This paper aims to comprehensively review 891 documents in the Scopus database about Internet of Things (IoT) in Ind 4.0 to understand the historical growth, current state, and potential expansion trend. From 2014 to 2020, a systematic methodology gathered information on IoT in Ind 4.0 documents in various Scopus databases. The relevant IoT research in Ind 4.0 documents is provided, and their types, publications, citations, and predictions are discussed. The VOSviewer 1.16.6 and Biblioshiny 2.0 applications display IoT status in Ind 4.0 publications for visualization research. The citation review aims to find the most prominent and influential authors, sources, papers, countries, and organizations. For citation analysis and ranking, document selection criteria were well defined. The author keywords, index keywords, and text data content analysis were used to identify the hotspots and development trends. The yearly IoT in Ind 4.0 article publications presented a speedily increasing trend, and a curve was fitted employing an exponential function. The paper “Intelligent manufacturing in the context of Industry 4.0: a review” was rated first with 754 citations. With 1629 citations, the “International Journal of Production Research” was ranked #1 along with Wan J. The South China University of Technology in Guangzhou, China, was placed first along with the United States as the most prolific and influential country. ‘Industry 4.0’ appeared the first time in 2014 with an application of IoT in Ind 4.0 with an overall appearance of 528, followed by the ‘internet of things’ in 2015, three times with a total count of 220 up to 2020. The IoT in Ind 4.0 assessment and bibliometric analysis intended to provide intellectuals a broad perspective working in IoT in Ind 4.0. Scholars should understand the hotspots in this area as soon as possible. This is also the first paper to thoroughly use bibliometric research to examine the IoT in Ind 4.0 literature. It will assist researchers of IoT in Ind 4.0 in expanding their knowledge and quickly comprehending the development status and pattern.

To achieve greater sustainability of the traffic system, the trend of traffic accidents in road traffic was analysed. Injuries from traffic accidents are among the leading factors in the suffering of people around the world. Injuries from road traffic accidents are predicted to be the third leading factor contributing to human deaths. Road traffic accidents have decreased in most countries during the last decade because of the Decade of Action for Road Safety 2011–2020. The main reasons behind the reduction of traffic accidents are improvements in the construction of vehicles and roads, the training and education of drivers, and advances in medical technology and medical care. The primary objective of this paper is to investigate the pattern in the time series of traffic accidents in the city of Belgrade. Time series have been analysed using exploratory data analysis to describe and understand the data, the method of regression and the Box–Jenkins seasonal autoregressive integrated moving average model (SARIMA). The study found that the time series has a pronounced seasonal character. The model presented in the paper has a mean absolute percentage error (MAPE) of 5.22% and can be seen as an indicator that the prognosis is acceptably accurate. The forecasting, in the context of number of a traffic accidents, may be a strategy to achieve different goals such as traffic safety campaigns, traffic safety strategies and action plans to achieve the objectives defined in traffic safety strategies.

Today’s patients are more informed and quality-conscious than ever before, which is crucial for healthcare practitioners as they interact with people’s lives daily. One of the most important challenges facing the healthcare sector worldwide concerns how to improve the overall quality of hospital care. As a result of the highly competitive nature of the economy in which healthcare services are offered, both public and private hospitals in Saudi Arabia must have their patient satisfaction rates assessed to help consumers make more informed decisions. As a result, we used the analytical hierarchy process (AHP) model to ascertain how patients in Saudi Arabia perceive the quality of the service that is provided by hospitals. The objective of the research work is to identify criteria for enhancing healthcare services using the analytic hierarchy process (AHP) technique to model the five SERVQUAL dimensions along with 2 dimensions and 31 sub-criteria. Three healthcare service organizations were selected for the study and evaluated based on their service quality performance. The AHP-based model has been demonstrated systematically for ranking the hospitals based on the healthcare system. It is observed that hospitals should concentrate the most on reliability, tangibles, and security and the least on consistency. In addition, according to the sub-criteria, the hospitals’ primary priority should be infection prevention and hygiene, with completeness receiving the least attention. Based on a survey of dimensions and their sub-criteria, the best hospital is Abha Private Hospital, followed by AHH, and then Asir General Hospital. Therefore, this study has implications for choices on the efficient monitoring of the overall health system to improve quality service delivery that would boost patient happiness, which is the goal of creating hospitals.

The use of carbon fiber reinforced plastic (CFRP) is increasing in engineering applications such as aerospace, automobiles, defense, and construction. Excellent strength-to-weight ratio, high impact toughness, and corrosion resistance make CFRP highly suitable for aerospace applications. Curing temperature, curing time, and autoclave pressure are among the most important curing parameters affecting the properties of CFRP. Tensile strength, impact toughness, and hardness of CFRP were selected as desirable properties for optimization. A 23 full factorial design of experiment (DOE) was employed by varying curing temperature (120 and 140 °C), curing time (90 and 120 min), and autoclave pressure (3 and 7 bar) while keeping the number of experiments to a minimum level. The cured samples were subjected to tensile strength, impact toughness, and hardness tests at room temperature as per relevant ASTM standards. Analysis of variance (ANOVA) was used, and it was found that tensile strength, impact toughness, and hardness were influenced most significantly by temperature and time. The maximum tensile strength and hardness were achieved for curing cycle parameters of 140 °C, 120 min, and 7 bar, and impact toughness was maximized for 140 °C, 120 min, and 3 bar. A concept of composite desirability function was used to achieve simultaneous optimization of conflicting tensile strength and impact toughness properties for the specific application of aircraft skin.

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