges to realise it. To illustrate the novelty of our work, we present a brainstorming mind-map of all the topics discussed in this article. We emphasise the design aspects of the TI and discuss the three main sections of the TI, i.e., master, network, and slave sections, with a focus on the proposed application-centric design architecture. With the help of the proposed illustrative diagrams of use cases, we discuss and tabulate the possible applications of the TI with a 5G framework and its requirements. Then, we extensively address the currently identified issues and challenges with promising potential enablers of the TI. Moreover, a comprehensive review focussing on related articles on enabling technologies is explored, including Fifth Generation (5G), Software-Defined Networking (SDN), Network Function Virtualisation (NFV), Cloud/Edge/Fog Computing, Multiple Access, and Network Coding. Finally, we conclude the survey with several research issues that are open for further investigation. Thus, the survey provides insights into the TI that can help network researchers and engineers to contribute further towards developing the next-generation Internet.

A Survey of the Tactile Internet: Design Issues and Challenges, Applications, and Future Directions

This article presents an overview of the current state of research and application of haptic (primarily kinesthetic) feedback and force-based teleoperation in the context of surgical robotics. Telerobotic surgery provides an approach for transferring the sensorimotor skills of a surgeon through a robotic platform to perform surgical intervention inside a patient’s body. Integration of advanced sensing and haptic technologies in telerobotic surgery can help to enhance the sensory awareness and motor accuracy of the surgeon, thereby leading to improved surgical procedures and outcomes for patients. The primary mode of sensory feedback has been through 3-D visual observation using stereo endoscopes. However, until recently, the sense of touch, i.e., haptics, has been missing in the commercial telesurgery robots approved for use in the operating room despite over two decades of research and development in the field of haptics for teleoperated systems (“telehaptics”). Research has shown that high-fidelity force feedback can enhance the performance of telesurgery and potential outcomes by enabling the surgeon to have a more natural feel of interaction between surgical tools and tissue as normally experienced during open surgery. Interaction forces, such as those generated during palpation of tissue, insertion of a needle, unintentional (and potentially unsafe) exertion of force by a tool, suture breakage, needle slippage, or tool interaction, are replaced by indirect (virtual) sensations, termed visual haptics, which provides an alternative to sensory compensation. Although there is a significant amount of literature supporting this benefit, there are still several important technical challenges in introducing haptics in telesurgery, including instrumentation, fidelity (transparency), stability, and modalities for force reflection, e.g., direct or indirect. This article examines these challenges and discusses recent work on haptics-based teleoperated surgical robotic systems.

Haptic Feedback and Force-Based Teleoperation in Surgical Robotics

e-BMI: A gait based smart remote BMI monitoring framework implementing edge computing and incremental machine learning

5G Enabled Tactile Internet for Tele-Robotic Surgery

Digital representation of odor has a basic principal of chemosensory organism of sensory molecules. A body organism responds to external odor environments. A body of animal/human perceives the odor in the form of molecule structure. But the questions still arises how that odor molecule is presented in the digital format. Also how it act a specific odor behavior. The mechanism used in animal/human body is to solve the problem as per thought process level. Thought process retrieve the stored molecule of odor in a visual smell. Similar concepts are carrying forward to store in a computer system with the help of electron. The system is applied to perform Machine-learned odor recognition from physico-chemical properties of volatile molecules. The properties of volatile molecules are to match the pattern of chemosensory organisms. Artificial intelligence is used to predict the molecule of smell by applying neural network. This paper focuses on the behavior of odors and its digital representation techniques for olfactory features.

http://www.it-in-industry.org/index.php/itii/article/download/131/116

Dewanand A. Meshram

Papers

5G Enabled Tactile Internet for Tele-Robotic Surgery

Digital representation techniques for olfactory features