Highlights A review of COVID-19 guidelines ensures the need of disruptive technologies. COVID-19 enforces healthcare system to find alternatives for patients' treatment. The disruptive technologies used to analyze and to restrict the spread of COVID-19. The study aids healthcare team to detect the plan of treatment remotely and safely. The analysis of COVID-19 patients ensures the importance of intelligent framework.

The Internet of Things (IoT) connects billions of devices to afford inventive opportunities between things and people. The rapid development of products related to the IoT is a new challenge to keep security issues, lack of confidence, and understanding of the IoT. Analytical hierarchy process (AHP) is a classic multi-criteria decision making (MCDM) method used to analyze and scale complex problems and to obtain weights for the selected criteria. The vague and inconsistent information in real situations can lead to the decision maker's confusion. The decision makers cannot determine accurate judgments for all situations due to the conditions of uncertainty factors in real life; in addition to the limited knowledge and experience of decision makers. In this research, we present a neutrosophic AHP of the IoT in enterprises to help decision makers to estimate the influential factors. The estimation of influential factors can affect the success of the IoT-related enterprise. This study combines AHP methods with neutrosophic techniques to effectively present the criteria related to influential factors. The recommended alternatives are presented based on neutrosophic techniques satisfying the estimated influential factors for a successful enterprise. A case study is applied in Smart Village, Cairo, Egypt, to show the applicability of the proposed model. The smart village' consistency rate is measured after applying neutrosophic methodologies to reach to nearest optimum results. Additional case studies on the smart city in the U.K. and China have been presented to justify that our proposal can be used and replicated in different environments.INDEX TERMS Multi-criteria decision making (MCDM), analytical hierarchal Process (AHP), neutrosophic sets, Internet of Things (IoT).

Personnel selection is a critical obstacle that influences the success of the enterprise. The complexity of personnel selection is to determine efficiently the proper applicantion to fulfill enterprise requirements. The decision makers do their best to match enterprise requirements with the most suitable applicant. Unfortunately, the numerous criterions, alternatives, and goals make the process of choosing among several applicants is very complex and confusing to decision making. The environment of decision making is a multi-criteria decision making surrounded by inconsistency and uncertainty. This paper contributes to support personnel selection process by integrating neutrosophic analytical hierarchy process (AHP) with the technique for order preference by similarity to an ideal solution (TOPSIS) to illustrate an ideal solution amongst different alternatives. A case study on smart village Cairo Egypt is developed based on decision maker's judgments recommendations. The proposed study applies neutrosophic AHP and TOPSIS to enhance the traditional methods of personnel selection to achieve the ideal solutions. By reaching the ideal solutions, the smart village will enhance the resource management for attaining the goals to be a successful enterprise. The proposed method demonstrates a great impact on the personnel selection process rather than the traditional decision-making methods.

The development of economic activities and social progress index leads to the governmental considerations for the environmental challenge's issues. The Green Credit Policy (GCP) in China for manufacturing, as a part of a sustainable finance package, initiatives restrictions with suppliers to reduce harmful pollution for the environment. The study mainly validates the impact of GCP on manufacturing for diminishing the emerged pollution to the environment. The study develops Neutrosophic Multiple-Criteria Decision-Making Framework (N-MCDMF) according to neutrosophic theory and various MCDM methods of grey relational analysis (GRA), analytic network process (ANP), the Decision-Making Trial and Evaluation Laboratory technique (DEMATEL), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to support the decision-makers with highly systematic procedures in the uncertain and inconsistent environmental conditions. The N-MCDMF evaluates the conditions of GCP and recommends the optimal Supply Chain Management (SCM) in manufacturing alternatives. A case study is presented for the validation of the issues of applicability and flexibility for the proposed N-MCDMF. The results obtained from the implementation of the N-MCDMF indicates the applicability and flexibility of the proposed approach. In addition, results show that SCM in manufacturing can provide more cooperation for the environment to reduce harmful pollution and to attain sustainability for achieving motivations under the restrictions of GCP.

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A blockchain, as a form of distributed ledger technology, represents the unanimity of replication, synchronization, and sharing of data among various geographical sites. Blockchains have demonstrated impressive and effective applications throughout many aspects of the business. Blockchain technology can lead to the advent of the construction of Digital Twins (DTs). DTs involve the real representation of physical devices digitally as a virtual representation of both elements and dynamics prior to the building and deployment of actual devices. DT products can be built using blockchain-based technology in order to achieve sustainability. The technology of DT is one of the emerging novel technologies of Industry 4.0, along with artificial intelligence (AI) and the Internet of Things (IoT). Therefore, the present study adopts intelligent decision-making techniques to conduct a biased analysis of the drivers, barriers, and risks involved in applying blockchain technologies to the sustainable production of DTs. The proposed model illustrates the use of neutrosophic theory to handle the uncertain conditions of real-life situations and the indeterminate cases evolved in decision-makers’ judgments and perspectives. In addition, the model applies the analysis of Multi-criteria Decision Making (MCDM) methods through the use of ordered weighted averaging (OWA) and the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) to achieve optimal rankings for DT production providers based on consistent weighted decision-maker’s judgments in order to maintain and to assure sustainability. An empirical study is applied to the uncertain environment to aid decision-makers in achieving ideal decisions for DT providers with respect to various DT challenges, promoting sustainability and determining the best service providers. The Monte Carlo simulation method is used to illustrate, predict, and forecast the importance of the weights of decision-makers' judgments as well as the direct impact on the sustainability of DT production.

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Applications that are enabled by blockchain technology have been infused with a decentralized system without the need for intermediate entities. Blockchain technology indicates opportunities with various technologies and applications. Recently, a meteoric rise in the amount of interest has been indicated by academics in blockchain technology. Nevertheless, the acceptance of this blockchain technology paradigm in corporate distributed systems is not exactly promising. Executives and technocrats in a business are required to engage in multiple-criteria decision-making (MCDM) with operating uncertainty factors for the acceptance of new technologies. The proposed model aims to develop a model to identify and keep track of major elements that contribute to the sluggish pace for blockchain technology to be adopted by the general public. The study applied the Evaluation Based on the Distance from Average Solution (EDAS) approach to its interval-valued neutrosophic variant, which has the benefit of concurrently with the consideration of a decision maker's truthiness, falsity, and indeterminacy. The EDAS considers the distances of alternatives from the actual solutions considered by each criterion. In addition, the proposed model illustrated the use of neutrosophic theory with the EDAS method to rank blockchain technology in enterprise-distributed applications in uncertain conditions to aid decision-makers in optimal solutions. A numerical case study is illustrated to show the effectiveness of the proposed model in aiding decision-makers to achieve optimal solutions in uncertain conditions.