Exploring the Application Sphere of the Internet of Things in Industry 4.0: A Review, Bibliometric and Content Analysis

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.


Introduction
The term "Internet of Things" (IoT) was introduced by Kevin Ashton in the year 1999 [1]. However, the concept of the IoT evolved over many years. Some different definitions were proposed by various researchers from time to time [2][3][4], but significant developments in this technology have only been observed in the previous few years [5]. It is acquiring massive admiration in the era of wireless communication. In the last decade, it has garnered much attention by showcasing its aim of connecting global infrastructure by catering all time and all place connectivity [6,7] to smart objects. Another aspect of the IoT facilitates thing-thing, human-human, and human-thing connectivity by allocating a unique identification code to each device on the network [8]. Key enabling technologies for

The Implication of the State-of-Art Review
The review indicated that most studies were done in several research areas to use IoT in the Industry 4.0 approach based on a comprehensive literature assessment. However, only a few review studies in the relevant field of research were conducted during this era as per the document type choice for information obtained from the Scopus database. However, in different applications, no attempt was made to test the usefulness of the IoT technology in Industry 4.0. In addition, in the Industry 4.0 method, the current literature has not conducted a systemic IoT literature review. Thus, the study required the IoT in Ind 4.0 approach to be thoroughly analyzed. There are many bibliometric studies undertaken to highlight the importance of IoT in different fields, such as IoT and the water supply chain [40], IoT-based management in agriculture [41], IoT, cyber-physical system and smart city [42], megatrends in society [43], smart education [44], IoT and RFID [45], IoT, communication technologies in smart meters [46], IoT, digital transition and sustainability [47], actuators in a smart city [48], entropy weights [49], and technological forecasting [50]. However, the review of bibliometrics revealed that no such analysis is available covering the application of IoT in Industry 4.0. Therefore, sophisticated visualization tools are critical in IoT applications in the Industry 4.0 sector, especially when considering a systematic literature review and content analysis. Thus, the study extensively planned to examine the IoT applications in the industry 4.0 literature for six years, from 2014 to 2020.

Research Questions and Intended Contributions of the Existing Review
Keeping in mind the research gap derived from the above analysis, the study focuses on one of the essential research questions: "Do we need any Bibliometric Analysis of the Internet of Things in Industry 4.0?" The answer to this research question is yes; the extensive literature survey on IoT in Ind 4.0 has revealed an absence of a systematic analysis of IoT in Ind 4.0 frequently utilized by the academic world, industries, and research scholars. Suppose the proposed study systematically evaluated the entire literature in the form of bibliometric analysis. In that case, it will augment the overall methodical yield of IoT in Ind 4.0 and a considerate assessment of current bibliometric shreds of evidence and scrutiny of countless reasons for the diverse and multi-disciplinary practice of IoT in Ind 4.0. This will also help young researchers and users to draw valid conclusions on IoT in Ind 4.0. Therefore, the study has proceeded ahead with a positive intention to underwrite elucidated narrative reviews, a systematic review of IoT in Ind 4.0, and offer the much-needed future scope of IoT in Ind 4.0. Therefore, the study has arranged the following research objectives based on this research question.

Objectives of the Present Review
The study is based on the following research objectives based on an extensive literature review, research gap, and research questions under present investigation.
(1) To conduct an extensive bibliometric analysis of the existing literature on IoT in Ind 4.0. (2) To propose a relevant research outlook related to the application of IoT in Ind 4.0 describing its future scope.
The study has organized a comprehensive bibliometric and statistical analysis of IoT in Ind 4.0 with the help of available research tools and software discussed in the upcoming subsection. The bibliometric analysis helps users gain an exhaustive picture of the study topic of their interest. The word was invented by Alan Pritchard [51], who argued that it might be used in any study seeking to describe the texting mechanism. This type of quantitative analysis will make different investigators aware of a given subject's area, supporting them in appreciating the topic's important history, the vast diversity of progress that has been made in this field, and future study opportunities.

Research Design
The systematic mapping study used a research plan that examines the complete IoT literature on Industry 4.0 by utilizing research techniques and software well described by [52,53]. The study employed a two-stage structured approach for bibliometric analysis and graphical evaluations [54] of the published scientific literature [55]. In addition, the inquiry led to the full examination of diverse publishing houses on the accessible IoT application in Industry 4.0. A determined effort was made to prevent the lack of any key IoT papers in Ind 4.0. Table 1 shows the data accumulating steps accomplished in Scopus. The data collection was completed in October 2021 and limited the collection to 2020. As a result, the keywords search resulted in 3907 documents, limited to English results with 3810 and 3433 remaining while excluding 2021, and then the search was limited to articles only and excluded some subject area results of 891 studies. Further, all bibliometric analysis was performed on 891 articles. Table 1. IoT in Ind 4.0 data assortment steps.

Exploration
Steps

Inclusive and Exclusive Criteria
IoT in Ind 4.0, inclusion-exclusion criteria were used to choose the necessary content. First, the survey considered only articles published in English, removing the remainder. Secondly, the publishing year was an essential factor for exclusion, and the period between 2014 and 2020 was the research period. Table 2 encapsulates the more progressive elements of inclusion and exclusion. included in the last portion of the study. To fully comprehend their steady growth in the present state and future expansion trends in several other disciplines, the research aimed to examine 891 IoT database Scopus IoT articles from 2014 to 2020. Therefore, the scope of the investigation was restricted to articles between 2014 and 2020, and all other findings were eliminated. Consequently, the Scopus database recommended 891 final readable related materials in the article publications based on the keywords examined.

Research Procedure and Software Aid
The relevant data were analyzed using bibliometrics, visualization, content, and citation analysis. In addition, VOSviewer and Biblioshiny software packages were used in the research. VOSviewer 1.6.16 is a software application created by researchers at Leiden University in the Netherlands, i.e., Nees van Eck and Ludo Waltman. This program supports engrossed text mining, constructive features, and visualization display. It also offers an integrated representation of different bibliometric information, networks, and research [56]. Another quantitative research program employed in the current investigation was Biblioshiny Version 2.0. This program was developed by Massimo Aria and Corrado Cuccurullo from Naples University Federico II, Italy. This tool can carry out a thorough bibliometric analysis, drawing up the necessary data matrices, useful in a quotation, coreferencing, the comprehensive and wide-ranging linkage between variables, cooperation, and Coward's research [57]. Many equations were utilized to determine normalized link strengths, association strength, fractionalization, and clustering and to accomplish different network plots in VOSviewer software; they are well presented in [58].

Statistical Methods of Data Summarization
Relevant research of IoT in Ind 4.0 is shown in graphs and diagrams concerning documentation, publications, citations, and predictions. From the perspective of the growth of IoT in Ind 4.0 publications, the tools VOSviewer and Biblioshiny were used to analyze the visualization effects. This research recognizes the most fruitful and dominant writers, sources, publications, nations, and organizations. For citation analysis and ranking, the screening process of documents was established. Prominent authors, sources, publications, nations, and organizations were allocated the most high-ranking positions according to the total citations, the collection of publications, the average total citation, and the overall strength of the links. Finally, in Ind 4.0, IoT features hotspots and progressive trends in author keywords, index keywords, and text data analysis. The prime evidence mined from the Scopus database on IoT in Ind 4.0 exploration data is shown in Figure 2. The IoT in Ind 4.0 records entailed 891 articles from 2014 to 2020 available in 391 journals. The composed articles had the following characteristics: 2.15 average years from a periodical, 23.54 average citations per article, and 6.293 average citations per year. All journals related to IoT in Ind 4.0 had 40,570 references. The mined statistics had only 391 sources. The 891 articles had 3765, 2501, 2817, and 3279 index and author keywords, authors, and appearances, respectively. Single authored articles totaled 79, with 0.316 and 3.16 authors per document. There were 3.68 co-authors per article with a 3.38 collaboration index.

Scrutiny of Articles
From 2014 to 2020, 891 articles were published on IoT in Ind 4.0, and the year-wise dispersal is shown in Figure 3. In total, 54 articles were published, with an average of 18 from 2014 to 2016 IoT in Ind 4.0 data collection. After that article periodical rate increased rapidly; from 2017 to 2019, 477 articles were published at an average of 159 articles. In 2020, 360 articles were published, and the publication trend increased. Since 2017, the article periodical frequency on IoT in Ind 4.0 amplified at a quicker stride. Overall, the annual article publications on IoT in Ind 4.0 displayed a rapidly intensifying drift since 2016. To show IoT in Ind 4.0 articles, a curve was fitted between time and reports published per annum, employing an exponential function, as displayed in Figure 3, showing the articles published annually; the R-square value was 88.25%.

The Most Productive and Leading Article Citation Analysis
The most cited articles on IoT in Ind 4.0 are explained and analyzed in this part [56]. The 891 articles on IoT in Ind 4.0 were analyzed using 30 citations, and 166 met the criteria. One hundred and twelve articles were connected and were divided into 16 clusters. Cluster 1 to cluster 16 consisted of 12, 10,9,8,8,8,7,7,7,7,6,6,6,5,3, and 3 documents, respectively, as shown in Figure 5.
The consolidated citations were chosen as a ranking factor, with strong linkages and cumulative citations each year, and the ten leading articles are given in Table 3. The Zhong et al., (2017) [59] article titled "Intelligent manufacturing in the context of Industry 4.0: a review" ranked number one. The article has 754 citations, nine links, and 251.3 total citations per year. The article's authors are affiliated with the University of Auckland, New Zealand and the University of Bath, United Kingdom. This article became productive and the leading article in IoT in Ind 4.0. and was published in the journal "Engineering". The article titled "Industry 4.0: state of the art and future trends" ranked number one witȟ TĈ/ŷ of 343 and second based onŤĈ 686, authored by Xu et al., (2018) [32], and it was published in the journal "International Journal of Production Research". The article titled "Industry 4.0 and the current status as well as prospects on logistics" ranked first based oň TŁŜ of 15, fifth with 514 citations, and 171.3ŤĈ/ŷ. This article was authored by Hofmann and Rusch (2017) [60] and it was published in the journal "Computers in Industry". The prominent articles were cited more than 275 times, and the top five more than 500 times.   The findings of the citation study revealed that the most successful and excellent papers on IoT in Industry 4.0 processes were authored and analyzed properly. These findings indicate that the reader is ready to work on IoT for Industry 4.0. These academic publications summarize ideas from a wide range of papers. Often these papers cover a  The findings of the citation study revealed that the most successful and excellent papers on IoT in Industry 4.0 processes were authored and analyzed properly. These findings indicate that the reader is ready to work on IoT for Industry 4.0. These academic publications summarize ideas from a wide range of papers. Often these papers cover a wider range. While most of these references or quotations indicate research that is critical, Ŝŷ : Publication start year;Ĉŷ: Citable years;ŤĈ/ŷ: Total citations yearly. The findings of the citation study revealed that the most successful and excellent papers on IoT in Industry 4.0 processes were authored and analyzed properly. These findings indicate that the reader is ready to work on IoT for Industry 4.0. These academic publications summarize ideas from a wide range of papers. Often these papers cover a wider range. While most of these references or quotations indicate research that is critical, noteworthy, or pertinent to the critical evaluation by the usage of IoT in Ind 4.0, others describe literary works with a descriptive enough and wide background. The top 10 IoT documents in Ind 4.0 were published in leading scientific publications, as shown in Table 3. In addition, credit could not be awarded for their accessibility and the study findings given. Eminent scientists from the most recognized educational institutions around the globe have also submitted papers. Subsequently, they have garnered great respect and appreciation in their field of specialization. The top 10 quoted journals are from New Zealand, the UK, South Korea, Germany, Switzerland, Sweden, China, Brazil, and France. They all come from Germany and France. At the same time, they showed a strong potential for prompt marketing of inventions. In this review, the authors' main focus was the different technologies used and the sustainability of Industry 4.0 operations. IoT, CPS, Cloud Computing, Simulation and Prototyping, 3-D printing, and Cyber Security in industrial automation were discussed. From a sustainability aspect, the key areas discussed were economic stability, sustainable industrial processes, and the environment [69]. Boyes et al., (2018) presented IoT as the key technology to enable connectivity in industrial automation. The development of Industrial IoT (IIoT) and its relationship to CPS was discussed in detail. The authors also presented the research gaps and future directions to overcome those gaps. The significance of the security of industrial data while communicating in cyberspace was impressed upon in this article [70]. Muller and Voigt (2018) discussed the impact of the Internet of Things and Services (IoT) on the automation of various processes and mechanisms in the Industry 4.0 framework. It was also discussed that IIoT realizes complete connectivity in Industry 4.0.
Technical and economic aspects, opportunities, and challenges were reviewed for Industry 4.0 applications from a sustainability aspect [71]. Jabbour et al., (2018) conducted a review on Circular Economy (CE) in industrial applications. Different advanced technologies playing a key role in Industry 4.0 were also discussed. The fundamental aim of this review work was to explore the methods to increase the CE application stake in Industry 4.0 by integrating these two technologies [72]. Pereira and Romero (2017) reviewed basic concepts, technologies, and developments in Industry 4.0. In this paper, IoT, CPS, and their integration to improve industrial processes, productivity, market share and economy, develop new business strategies, and customize the work environment on Industry 4.0 were discussed [73]. Buer et al., (2018) discussed the increased popularity of Industry 4.0 concepts in academia and industry. This review was carried out to identify the relationship between Lean Manufacturing and Industry 4.0. The authors highlight that at the beginning of the development of the concept of Lean Manufacturing, many challenges were administered using Information and Communication Technology (ICT). It was also discussed that ICT in Lean Manufacturing caused new opportunities and potential developments in Industry 4.0. IoT and CPS were presented as the key technologies to realize distributed, reliable, automated, and flexible industrial systems [74].
Xu and Duan (2018) discussed Big Data and CPS as the key role players for resource optimization in the Industry 4.0 framework. Optimal resource utilization is one of the key factors in sustainable industrial development. The authors also addressed a lesser number of surveys where the integration of these two technologies in industrial automation has been discussed. In this work, the basic concept of big data, its characteristics, and the big data challenges of CPS are discussed in detail. Finally, the paper was concluded with future research challenges in the security domain of CPS in Industry 4.0 [75]. Kiel et al., (2017) discussed IoT and IIoT's role in delivering reliable, economic, and sustainable Industry 4.0 applications. CPS was discussed as the key component of IIOT. The authors also presented the benefits and major challenges of integrating IIoT in various industrial processes. The authors compared three industrial sectors, i.e., electrical firms, machine industry, and automation, regarding benefits and challenges faced in IIoT applications [76]. Barreto et al., (2017) discussed the role of IIoT in the supply chain and presented it as the key reason behind logistics in Industry 4.0. In addition, the authors discussed various requirements and fundamental issues different organizations face in deploying fully functional Logistics 4.0. Possible future research directions in the deployment of technology equipped logistics were also presented in this paper [77]. Finally, Haseeb et al., (2019) studied the role of Industry 4.0 in increasing business sustainability. This survey was conducted for SMEs in Thailand. In this survey, IoT, CPS, Big Data, and Smart Factories emerged as the key technologies to promote sustainable business for SMEs. However, the survey was conducted only for SMEs, so observations cannot be generalized to other industries [78]. Aazam et al., (2018) impressed upon the industrial revolution caused by technological development. The authors mentioned IoT as the key technology for Industry 4.0 and also the base of IIoT. Using these two technologies loaded with different sensing devices and equipment, a huge volume of data is generated from diverse industrial processes. These data need to be processed locally to avoid delays and security issues, which is the fundamental reason to deploy Fog in IIoT. In this paper, the authors discussed the basic concepts of Fog Computing, IIoT, and Industry 4.0. Various advantages of integrating Fog Computing in industrial applications were also discussed. The authors concluded their work with the challenges of integrating Fog Computing in Industry 4.0 applications [79]. Yin et al., (2017) presented a review on the revolution of the production system from Industry 2.0 to Industry 4.0. Customer demand was characterized as the key player in the evolution of the production system over time. The authors also discussed the future possibilities of IoT-facilitated smart factories [80]. Schroeder et al., (2016) proposed a new model using Automation ML for Digital Twin. This model was proposed concerning using CPS for industrial manufacturing systems and delivering better quality product services in Industry 4.0 [81]. Sommer (2015) discussed Industry 4.0 as the evolution caused by smart devices and equipment. In the Industry 4.0 framework, SMEs face several challenges in terms of their competence, readiness, and potential to integrate the advanced technologies in various subsystems and processes. Due to these challenges, the German industry cannot take all benefits of industrial automation in the SME sector. However, this industry is planning and adopting several action plans to overcome these issues [82]. The technologies for possible integration, domains, and evolution of technologies are shown in Table 4 for top-cited documents related to IoT applications in Industry 4.0. From the literature analysis of top-cited articles, the integration of IoT in different processes revolutionized the various domains in the Ind 4.0 environment focusing on different aspects such as the design, production processes, manufacturing, economy, services, sustainability, business strategies, supply chain, security, and communication of data, etc. in different types of organizations, viz. SMEs, the electrical and machine industry, etc. During the study, it was observed that major development is caused by the integration of IoT with other advanced technologies such as AI, big data, cloud computing, fog computing, blockchain, and CPS. CPS is observed as one of the key role players in this IoT era of industrial development. IIoT is an evolution of IoT by emphasizing smart industrial devices and equipment, conveniently making secure M2M communication possible. The confluence of IoT with other technologies offers economical, sustainable, and better-quality services to the users in the smart industry. It has also reasoned the optimal utilization of the industrial resources and secured transfer and management of industrial data gathered through different processes.

The Most Productive and Leading Journal Citation Analysis
Journal overlay visualization based on 20 citations and two articles is shown in Figure 6.  The top ten sources constructed based on theŤĈ, NoA,ŤŁŜ, and average ÄĈ are shown in Table 5. The "International Journal of Production Research" ranked first when theŤĈ was selected as a measure for the journal's influence, with 1629ŤĈ, and the first paper on IoT in Ind 4.0 was published in 2018. The IEEE Access ranked first based on NoA (53), second based on 1470ŤĈ, and nine based on ÄĈ. The Computers in Industry ranked second with a 71ŤŁŜ and third with 1247ŤĈ. The PSY,ȊF, and CS of the top ten journals are also shown in Table 5. Out of the top 10 sources, "IEEE Industrial Electronics and Magazine" has anȊF of 13.593 with 710ŤĈ in IoT in Ind 4.0.    The findings of the citation study revealed that the most successful and ex pers on IoT in Industry 4.0 processes were authored and analyzed properly. T ings indicate that the reader is ready to work on IoT for Industry 4.0. These publications summarize ideas from a wide range of papers. Often these pape wider range. While most of these references or quotations indicate research that noteworthy, or pertinent to the critical evaluation by the usage of IoT in Ind describe literary works with a descriptive enough and wide background. The documents in Ind 4.0 were published in leading scientific publications, as show 3. In addition, credit could not be awarded for their accessibility and the stud given. Eminent scientists from the most recognized educational institutions a globe have also submitted papers. Subsequently, they have garnered great re appreciation in their field of specialization. The top 10 quoted journals are from land, the UK, South Korea, Germany, Switzerland, Sweden, China, Brazil, an They all come from Germany and France. At the same time, they showed a stro tial for prompt marketing of inventions. The findings of the citation study revealed that pers on IoT in Industry 4.0 processes were authored ings indicate that the reader is ready to work on I publications summarize ideas from a wide range o wider range. While most of these references or quota noteworthy, or pertinent to the critical evaluation b describe literary works with a descriptive enough a documents in Ind 4.0 were published in leading scie 3. In addition, credit could not be awarded for their given. Eminent scientists from the most recognized globe have also submitted papers. Subsequently, th appreciation in their field of specialization. The top 1 land, the UK, South Korea, Germany, Switzerland, They all come from Germany and France. At the sam tial for prompt marketing of inventions.

The Most Prolific and Dominant Author Citation Analysis
The most prolific authors were selected, having a minimum of two articles and 20 citations. Figure 8 shows the 172 authors' network of IoT in industry 4.0, out of 2817, divided into twelve clusters. The diverse rankings of the authors are shown in Table 6      The findings of the citation study revealed that pers on IoT in Industry 4.0 processes were authored ings indicate that the reader is ready to work on I publications summarize ideas from a wide range o wider range. While most of these references or quota noteworthy, or pertinent to the critical evaluation b describe literary works with a descriptive enough a documents in Ind 4.0 were published in leading scie 3. In addition, credit could not be awarded for their given. Eminent scientists from the most recognized globe have also submitted papers. Subsequently, th appreciation in their field of specialization. The top 1 land, the UK, South Korea, Germany, Switzerland, Ŝŷ : Publication start year.

Lotka's Function: Author Script Explanation
The law of Lotka is a series of Zipf's special laws named for Alfred J. Lotka. It specifies how often writers publish in a certain field. It emphasizes that a portion of the total number of academics who participate in one year is the number of scholars contributingconsequently, the frequency of production declines with the number of publications [83,84]. Figure 10 shows the number of writers who collaborated on a particular article. Two thousand, five hundred and twelve authors wrote one article with a proportion of authors of 0.8992, and two papers were written by 227 authors with a proportion of 0.081. Forty-six authors wrote three articles with a 0.016 ratio of authors. Four documents were written by 17 authors, five by six, six by three, and seven by two authors, referred to in Figure 10. A solo author wrote the top ten 15 documents with zero proportion of other writers.

Co-Occurrence of Keyword and Content Analysis
The co-occurrence paradox discusses how some things exist simultaneously, such as keywords or index terms. The literature includes more information than the research, including organizations, publications, authors, and keywords. A quantifiable analysis of the co-occurrence structure exposes the implication of information and the knowledge that some items hide. Keywords can also be used to determine the parameters of the survey and control hotspots and phenotypic expression for the field of practice and study [85]. Content analysis is a method of study used in evaluating and coding textual content to provide reproducible and accurate information. Qualitative information may be turned into quantitative information such as papers, oral statements, and graphics by methodically examining words [56].

Co-Occurrence Analysis of Author Keywords in IoT in Ind 4.0
This section analyses the authors' co-occurrence in IoT in Ind 4.0 from 2014 to 2020 based on Scopus datasets. Five co-occurrences were used for the IoT in Ind 4.0 to choose the keywords. There appeared to be 2501 author keywords and 90 relative to the five co-occurrence criteria of author keywords. The largest group of linked items comprised 90 keywords split into 11 clusters. The visualization of co-occurrences by the authorkeyword network is displayed in Figure 12. The word cloud of the top 30 author keywords is shown in Figure 13 Table 8 depicts the evolution of author keywords from 2014 to 2020. The term "Industry 4.0" first emerged in 2014, and since then, its use has grown exponentially. It had reached 219 by the end of 2020 and was featured 528 times in total, averaging 132 per year from 2014 to 2020. The author keyword internet of things first occurred in 2015, and its popularity grew steadily from there, peaking at 220 in 2020 with an average of 55. More than 15 times, the terms IoT, Industrial Internet of Things, and Cyber-Physical Systems appeared. Except for Industry 4.0, no one term from the top ten-word dynamics was utilized in 2014.

Index Keywords of IoT in Ind 4.0: Co-Occurrence Analysis
These are keywords selected by content providers and standardized according to the vocabulary available to the public. Contrasting the author's keywords, synonyms, spelling, and plural forms are considered in the indexed keywords. An index term, a term, a topic or a descriptor is a term that encapsulates the core of a document's subject matter in the collection of information. Index words provide a regulated language for use in bibliographic documents. The bibliographic controls are an inherent component of the libraries' collection, management, and distribution.
This portion describes the co-occurrence of index terms in IoT in Ind 4.0 between 2014 and 2020 for Scopus records. The index keywords for IoT in Ind 4.0 were determined based on a total of 15 cases. As a result, there were 3765 index keywords for IoT in Ind 4.0, of which 58 fulfilled the threshold for 15 co-occurrences. Thus, 58 index keywords were divided into five groups in the most thorough list of associated items. Figure 14 shows the index keyword density representation. Word dynamics of index keywords from 2014 to 2020 are illustrated in Table 9. The word cloud of the top 30 index keywords is shown in Figure 15 (Figure generated from: https://worditout.com/word-cloud/create, accessed on 25 May 2022).

Text Data Analysis of IoT in Ind 4.0
The VOSviewer software executes an exclusion method with a text data analysis and calculates each term's relevance score. Words with higher relevance mean explicit topics addressed by text information throughout the text data extraction procedure. The phrases for the extraction of text data, on the other hand, tend to be less relevant and do not reflect a specific topic. Thus, phrases collected with insufficient relevance data are selected, and explicit and informative pieces are the key topics. About 40% of data collected are removed with poor relevance ratings [56]. The words in the title and abstract of the article are retrieved in textual analysis. Even with the binary technique and the relevance score, the title and abstract data retrieved from the article are analyzed [86].  Terms were selected based on 30 occurrences in the IoT text-data analysis in Ind 4.0. In Ind 4.0, 18,225 text-data words and 154 correspond to 30 events on IoT. Therefore, 60 percent of the relevant words were taken into account, with 92 based on the relevancy score. Figure 16 shows the display of the density of linked words. The largest range comprises 92 words grouped into clusters 1, 2, and 3, consisting of 52, 39, and one IoT in Ind 4.0 terms. Table 10 depicts IoT in Ind 4.0 text data, i.e., data extracted from the abstract and title of collected relevant documents. For example, the word "application" appeared 282 times with a relevance score (RS) of 0.407 from the top 25 terms. On the other hand, the term "design methodology approach" topped the list based on an RS of 8.432 with an occurrence (Occ) of 34. Furthermore, the terms "study", "network", "solution", and "research" were in the top five based on the occurrence of 215, 210, 19, and 195, having relevance scores of 0.856, 1.230, 0.485, and 0.686, respectively. Finally, the terms "originality value", "IoT device", "manager", and "protocol" were in the top five based on a relevance scores of 7.  Tables 11 and 12, respectively. A tree plot of the top 30 title words is shown in Figure 17; 'industry' appeared 395 times with 18%, followed by 'smart' and 'manufacturing', i.e., 7%. The tree plot of the top 30 abstract words is shown in Figure 18; 'industry' appeared 1775 times, i.e., 11%, followed by 'data' and 'manufacturing', i.e., 7%.    2014  2  0  0  0  1  1  0  0  0  0  2015  8  3  5  4  3  4  3  2  2  1  2016  22  9  13  9  11  6  5  5  3  6  2017  34  16  13  6  6  6  14  7  4  7  2018  77  31  30  24  23  21  18  19  15  11  2019  96  39  41  26  26  26  27  18  23  14  2020  155  52  47  58  42  38  26  39  23  31   Sum  394  150  149  127  112  102  93  90  70  70   Avg.  99  38  37  32  28  26  23  23  18 18

Three Field Plots on IoT in Ind 4.0: Sankey Illustrations
A Sankey illustration is used to represent a flow from one subset to another. The linkages are called nodes, and the interconnections are called links. The ideal way to display Sankeys is to map different systems. Sankey diagrams are usually used in numerous networks and techniques as representations of energy or material flows. They represent quantitative details of flows, relationships, and transition. Sankey diagrams provide guided and weighted designs with weight characteristics that maintain the flow. At each node, the weights of the inflow are the same as the outcome [87].
Biblioshiny's three-field plot visually evaluates the link between sources, nations, affiliations, index keywords, authors, journals, and author keywords, etc. Rectangular diagrams depict relevant elements with different descriptions using colors. The rectangle's height links several factors such as nations, sources, renowned authors, writers' and keywords. The larger the rectangle, the more interconnections between different components. Figure 19 shows the illustration for research related to IoT in Ind 4.0 literature. The left side of the diagram presents the author keyword; on the right side, journal names are shown, and in the middle, the author's names. The scrutiny of a diagram can show which author keyword of IoT in Ind 4.0 had been used most recurrently by diverse authors and journals. For example, four keywords, i.e., "industrial internet of things", "industry 4.0", "internet of things", and "cloud computing", were utilized by Voigt K. I., Muller J. M., Fraga-Lamas P. and Wan J. and published in Sustainability, IEEE Access, and IEEE Internet of Things Journal. Similarly, Figure 20 shows the illustration for research related to IoT in Ind 4.0 literature. Again, the left side of the diagram presents the index keyword; on the right side, journal names are shown, and in the middle, authors' names. In the visualization of the uppermost index keyword, authors and sources specified that there were index keywords, including "industry 4.0", "internet of things", embedded systems", and "big data", that had been utilized mostly by Li D., Wan J., Wang S., Liu Y. and Xu X. and frequently published in Sustainability, IEEE Access, and IEEE Internet of Things Journal. Figure 21 shows the illustration for research related to IoT in Ind 4.0 performed by different countries and published in different journals. The larger size of the rectangle signifies that China performed well with significant contributions of Li D., Liu C., Wan J., Wang S. and Imran M., and these authors from China mainly published their research related to IoT in Ind 4.0 in IEEE Access. On the other hand, the rectangle size indicates that Germany also performed well; Muller J. M., Liu Y., Voigt K. I. and Veile J. W. published their research related to IoT in Ind 4.0, mainly in Sustainability and IEEE Access. Italy has main authors such as Ferrao P., Conti M. and Sisinni E, who published mainly in Electronics (Switzerland).   In addition, the evolutionary trend of IoT in different types of industrial applications was analyzed using index keywords and author's keywords, shown in Figures 22 and 23, respectively. For this analysis, the period considered was from 2014 to 2020. While studying the base of index keywords, it was observed that in the year 2017, IoT was integrated into industrial design applications.  In 2018, this revolutionary technology was mingled with many other evolving technologies, such as big wise data, cloud computing, distributed systems, and manufacturing. With further development, it was placed in cyber-physical systems and embedded systems to benefit various applications in Industry 4.0. Recent growth in the industrial usage of the Internet of Things has introduced the Industrial Internet of Things (IIoT), amalgamated into various industrial domains. IoT in conjunction with AI and Blockchain provides more secure industrial applications. Using author keywords, IoT is closely integrated with many other advanced technologies such as machine learning, intelligent manufacturing, cloud computing, and simulation to provide sustainable solutions in the Industry 4.0 ecosystem.

Summary and Future Roadmaps for IoT in Ind 4.0
The unavailability of systematic evolutionary development of IoT in the Industry 4.0 environment for the considered period is the biggest motivation behind this novel piece of work. On one side, this work has provided insight into the field and has offered possible future research directions. To avoid any misinterpretation or confusion, universally recognized keywords related to the domain were used to gather the data. The present systematic review portrays the role played by IoT in Industry 4.0 ecosystem in coordination with other advanced technologies. It has been observed that IoT plays a key role in many industrial processes in coordination with other advanced technologies such as artificial intelligence, machine learning, big data, cloud computing, cyber-physical systems, and intelligent manufacturing. This firm collaboration has benefitted many industrial operations and processes. This systematic review has derived the following possible research directions for scientists and engineers:

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In-depth understanding of IoT and Industry 4.0 ecosystem and applications.

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Optimal interfacing of IoT with other advanced technologies. • Standardization of protocols for smart industrial processes. • Developing smart embedded systems.

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Integration of IoT to cater to sustainable development of industrial applications. • Implementing optimal, productive, flexible, and customized industrial solutions.
IoT is further expected to play a more vital role in monitoring, predictive maintenance, inventory management, quality control, supply chain optimization, and plant safety.

Limitations of Analysis for IoT in Ind 4.0
While undertaking a theoretical assessment, the current study has obvious limitations. The study's data gathering was constrained because it relied solely on Scopus for its literature review, and conference proceedings were not considered for analysis. As a result, the paper's reach can be expanded by including articles from other databases, such as Google Scholar. Comprehensive bibliometric research was presented to distinguish between ISI-WoS and Scopus results. According to the bibliometric study, around 2/3 of the referred documents were found in both databases, whereas 1/3 were only found in one. The citation effect of the core papers in both databases was larger, but the influence of the peripheral publications in just one database must not be overlooked because some high-impact articles may be identified among them. Many Scopus publications were not detected in WoS. However, they were documented in ISI Transactions since Scopus includes an aggregate reference to the conference proceedings without a descriptor of each contribution and, hence, of the names or addresses of their authors [88,89].

Concluding Remarks
In this work, we made an effort to contribute to Industry 4.0 by studying the evolution of IoT in the various processes, applications, subsystems, and other areas. This muchneeded work was carried out in this most significant domain using bibliometric and content analyses. We gathered eight hundred and ninety-one articles from 2014 to 2020 from the most authentic Scopus database to carry out this research work. In this study, we aimed to conduct a bibliometric investigation and visual valuation of IoT in Ind 4.0 evolution to link the disparity in the available literature analysis and research directions.
The paper "Intelligent manufacturing in the context of Industry 4.0: a review" by Zhong et al., (2017) [59] was rated first with 754 citations, followed by "Industry 4.0: state of the art and future trends" by Xu et al., (2018) [32]. The integration of IoT in multiple processes revolutionized multiple facets in the Ind 4.0 environment, dedicated to different aspects such as design, production processes, manufacturing, economy, services, sustainability, business strategies, supply chain, data security and communication, and so on in various types of organizations, such as SMEs and the electrical and machine industries. Integrating IoT with other sophisticated technologies such as AI, big data, cloud computing, fog computing, blockchain, and CPS has resulted in a significant advancement. CPS has been identified as a crucial participant in the IoT era of industrial development.
With 1629 citations, the "International Journal of Production Research" was ranked #1, and the first paper on IoT in Industry 4.0 was published in 2018. The IEEE Access ranked first with 53 articles and second with 1470 total citations. Wan J. ranked first, based on a score of 1031, second based on a score of 132, and third with eight NoA. Wan J. is a researcher at Guangzhou's South China University of Technology's School of Mechanical and Automotive Engineering. In addition, 2512 authors contributed to one article with a proportion of authors of 0.8992, while 227 authors produced two papers with a proportion of 0.081. Three reports were written by 46 authors, resulting in a 0.016 ratio of authors. The South China University of Technology in Guangzhou, China, was placed first with a score of 788, 4, and 17. Beihang University in Beijing, China, came in second place with a score of 439 and first place with a score of 220. With 4820 total citations, 254 articles, and 178 total link strengths, the United States was identified as the most prolific and influential country, ranking fourth in average article citations (19). Singapore was in the first place, with an average of 82 article citations.
The author keyword dynamics revealed that 'Industry 4.0' appeared first in 2014 with the application of IoT in Ind 4.0 with an overall appearance of 528, followed by the 'internet of things' in 2015, and three times with a total count of 220 up to 2020. The terms have much scope for research with IoT in industry 4.0, such as 'industrial internet of things' with an appearance of only 17 times, 'cyber-physical systems' (16 times), and 'big data' (14 times). 'Smart manufacturing', 'smart factory', and 'cloud computing' with appearances of 13, 11, and 10 also have much potential, and these are termed as research gaps in the application of IoT in Ind 4.0. Similar results were revealed by index keyword dynamics, and a central gap exists in the terms 'decision making' and 'industrial revolution' while using IoT in Ind 4.0.
In text data from IoT in Industry 4.0, i.e., data taken from abstracts and titles of supporting documents, the word "application" appears 282 times in the top 25 phrases, having a relevance score of 0.407. On the other hand, the term "design methodology approach" was at the top of the list, with an RS of 8.432 and an occurrence of 34. Sankey diagrams are commonly utilized as representations of energy or material flows in a variety of networks and methodologies. They are numerical representations of flows, linkages, and transitions. Sankey diagrams create guided and weighted designs that keep the flow going. Voigt K. I., Muller J. M., Fraga-Lamas P. and Wan J. used four keywords: "industrial internet of things", "industry 4.0", "internet of things", and "cloud computing" in articles published in Sustainability, IEEE Access, and IEEE Internet of Things Journal.
It has been observed that over time, IoT started to amalgamate with other advanced technologies such as Artificial Intelligence, Cloud Computing, Bigdata, Distributed Systems, Embedded Systems, Cyber-physical Systems, Blockchain, and IIoT. This integration benefitted several Ind 4.0 application domains, such as design, manufacturing, robotics, supply-chain, etc. For example, manufacturing evolved as intelligent manufacturing. As most of the data are transmitted in cyberspace, more secure and reliable IoT integrated secure applications are deployed in the Ind 4.0 ecosystem. A huge volume of data gathered from various industrial applications is stored in the cloud, which reduces memory requirements and initiates optimal usage of the resources. The inclusion of IoT in various industrial processes caused energy efficiency, economical products and services, better quality, efficient decisions, and reduced equipment downtime.
The research hotspots and gaps related to IoT in Ind 4.0 show a prominent scope for future young researchers. However, such as in every study, this investigation also suffered from some inherent limitations. For example, many papers in other languages were not considered in the present research. There are also many articles not available in this database that were not part of this study. Nevertheless, the significant results of this bibliometric analysis can be used for future research with some novel applications in various research areas. Furthermore, the study will allow researchers in IoT in Ind 4.0 to expand quickly in comprehending the development status and pattern.