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Many investigations are going on in monitoring, contact tracing, predicting and diagnosing the COVID-19 disease and many virologists are urgently seeking to create a vaccine as early as possible. Even though there is no specific treatment for the pandemic disease, the world is now struggling to control the spread by implementing the lockdown worldwide and giving awareness to the people to wear masks and use sanitizers. The new technologies, including the Internet of things (IoT), are gaining global attention towards the increasing technical support in health-care systems, particularly in predicting, detecting, preventing and monitoring of most of the infectious diseases. Similarly, it also helps in fighting against COVID-19 by monitoring, contract tracing and detecting the COVID-19 pandemic by connection with the IoT-based smart solutions. IoT is the interconnected Web of smart devices, sensors, actuators and data, which are collected in the raw form and transmitted through the internet. The purpose of this paper is to propose the concept to detect and monitor the asymptotic patients using IoT-based sensors.

In recent days, the surge of the COVID-19 contagion has infected all over the world and it has ruined our day-to-day life. The extraordinary eruption of this pandemic virus placed the World Health Organization (WHO) in a hazardous position. The impact of this contagious virus and scarcity among the people has forced the world to get into complete lockdown, as the number of laboratory-confirmed cases is increasing in millions all over the world as per the records of the government.

COVID-19 patients are either symptomatic or asymptotic. Symptomatic patients have symptoms such as fever, cough and difficulty in breathing. But patients are also asymptotic, which is very difficult to detect and monitor by isolating them.

Asymptotic patients are very hazardous because without knowing that they are infected, they might spread the infection to others, also asymptotic patients might be having very serious lung damage. So, earlier prediction and monitoring of asymptotic patients are mandatory to save their life and prevent them from spreading.

This paper aims to outline the results of a study of the potential use of sensor technology such as radio frequency identification (RFID) and/or ZigBee technology in providing real-time tracking and tracing of patients and equipment in hospitals. The government of Saudi Arabia has given high priority to providing the best practice in patients’ care. However, the growing requirement of the healthcare industry to obtain real-time information and data from various applications that can improve the performance and accuracy of management systems has not been addressed seriously in Saudi Arabia.

ZigBee and RFID are both emerging technologies and have become important topics in recent years. RFID technology is a non-contact identification technology that does not require direct eyesight to the target object. It is cheap and reliable, but its coverage zone is limited. ZigBee is another communication technology, which has a larger coverage and can also be used as an automatic identification technology with the benefits of lower power consumption.

This paper proposes a smart hospital management system that can be used to detect, locate and monitor patients and track assets and equipment using modern sensor technologies in a real-time environment for e-health systems in Saudi Arabia.

A novel management information system/knowledge management system framework based on sensor technologies for supporting and speeding up development of healthcare systems.

Describes the authority′s strategy, recording system, visiting programme, and guide to monitoring. Describes four developments in detail which South Lincolnshire′s review of its quality monitoring approach has stimulated. The strategy identifies three levels of monitoring activity: an overview, a means of identifying when closer monitoring is indicated, and causes for concern; a selective view, a means of assessing the severity of causes for concern; and an investigative view, to examine and identify solutions to confirmed problems. Explains how the strategy identifies corporate responsibility for quality monitoring, and how this may be achieved; how the “monitoring matrix” enables a comparative overview of each provider′s compliance to purchaser standards. An up‐to‐date record of progress on individual standards is constantly available. Quality monitoring visiting can be hit or miss. The South Lincolnshire approach attempts to minimize this through the management of the visit and the use of a pocket guide to monitoring. The guide′s objective is to provide a practical guide to monitoring. An attempt has also been made to unveil some of the mystique surrounding quality.

The application of pervasive systems to healthcare has increased in recent years, but resistance to such systems by patients remains high. In this study, the aim is to examine patient and caregiver perceptions of this technology to further develop an understanding of the benefits and functionalities that prospective patients deem as desirable, undesirable, inadequate or in need of further development. The study was conducted as part of the European Union BraveHealth project which is developing a patient‐centred pervasive healthcare system to support cardiac patients at home in everyday life using innovative monitoring and diagnosis, thereby enabling the patient to be more proactive in health management.

Focus group studies were conducted in Italy and the Midlands area of the UK, along with a 31‐item questionnaire. The findings were categorized under seven main headings: personal profile; benefits; adoption; acceptance; risks; security, privacy and trust; and (use of) cell phone.

In the focus group study, most participants felt that there is a great future for this technology and showed positive response to the potential benefits but there are concerns over reliability, security, privacy and trust.

Even though this study constitutes only a small group of participants, the Italian and UK study does represent similar patients' and caregivers perceptions towards at‐home healthcare systems.

This paper contributes to the understanding of the benefits and functionalities that prospective patients and care‐givers deem as either desirable or undesirable.

Primary care practitioners in the UK today undertake more responsibility for the management of chronic diseases than ever before, including the monitoring of medications initiated in the secondary care setting. This has not necessarily been accompanied by the introduction of guidelines or additional funding. Examining the aminosalicylate group of drugs (sulfasalazine, mesalazine, olsalazine and balsalazide), it was found that despite their potential to cause life‐threatening adverse reactions, there is no agreed protocol on the most appropriate type and frequency of monitoring. A search of the literature confirmed that there is a paucity of evidence from which to construct a guideline. An audit of one family practice suggests current levels fall short of a minimal standard. Based on the current best available evidence, a protocol is suggested for aminosalicylate monitoring. Other groups of drugs warrant similar attention in primary care, and issues regarding funding for the responsibility and cost of monitoring need addressing.

The purpose of this paper is to ensure the anonymity and security of health data and improve the integrity and authenticity among patients, doctors and insurance providers. Simulation and validation algorithms are proposed in this work to ensure the proper implementation of the distributed system to secure and manage healthcare data. The author also aims to examine the methodology of Wireless Body Area Networks and how it contributes to the health monitoring system.

Wireless Body Area Network (WBAN) plays an important role in patient health data monitoring. In this paper, a novel framework is designed and proposed to generate data by the sensor machines and be stored in the cloud, and the transactions can be secured by blockchain. DNA cryptography is used in the framework to encrypt the hashes of the blocks. The proposed framework will ensure the anonymity and security of the health data and improve the integrity and authenticity among the patients, doctors and insurance providers.

Cloud Computing and Distributed Networking have transformed the IT industry and their amalgamation with intelligent systems would revolutionize the Healthcare Industry. The data being generated by devices is huge and storing it in the cloud environment would be a better decision. However, the privacy and security of healthcare data are still a concern because medical data is very confidential and desires to be safe and secure. The blockchain is a promising distributed network that ensures the security aspect of the data and makes the transactions authentic and transparent. In this work, the data is collected using various sensor devices and is transmitted to the cloud through the WBAN via the blockchain network.

In this paper, a framework for securing and managing the healthcare data generated by intelligent systems is proposed. As the data generated by these devices are heterogeneous and huge in nature, the cloud environment is chosen for its storage and analysis. Therefore, the transactions to and from the cloud are secured by using the blockchain-based distributed network.

The target end-users of our system are the patients to keep themselves informed and healthy, healthcare providers to monitor the conditions of their patients virtually, and the health insurance providers to have a track of the history of the patients, so that no fraudulent claims can be made.

The target end-users of our system are the patients for keeping themselves informed and healthy, healthcare providers for monitoring the conditions of their patients virtually and the health insurance providers to have a track of the history of the patients, so that no fraudulent claims can be made.

The present study aims to summarize different non-invasive techniques for continuous glucose monitoring (CGM) in diabetic patients using glucose-oxidase biosensors. In diabetic patients, the self-monitoring of blood glucose (BG) levels through minimally invasive techniques provides a quick method of measuring their BG concentration, unlike conventional laboratory measurements. The drawbacks of minimally invasive techniques include physical pain, anxiety and reduced patient compliance. To overcome these limitations, researchers shifted their attention towards the development of a pain-free and non-invasive glucose monitoring system, which showed encouraging results.

This study reviews the development of minimally and non-invasive method for continuous glucose level monitoring in diabetic or hyperglycemic patients. Specifically, glucose monitoring using non-invasive techniques, such as spectroscopy-based methods, polarimetry, fluorescence, electromagnetic variations, transdermal extraction-based methods and using body fluids, has been discussed. The various strategies adopted for improving the overall specificity and performance of biosensors are discussed.

In conclusion, the technology of glucose oxidase-based biosensors for glucose level monitoring is becoming a strong competitor, probably because of high specificity and selectivity, low cost and increased patient compliance. Many industries currently working in this field include Google, Novartis and Microsoft, which demonstrates the significance and strong market potential of self-monitored glucose-oxidase-based biosensors in the near future.

This review paper summarizes comprehensive strategies for continuous glucose monitoring (CGM) in diabetic patients using non-invasive glucose-oxidase biosensors. Non-invasive techniques received significant research interest because of high sensitivity and better patient compliance, unlike invasive ones. Although the results from these innovative devices require frequent calibration against direct BG data, they might be a preferable candidate for future CGM. However, the challenges associated with designing accurate level sensors to biomonitor BG data easily and painlessly needs to be addressed.

The purpose of this study is to plan and develop a cost-effective health-care robot for assisting and observing the patients in an accurate and effective way during pandemic situation like COVID-19. The purposed research work can help in better management of pandemic situations in rural areas as well as developing countries where medical facility is not easily available.

It becomes very difficult for the medical staff to have a continuous check on patient’s condition in terms of symptoms and critical parameters during pandemic situations. For dealing with these situations, a service mobile robot with multiple sensors for measuring patients bodily indicators has been proposed and the prototype for the same has been developed that can monitor and aid the patient using the robotic arm. The fuzzy controller has also been incorporated with the mobile robot through which decisions on patient monitoring can be taken automatically. Mamdani implication method has been utilized for formulating mathematical expression of M number of “if and then condition based rules” with defined input X_j (j = 1, 2, ………. s), and output y_i. The inputs and output variables are formed by the membership functions µ_Aij(x_j) and µ_Ci(y_i) to execute the Fuzzy Inference System controller. Here, Aij and Ci are the developed fuzzy sets.

The fuzzy-based prediction model has been tested with the output of medicines for the initial 27 runs and was validated by the correlation of predicted and actual values. The correlation coefficient has been found to be 0.989 with a mean square error value of 0.000174, signifying a strong relationship between the predicted values and the actual values. The proposed research work can handle multiple tasks like online consulting, continuous patient condition monitoring in general wards and ICUs, telemedicine services, hospital waste disposal and providing service to patients at regular time intervals.

The novelty of the proposed research work lies in the integration of artificial intelligence techniques like fuzzy logic with the multi-sensor-based service robot for easy decision-making and continuous patient monitoring in hospitals in rural areas and to reduce the work stress on medical staff during pandemic situation.

The areas of patient care and satisfaction are focused on. A patient satisfaction monitoring and management programme is described within a multi‐hospital system in North Central United States. The programme was set up as the core of a comprehensive system for continuous quality improvement at all levels in the organisation. The concept of patient satisfaction management is defined; the dimensions of clinical and patient satisfaction are balanced; the critical success factors are assessed, and the future challenges of broadening the programme into a system of continuous quality improvement are summarised.

Expert knowledge is an important organisational resource, and organisations need to retain the knowledge learned by experience, which can be shared as part of inter-professional learning. In a healthcare context, radio-frequency identification (RFID) and ZigBee technologies can be used together, to provide real-time information for decision support and to create a secure and reliable smart hospital management information system (SHMIS) that allows the dynamic control of objects and transforms operational processes, while minimising any potential risks to patients and staff. Currently, the RFID technology in Saudi Arabia is being solely used for the monitoring of newborn infants, and some difficulties have been encountered during the different stages of tagging and monitoring. The current system in Medina Maternity and Children’s Hospital (MMCH) uses battery-powered active RFID tags, which are expensive and require routine maintenance. This study aims to discuss the way in which the MMCH in Medina, Saudi Arabia, could be transformed into an SHMIS.

The extraordinary growth of RFID and ZigBee technologies has made it possible to identify, locate and track objects in various environments in real time. The RFID technology is a non-contact identification technology that is cheap and reliable but has limited range in the case of passive tags. ZigBee has greater range and lower power consumption, giving more precise location of the object’s movements (0.6 m). Passive RFID when combined with ZigBee technology can be used to improve services provided by healthcare organisations through continuous data collection and supporting real-time decision-making, by applying expert knowledge of domain experts to data produced by communication from electronic and sensor technologies.

A prototype object-tracking system using RFID and ZigBee was developed to support the knowledge transformation for knowledge reasoning for decision support (KRDS), and the outcome of this research was validated with domain experts in hospitals in Saudi Arabia. Two feasibility case studies were conducted at MMCH in Saudi Arabia, to evaluate the proposed system. A survey was also conducted to address the requirements at MMCH, and the researcher adopted a range of strategy techniques, including interviews and meetings with staff, and the setting up of communities of practise (CoPs) at the target hospital.

This paper has investigated the transformation process of an automatic healthcare tracking and monitoring systems for the purpose of developing a smart system in Saudi hospitals. For the scope of the project, the prototype implementation was restricted to a laboratory environment, to demonstrate the proposed proof of concept. The next phase will include conducting a scale up of the system, with implementation and testing done in a real hospital environment.

This paper proposes a prototype application of an (SHMIS that allows the dynamic control of objects and transforms operational processes, while minimising any potential risks to patients and staff.