Network Management System for IoT Based on Dynamic Systems.

The Internet of Things (IoT) has the potential to transform the public sector by combining the leading technical and business trends of mobility, automation, and data analysis to dramatically alter the way public bodies collect data and information. Embedded sensors, actuators, and other devices that capture and transmit information about network activity in real-time are used in the Internet of Things to connect networks of physical objects. The design of a network management system for an IoT network is presented in this paper, which uses the edge computing model. This design is based on the Internet management model, which uses the SNMP protocol to communicate between managed devices, and a gateway, which uses the SOAP protocol to communicate with a management application. This work allowed for the identification and analysis of the primary network management system initiatives for IoT networks, in which there are four fundamental device management requirements for any deployment of IoT devices: provisioning and authentication, configuration and control, monitoring and diagnostics, and software updates and maintenance.

Development of an IoT-Based Sleep Apnea Monitoring System for Healthcare Applications.

Sleep is an essential and vital element of a person's life and health that helps to refresh and recharge the mind and body of a person. The quality of sleep is very important in every person's lifestyle, removing various diseases. Bad sleep is a big problem for a lot of people for a very long time. People suffering from various diseases are dealing with various sleeping disorders, commonly known as sleep apnea. A lot of people die during sleep because of uneven body changes in the body during sleep. On that note, a system to monitor sleep is very important. Most of the previous systems to monitor sleeping problems cannot deal with the real time sleeping problem, generating data after a certain period of sleep. Real-time monitoring of sleep is the key to detecting sleep apnea. To solve this problem, an Internet of Things- (IoT-) based real-time sleep apnea monitoring system has been developed. It will allow the user to measure different indexes of sleep and will notify them through a mobile application when anything odd occurs. The system contains various sensors to measure the electrocardiogram (ECG), heart rate, pulse rate, skin response, and SpO2 of any person during the entire sleeping period. This research is very useful as it can measure the indexes of sleep without disturbing the person and can also show it in the mobile application simultaneously with the help of a Bluetooth module. The system has been developed in such a way that it can be used by every kind of person. Multiple analog sensors are used with the Arduino UNO to measure different parameters of the sleep factor. The system was examined and tested on different people's bodies. To analyze and detect sleep apnea in real-time, the system monitors several people during the sleeping period. The results are displayed on the monitor of the Arduino boards and in the mobile application. The analysis of the achieved data can detect sleep apnea in some of the people that the system monitored, and it can also display the reason why sleep apnea happens. This research also analyzes the people who are not in the danger of sleeping problems by the achieved data. This paper will help everyone learn about sleep apnea and will help people detect it and take the necessary steps to prevent it.

AIoT Used for COVID-19 Pandemic Prevention and Control.

The pandemic of COVID-19 is continuing to wreak havoc in 2021, with at least 170 million victims around the world. Healthcare systems are overwhelmed by the large-scale virus infection. Luckily, Internet of Things (IoT) is one of the most effective paradigms in the intelligent world, in which the technology of artificial intelligence (AI), like cloud computing and big data analysis, is playing a vital role in preventing the spread of the pandemic of COVID-19. AI and 5G technologies are advancing by leaps and bounds, further strengthening the intelligence and connectivity of IoT applications, and conventional IoT has been gradually upgraded to be more powerful AI + IoT (AIoT). For example, in terms of remote screening and diagnosis of COVID-19 patients, AI technology based on machine learning and deep learning has recently upgraded medical equipment significantly and has reshaped the workflow with minimal contact with patients, so medical specialists can make clinical decisions more efficiently, providing the best protection not only to patients but also to specialists themselves. This paper reviews the latest progress made in combating COVID-19 with both IoT and AI and also provides comprehensive details on how to combat the pandemic of COVID-19 as well as the technologies that may be applied in the future.

Mapping the co-evolution of artificial intelligence, robotics, and the internet of things over 20 years (1998-2017).

Understanding the emergence, co-evolution, and convergence of science and technology (S&T) areas offers competitive intelligence for researchers, managers, policy makers, and others. This paper presents new funding, publication, and scholarly network metrics and visualizations that were validated via expert surveys. The metrics and visualizations exemplify the emergence and convergence of three areas of strategic interest: artificial intelligence (AI), robotics, and internet of things (IoT) over the last 20 years (1998-2017). For 32,716 publications and 4,497 NSF awards, we identify their topical coverage (using the UCSD map of science), evolving co-author networks, and increasing convergence. The results support data-driven decision making when setting proper research and development (R&D) priorities; developing future S&T investment strategies; or performing effective research program assessment.

Application of cognitive Internet of Medical Things for COVID-19 pandemic.

BACKGROUND AND AIM: In the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based IoT specific for the medical domain referred to as Cognitive Internet of Medical Things (CIoMT) is explored to tackle the global challenge. This concept of CIoT is best suited to this pandemic as every person is to be connected and monitored through a massive network that requires efficient spectrum management. METHODS: An extensive literature survey is conducted in the Google Scholar, Scopus, PubMed, Research Gate, and IEEE Xplore databases using the terms "COVID-19" and "Cognitive IoT" or "Corona virus" and "IoMT". The latest data and inputs from official websites and reports are used for further investigation and analysis of the application areas. RESULTS: This review encompasses different novel applications of CIoMT for fighting the ongoing COVID-19 health crisis. The CR based dynamic spectrum allocation technique is the solution for accommodating a massive number of devices and a wide number of applications. The CIoMT platform enables real-time tracking, remote health monitoring, rapid diagnosis of the cases, contact tracking, clustering, screening, and surveillance thus, reducing the workload on the medical industry for prevention and control of the infection. The challenges and future research directions are also identified. CONCLUSIONS: CIoMT is a promising technology for rapid diagnosis, dynamic monitoring and tracking, better treatment and control without spreading the virus to others.

Internet of things (IoT) applications to fight against COVID-19 pandemic.

BACKGROUND AND AIM: The current global challenge of COVID-19 pandemic has surpassed the provincial, radical, conceptual, spiritual, social, and pedagogical boundaries. Internet of Things (IoT) enabled healthcare system is useful for proper monitoring of COVID-19 patients, by employing an interconnected network. This technology helps to increase patient satisfaction and reduces readmission rate in the hospital. METHODS: Searched the databases of Google Scholar, PubMed, SCOPUS and ResearchGate using the keywords "Internet of things" or "IoT" and "COVID-19". Further inputs are also taken from blogs and relevant reports. RESULTS: IoT implementation impacts on reducing healthcare cost and improve treatment outcome of the infected patient. Therefore, this present study based research is attempted to explore, discuss, and highlight the overall applications of the well-proven IoT philosophy by offering a perspective roadmap to tackle the COVID-19 pandemic. Finally, twelve significant applications of IoT are identified and discussed. It has ultimately forced the researchers, academicians, and scientists to propose some productive solutions to overcome or confront this pandemic. CONCLUSIONS: IoT is helpful for an infected patient of COVID-19 to identify symptoms and provides better treatment rapidly. It is useful for patient, physician, surgeon and hospital management system.

The impact of IoT security labelling on consumer product choice and willingness to pay.

The Internet of Things (IoT) brings internet connectivity to everyday electronic devices (e.g. security cameras and smart TVs) to improve their functionality and efficiency. However, serious security and privacy concerns have been raised about the IoT which impact upon consumer trust and purchasing. Moreover, devices vary considerably in terms of the security they provide, and it is difficult for consumers to differentiate between more and less secure devices. One proposal to address this is for devices to carry a security label to help consumers navigate the market and know which devices to trust, and to encourage manufacturers to improve security. Using a discrete choice experiment, we estimate the potential impact of such labels on participant's purchase decision making, along with device functionality and price. With the exception of a label that implied weak security, participants were significantly more likely to select a device that carried a label than one that did not. While they were generally willing to pay the most for premium functionality, for two of the labels tested, they were prepared to pay the same for security and functionality. Qualitative responses suggested that participants would use a label to inform purchasing decisions, and that the labels did not generate a false sense of security. Our findings suggest that the use of a security label represents a policy option that could influence behaviour and that should be seriously considered.

Evaluating the Uptake and Acceptability of Standardized Postoperative Rehabilitation Guidelines Using an Online Knowledge Translation Approach.

BACKGROUND: Providing physical therapists with evidence-based and consensus-derived guidelines to manage postoperative shoulder patients is essential; these guidelines should be readily available and provide clinically applicable information. Knowledge translation (KT) initiatives that encourage interaction between clinicians and researchers, that have multifaceted components and use a variety of strategies, can significantly change practice. OBJECTIVE: The objective of this study was to determine the uptake and acceptability of standardized postoperative shoulder guidelines with an accompanying online KT resource through evaluation of website analytics and a quantitative survey. DESIGN: A multi-pronged approach was used to assess uptake and acceptability of the guidelines and online KT resource. METHODS: Website analytics of usage and geographical location of users was measured as were physical therapist survey responses. RESULTS: Website analytics revealed that 5406 individuals used the online resource between October 2012 and September 2013 with the average visit lasting 8 minutes; only 47% of users were within the guideline developers' surgical referral region. Physical therapists who used the new shoulder guidelines were very satisfied or satisfied (96%) with the guidelines, reporting they promoted patient-specific clinical decision-making extremely or very well (68%). They viewed the online KT resource positively, with 79% rating it as "very useful" or "quite useful." Physical therapists from regions beyond those expected to use the new shoulder guidelines were also aware of the website and also rated it as very useful. LIMITATIONS: The survey sample was relatively small and did not directly assess patient outcomes. CONCLUSIONS: An online KT web resource developed in conjunction with standardized postoperative shoulder guidelines was perceived as useful based on website analytics and survey responses. Active KT strategies such as this can improve uptake and dissemination of best practice in physical therapy.

An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers.

In recent years, IoT (Internet of Things)-based smart devices have penetrated a wide range of markets, including connected health, smart home, and wearable devices. Among the IoT-based smart devices, wearable fitness trackers are the most widely diffused and adopted IoT based devices. Such devices can monitor or track the physical activity of the person wearing them. Although society has benefitted from the conveniences provided by IoT-based wearable fitness trackers, few studies have explored the factors influencing the adoption of such technology. Furthermore, one of the most prevalent issues nowadays is the large attrition rate of consumers no longer wearing their device. Consequently, this article aims to define an analytic framework that can be used to explore the factors that influence the adoption of IoT-based wearable fitness trackers. In this article, the constructs for evaluating these factors will be explored by reviewing extant studies and theories. Then, these constructs are further evaluated based on experts' consensus using the modified Delphi method. Based on the opinions of experts, the analytic framework for deriving an influence relationship map (IRM) is derived using the decision-making trial and evaluation laboratory (DEMATEL). Finally, based on the IRM, the behaviors adopted by mass customers toward IoT-based wearable fitness trackers are confirmed using the partial least squares (PLS) structural equation model (SEM) approach. The proposed analytic framework that integrates the DEMATEL and PLS-SEM was verified as being a feasible research area by empirical validation that was based on opinions provided by both Taiwanese experts and mass customers. The proposed analytic method can be used in future studies of technology marketing and consumer behaviors.