Internet of Things Concept in the Context of the COVID-19 Pandemic: A Multi-Sensor Application Design

ScalableDigitalHealth (SDH): An IoT-Based Scalable Framework for Remote Patient Monitoring

Addressing the increasing demand for remote patient monitoring, especially among the elderly and mobility-impaired, this study proposes the "ScalableDigitalHealth" (SDH) framework. The framework integrates smart digital health solutions with latency-aware edge computing autoscaling, providing a novel approach to remote patient monitoring. By leveraging IoT technology and application autoscaling, the "SDH" enables the real-time tracking of critical health parameters, such as ECG, body temperature, blood pressure, and oxygen saturation. These vital metrics are efficiently transmitted in real time to AWS cloud storage through a layered networking architecture. The contributions are two-fold: (1) establishing real-time remote patient monitoring and (2) developing a scalable architecture that features latency-aware horizontal pod autoscaling for containerized healthcare applications. The architecture incorporates a scalable IoT-based architecture and an innovative microservice autoscaling strategy in edge computing, driven by dynamic latency thresholds and enhanced by the integration of custom metrics. This work ensures heightened accessibility, cost-efficiency, and rapid responsiveness to patient needs, marking a significant leap forward in the field. By dynamically adjusting pod numbers based on latency, the system optimizes system responsiveness, particularly in edge computing's proximity-based processing. This innovative fusion of technologies not only revolutionizes remote healthcare delivery but also enhances Kubernetes performance, preventing unresponsiveness during high usage.

A Systematic Literature Review on Trustworthiness for Applications Used in eHealth Environments

Context

The technological advancement of the Internet of Things (IoT) creates opportunities in various social sectors. Patients in clinics or home care have their comfort and safety enhanced with remote monitoring, sensors and applications that control and transfer patient data. These applications must be trustworthy, since they deal with sensitive data.

Purpose

The purpose of this work is to identify gaps in trustworthiness, availability, effectiveness, security and other attributes. Also, to highlight challenges and opportunities for research and give guidance on choosing the right technology or application based on the resources available to support patients and doctors, protocol of communication and maturity level of these technologies.

Methodology

This work presents a systematic review of the literature following four steps: Definition of the Research Questions, Conduct Search, Screening of Papers, and Data Extraction and Mapping Process.

Results

Based on the articles studied, it was possible to answer important questions about eHealth applications. The results highlight how eHealth applications can enhance patient care by monitoring health data and supporting doctors' decision-making with a reasonable level of trustworthiness. Additionally, the results demonstrate how applications can notify external caregivers in emergencies and assist in diagnosis and treatment of illnesses. However, these applications still face problems related to sensor lifetime, medical data sharing, interoperability and lack of standardization. Finally, we suggest a literature mapping to support the choice of technologies based on resources available, communication protocol and technological maturity.

Conclusion

This work carries out a systematic literature review to discuss state-of-the-art eHealth applications and gather new information of current research. In this process it was possible to show how these applications work, map out their main technological characteristics to assist the decision-making process for future works and uncover eHealth applications' strengths, future perspectives and challenges, specifically related to the high level of trustworthiness necessary.

Massive Data Storage Solution for IoT Devices Using Blockchain Technologies

The Internet of Things (IoT) concept involves connecting devices to the internet and forming a network of objects that can collect information from the environment without human intervention. Although the IoT concept offers some advantages, it also has some issues that are associated with cyber security risks, such as the lack of detection of malicious wireless sensor network (WSN) nodes, lack of fault tolerance, weak authorization, and authentication of nodes, and the insecure management of received data from IoT devices. Considering the cybersecurity issues of IoT devices, there is an urgent need of finding new solutions that can increase the security level of WSNs. One issue that needs attention is the secure management and data storage for IoT devices. Most of the current solutions are based on systems that operate in a centralized manner, ecosystems that are easy to tamper with and provide no records regarding the traceability of the data collected from the sensors. In this paper, we propose an architecture based on blockchain technology for securing and managing data collected from IoT devices. By implementing blockchain technology, we provide a distributed data storage architecture, thus eliminating the need for a centralized network topology using blockchain advantages such as immutability, decentralization, distributivity, enhanced security, transparency, instant traceability, and increased efficiency through automation. From the obtained results, the proposed architecture ensures a high level of performance and can be used as a scalable, massive data storage solution for IoT devices using blockchain technologies. New WSN communication protocols can be easily enrolled in our data storage blockchain architecture without the need for retrofitting, as our system does not depend on any specific communication protocol and can be applied to any IoT application.

The Design and Development of a Microstrip Antenna for Internet of Things Applications

The Internet of Things (IoT) has become a part of modern life where it is used for data acquisition and long-range wireless communications. Regardless of the IoT application profile, every wireless communication transmission is enabled by highly efficient antennas. The role of the antenna is thus very important and must not be neglected. Considering the high demand of IoT applications, there is a constant need to improve antenna technologies, including new antenna designs, in order to increase the performance level of WSNs (Wireless Sensor Networks) and enhance their efficiency by enabling a long range and a low error-rate communication link. This paper proposes a new antenna design that is able to increase the performance level of IoT applications by means of an original design. The antenna was designed, simulated, tested, and evaluated in a real operating scenario. From the obtained results, it ensured a high level of performance and can be used in IoT applications specific to the 868 MHz frequency band.By inserting two notches along x axis, we find an optimal structure of the microstrip patch antenna with a reflection coefficient of -34.3 dB and a bandwidth of 20 MHz. After testing the designed novel antenna in real IoT operating conditions, we concluded that the proposed antenna can increase the performance level of IoT wireless communications.

An IoT-Based Wristband for Automatic People Tracking, Contact Tracing and Geofencing for COVID-19

The coronavirus disease (COVID-19) pandemic has triggered a huge transformation in the use of existing technologies. Many innovations have been made in the field of contact tracing and tracking. However, studies have shown that there is no holistic system that integrates the overall process from data collection to the proper analysis of the data and actions corresponding to the results. It is critical to identify any contact with infected people and to ensure that they do not interact with others. In this research, we propose an IoT-based system that provides automatic tracking and contact tracing of people using radio frequency identification (RFID) and a global positioning system (GPS)-enabled wristband. Additionally, the proposed system defines virtual boundaries for individuals using geofencing technology to effectively monitor and keep track of infected people. Furthermore, the developed system offers robust and modular data collection, authentication through a fingerprint scanner, and real-time database management, and it communicates the health status of the individuals to appropriate authorities. The validation results prove that the proposed system identifies infected people and curbs the spread of the virus inside organizations and workplaces.

Electronic Surveillance in Court Proceedings and in the Execution of Criminal Penalties: Legislative and Logistical Steps Regarding Operationalising the Electronic Monitoring Information System (EMIS) in Romania

The latest innovations in the field of electronics and telecommunications have revolutionised and brought new dimensions to human activities. As well as in other sectors, we observe that a wide range of electronic means have also shown their utility in criminal justice. Undergoing continuous development, these means ensure efficient monitoring of subjects and contribute to higher efficiency of judiciary systems, and provide “more humane” conditions compared with traditional incarceration for offenders when they execute criminal penalties. In this context, this study discussed the main challenges faced by Romania in implementing electronic monitoring (EM) devices in court proceedings and in the execution of criminal penalties. These have been researched from different perspectives, including those related to the current legal framework, opportunities provided by today’s developments in electronics, and in terms of financial public resources allocated for such purposes. Our study is among the few articles published on this topic and it brings to light both the advantages of introducing the Electronic Monitoring Information System (EMIS) in Romania, as well as the limitations, and overviews the international experience in this area by assessing the measures that have been taken so far worldwide to implement EMIS effectively. The final part of the paper presents the study conclusions, its limitations, and future lines of research.

Individual Factors Associated With COVID-19 Infection: A Machine Learning Study

The fast, exponential increase of COVID-19 infections and their catastrophic effects on patients' health have required the development of tools that support health systems in the quick and efficient diagnosis and prognosis of this disease. In this context, the present study aims to identify the potential factors associated with COVID-19 infections, applying machine learning techniques, particularly random forest, chi-squared, xgboost, and rpart for feature selection; ROSE and SMOTE were used as resampling methods due to the existence of class imbalance. Similarly, machine and deep learning algorithms such as support vector machines, C4.5, random forest, rpart, and deep neural networks were explored during the train/test phase to select the best prediction model. The dataset used in this study contains clinical data, anthropometric measurements, and other health parameters related to smoking habits, alcohol consumption, quality of sleep, physical activity, and health status during confinement due to the pandemic associated with COVID-19. The results showed that the XGBoost model got the best features associated with COVID-19 infection, and random forest approximated the best predictive model with a balanced accuracy of 90.41% using SMOTE as a resampling technique. The model with the best performance provides a tool to help prevent contracting SARS-CoV-2 since the variables with the highest risk factor are detected, and some of them are, to a certain extent controllable.

Antenna Systems in Medical Masks: Applications for 5G FR1 and Wi-Fi 7 Wireless Systems

This paper proposes a small antenna system (47 mm × 8 mm × 0.2 mm) to be used in a medical mask. The medical mask is composed of a frame and shield. The frame is made of polycarbonate (PC), and the shield is made of polyethylene terephthalate (PET). The author sets two groups of antennas on the upper side of the frame and sets two other groups of antennas on the sides facing away from the face of the shield. The substrates of the four antennas are all FR4 (εr = 4.4, tanδ = 0.02), so the first antenna type is a combination of PC and FR4, and the second antenna type is a combination of PET and FR4. The antenna system has three working frequency bands, in which the reflection coefficient is lower than −10 dB after actual measurement, and its working frequency bandwidth is 2.38–2.62 GHz, 3.38–3.74 GHz, and 5.14–8 GHz, respectively. It can be effectively used in 5G FR1 and Wi-Fi 7 frequency bands and can easily be combined with medical masks of different materials. This antenna system can use Wi-Fi 7 for wireless transmission indoors and use the 5G FR1 frequency band for wireless transmission outdoors, achieving seamless transmission capabilities.

Contact-Free Operation of Epidemic Prevention Elevator for Buildings

The COVID-19 pandemic broke out in early 2020, and the infection rate of COVID-19 variants is considerably higher than that of the original virus. The pandemic is still spreading globally. In June 2021, two families living on different floors of a building in Fongshan, Kaohsiung, were simultaneously infected with COVID-19. Investigation results suggested that an elevator in buildings was the most likely place where the virus transmission occurred. Building elevators are a necessary vertical transportation facility for residents or workers in high-rise buildings, and people touch elevator buttons while operating elevators. When a passenger carrying the virus touches elevator buttons, subsequent passengers may be easily infected if they touch those buttons and then touch their mouth, eyes, or nose by accident before sanitizing or washing their hands. In this study, we developed a contact-free elevator ride system by applying smart speech recognition, contact-free perceptual buttons, gesture recognition sensors, and a web page browser activated by quick response codes to operate an elevator. This system reduces the risk of virus infection caused by contact during an elevator ride, effectively enhancing pandemic prevention and protecting people’s health.