ABSTRACT
The deployment of Internet of Things platforms as well as the use of mobile and wireless technologies to support healthcare environments have enormous potential to transform healthcare. This has also led to a desire to make eHealth and mHealth part of national healthcare systems. The COVID-19 pandemic has accelerated the requirement to do this to reduce the number of patients needing to attend hospitals and General Practitioner surgeries. This direction, however, has resulted in a renewed need to look at security of future healthcare platforms including information and data security as well as network and cyber-physical security. There have been security frameworks that were developed to address such issues. However, it is necessary to develop a security framework with a combination of security mechanisms that can be used to provide all the essential security requirements for healthcare systems. In addition, there is now a need to move from frameworks to prototypes which is the focus of this paper. Several security frameworks for eHealth and mHealth are first examined. This leads to a new reference model from which an implementation framework is developed using new mechanisms such as Capabilities, Secure Remote Procedure Calls, and a Service Management Framework. The prototype is then evaluated against practical security requirements.
ABSTRACT
The latest 5G technology is being introduced the Internet of Things (IoT) Era. The study aims to focus the 5G technology and the current healthcare challenges as well as to highlight 5G based solutions that can handle the COVID-19 issues in different arenas. This paper provides a comprehensive review of 5G technology with the integration of other digital technologies (like AI and machine learning, IoT objects, big data analytics, cloud computing, robotic technology, and other digital platforms) in emerging healthcare applications. From the literature, it is clear that the promising aspects of 5G (such as super-high speed, high throughput, low latency) have a prospect in healthcare advancement. Now healthcare is being adopted 5G-based technologies to aid improved health services, more effective medical research, enhanced quality of life, better experiences of medical professionals and patients in anywhere-anytime. This paper emphasizes the evolving roles of 5G technology for handling the epidemiological challenges. The study also discusses various technological challenges and prospective for developing 5G powered healthcare solutions. Further works will incorporate more studies on how to expand 5G-based digital society as well as to resolve the issues of safety-security-privacy and availability-accessibility-integrity in future health crises.
ABSTRACT
In order to design effective public health policies to combat the COVID-19 pandemic, local governments and organizations must be able to forecast the expected number of cases in their area. Although researchers have developed individual models for predicting COVID-19 based on sensor data without requiring a test, less research has been conducted on how to leverage those individual predictions in forecasting virus spread for determining hierarchical predictions from the community level to the state level. The multilevel adaptive and dynamic biosensor epidemic model, or m-ADBio, is designed to improve on the traditional susceptible–exposed–infectious–recovered (SEIR) model used to forecast the spread of COVID-19. In this study, the predictive performance of m-ADBio is examined at the state, county, and community levels through numerical experimentation. We find that the model improves over SEIR at all levels, but especially at the community level, where the m-ADBio model with sensor-based initial values yielded no statistically significant difference between the forecasted cases and the true observed data meaning that the model was highly accurate. Therefore, the m-ADBio model is expected to provide a more timely and accurate forecast to help policymakers optimize the pandemic management strategy.