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The fourth industrial revolution and digital transformation have caused paradigm changes in the procedures of goods production and services through disruptive technologies, and they have formed new methods for business models. Health and medicine fields have been under the effect of these technology advancements. The concept of smart hospital is formed according to these technological transformations. The aim of this research, other than explanation of smart hospital components, is to present a model for evaluating a hospital readiness for becoming a smart hospital.

This research is an applied one, and has been carried out in three phases and according to design science research. Based on the previous studies, in the first phase, the components and technologies effecting a smart hospital are recognized. In the second phase, the extracted components are prioritized using type-2 fuzzy analytic hierarchical process based on the opinion of experts; later, the readiness model is designed. In the third phase, the presented model would be tested in a hospital.

The research results showed that the technologies of internet of things, robotics, artificial intelligence, radio-frequency identification as well as augmented and virtual reality had the most prominence in a smart hospital.

The innovation and originality of the forthcoming research is to explain the concept of smart hospital, to rank its components and to provide a model for evaluating the readiness of smart hospital. Contribution of this research in terms of theory explains the concept of smart hospital and in terms of application presents a model for assessing the readiness of smart hospitals.

Abundant studies of outpatient visits apply traditional recurrent neural network (RNN) approaches; more recent methods, such as the deep long short-term memory (DLSTM) model, have yet to be implemented in efforts to forecast key hospital data. Therefore, the current study aims to reports on an application of the DLSTM model to forecast multiple streams of healthcare data.

As the most advanced machine learning (ML) method, static and dynamic DLSTM models aim to forecast time-series data, such as daily patient visits. With a comparative analysis conducted in a high-level, urban Chinese hospital, this study tests the proposed DLSTM model against several widely used time-series analyses as reference models.

The empirical results show that the static DLSTM approach outperforms seasonal autoregressive integrated moving averages (SARIMA), single and multiple RNN, deep gated recurrent units (DGRU), traditional long short-term memory (LSTM) and dynamic DLSTM, with smaller mean absolute, root mean square, mean absolute percentage and root mean square percentage errors (RMSPE). In particular, static DLSTM outperforms all other models for predicting daily patient visits, the number of daily medical examinations and prescriptions.

With these results, hospitals can achieve more precise predictions of outpatient visits, medical examinations and prescriptions, which can inform hospitals' construction plans and increase the efficiency with which the hospitals manage relevant information.

To address a persistent gap in smart hospital and ML literature, this study offers evidence of the best forecasting models with a comparative analysis. The study extends predictive methods for forecasting patient visits, medical examinations and prescriptions and advances insights into smart hospitals by testing a state-of-the-art, deep learning neural network method.

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.

Facilities management (FM) activities affect citizens’ health and safety, long-term urban environmental sustainability and the relationships between the built and natural environments of cities. This study aims to comprehend the status of smart FM tools application, how they are used to improve the delivery of FM services and the barriers to their implementation.

To investigate the current smart solutions that leverage the quality of FM service, a case study based on the FM practice in Hong Kong was carried out. The case study was conducted in two phases of data acquisition based on a qualitative research methodology. After conducting in-depth interviews to determine the application of smart FM tools in different types of properties and to identify the initiatives and barriers to smart FM tool application, three workshops were conducted to validate the findings and further investigate the influence of FM professionals on smart FM tools application in Hong Kong.

The findings of the case study revealed, firstly, that four types of smart FM tools – user-centric, safety and hygiene, maintenance and sustainability-oriented – are used to assist the delivery of FM services. Secondly, smart FM tools are shown to be useful in assisting FM activities. Thirdly, the existing barriers to smart FM tool application manifest differently in shopping malls, office buildings and residential buildings. Fourthly, smart FM tools are used to address the four attributes of user needs: comfort, health and wellbeing, convenience and information to occupants.

The value of this study lies in its focus on the industry level (FM industry) and the application process of smart FM tools in different types of property, revealing the benefits, initiatives and barriers to their future application. This study provides a comprehensive picture of the current status and elaborates the barriers to smart FM tool application, which will help FM practitioners to make strategic decisions on selecting and developing smart FM tools. Also, this study will facilitate smart FM tool application policy development.

With the development of emerging engineering technology and industrialization, there are greater changes in the life style of people in smart urban cities; therefore, there is also more chance of various health problems in urban areas. The life style of persons in metro urban areas with the expansive volume of population is similarly influenced by different application and administration frameworks. These are affecting the human health system up to an extended extent and there are more health-related issues and health hazard concerns that can be identified in urban areas. The purpose of this paper is to present an analytical study on various aspects of the smart health care system in a smart perspective by analyzing them with respect to emerging engineering technologies such as mobile network, cloud computing, Internet of Things (IoT), big data analytics and ubiquitous computing. This paper also carries out a detailed survey of health issues and improved solutions in automated systems using these technologies. Second, the paper also presents a novel health care system using smart and safe ambulances and their appropriate control at traffic points with safety and security features in a smart city, so that the valuable life of patients can be saved in time by immediate treatment in nearest hospital or health care units.

In this paper, an analytical survey was conducted for improvement in the health care sector using computer technology and IoT-based various modern health care applications. An idea of Smart Health Care Hospital using sensors, mobile agent smart vehicle configuration and safety traffic control for ambulance was proposed.

A simulation was carried out to see the performance of a safety mechanism in the proposed approach. Comparative analysis was carried out with other approaches to know the execution time, response time and probable delay due to the implementation of this approach.

It is an original research work with motivation inspired from current emergent technology to apply in the health care system.

With the advancement in technology, the day-to-day life of people has gone through an immense transformation. The use of smart devices for day-to-day life is greater than before, and people are moving towards smart work rather than doing hard work. In this paper, a novel framework is proposed named Online Service Provider in Metro City (OSPMC) for IoT. The purpose of this study is to provide a theoretical framework for the E-Government in order to sustain or minimize the unemployment rate.

The utilization of the Web in the upcoming years would create further opportunities for smart work. Internet of Things (IoT) plays an essential part in a system of multiple networks that aims to connect all things in the world that are capable of being connected through the internet. OSPMC framework can be developed on ASP.NET through (visual C#) 3.0 and Microsoft SQL Server with frontend and backend languages, respectively, under a web-based environment built on .Net platform. This lucrative facility is available mainly for the people living in the smart city.

Rural people are coming to smart cities in search of jobs, better education and a healthy lifestyle. India is also coping up with the modern world. The Government of India has taken an initiative for the making of 100 smart cities where the residents are relied upon to use Information and Communication Technology with the assistance of web.

OSPMC promises to eliminate multiple evils like social injustice, crime, unemployment, tax fraud and would promote women empowerment. Also, provide opportunities to start-ups in order to grow and enhance their skill work.

The objective of OSPMC can be found useful for opening new job opportunities for urban/rural people while also encouraging people to learn skill work. For smart cities’ success in developing nations, it is important to recognize the elements influencing it. The motivation behind OSPMC is to identify those variables influencing the successful usage of allowing IoT in the smart cities by E-Government of India and to use IoT to help urban smart cities.

Delay in the clinical information system (CIS) restoration overseeing critical health-care operations after an unexpected data loss can be fatal for patients under care. Investment in information technology (IT) capabilities and synergy between various computerized systems has been argued as the resilient information system's enablers. The purpose of this study is to empirically quantify the influence of IT investment, integration and interoperability in recovering the CIS from a data disaster.

An archival dataset sourced from a European Commission-sponsored survey of 773 hospitals across 30 countries in Europe is utilized to study the relationships. The study adopts a quasi-experimental research design approach where sample observations are weighted based on their propensity to be selected in treatment groups. The artificial weighing allows attaining a pseudo-random sample to counter the effects of selection bias.

The study finds that hospitals with more than 5% of the budget dedicated to IT have 100% higher odds of recovering immediately from a critical data loss in comparison to those that have less than 1% investment in IT. The greater extent of IT integration significantly reduces the time to recover the CIS, while interoperability problems at the organizational level lessen the odds of immediate recovery by 19%. Interoperability problems at the technical and semantic levels do not significantly impact recovery times of the CIS.

The study proposes several empirically quantified and scientifically tested recommendations for health-care providers for faster restoration of critical CIS operations post data loss. The differential impact of the interoperability problems at the technical, semantic and organizational levels has also been highlighted.

The purpose of this paper is to provide a systematic literature review on the technological aspects of smart cities and to give insights about current trends, sources of research, contributing authors and countries. It is required to understand technical concepts like information technology, big data analytics, Internet of Things and blockchain needed to implement smart city models successfully.

The data were collected from the Scopus database, and analysis techniques like bibliometric analysis, network analysis and content analysis were used to obtain research trends, publications growth, top contributing authors and nations in the domain of smart cities. Also, these analytical techniques identified various fields within the literature on smart cities and supported to design a conceptual framework for Industry 4.0 adoption in a smart city.

The bibliometric analysis shows that research publications have increased significantly over the last couple of years. It has found that developing countries like China is leading the research on smart cities. The network analytics and article classification identified six domains within the literature on smart cities. A conceptual framework for the smart city has proposed for the successful implementation of Industry 4.0 technologies.

This paper explores the role of Industry 4.0 technologies in smart cities. The bibliometric data on publications from the year 2013 to 2018 were used and investigated by using advanced analytical techniques. The paper reviewS key technical concepts for the successful execution of a smart city model. It also gives an idea about various technical considerations required for the implementation of the smart city model through a conceptual framework.

Qualitative methods are not suitable to process high volumes of policy texts for exploring policy evolution. Therefore, it is hard to use qualitative methods to systematically analyze the characteristics of complex policy networks. So the authors propose a bibliometric research study for exploring policy evolution from time–agency–theme perspectives to excavate the rules and existing problems of China's medical informatization policy and to provide suggestions for formulating and improving the future medical informatization policies.

Initially, 615 valid samples are obtained by retrieving related China's medical informatization policy documents, and the joint policy-making agency network and the co-occurrence network models of medical informatization policies are defined, and then the authors research China's medical informatization policies from single-dimension and multi-dimension view.

The analysis results reveal that China's medical informatization policy process can be divided into four stages; the policy-making agencies are divided into four subgroups by community detection analysis according to the fast unfolding algorithm; the core policy theme keywords are identified based on the eigenvector centrality of the nodes in those networks; the focuses of theme terms are varied in different stages and the correlations between agencies and themes are gradually decentralized.

These findings provide experience and evidence on leveraging informatics in the medical and healthcare field of China. Also, they can help scholars and practitioners better understand the current status and future directions of medical and healthcare informatics development in China and provide a reference to formulate and improve China's future medical informatization policies.

This study proposes a quantitative bibliometric-based research framework to describe transitions and trends of China's medical informatization policy.