Role of Big data in HealthCare and Internet of Things: A Detailed Bibliometric Survey

This paper makes the Bibliographic study of the Big Data involvement in Healthcare and Internet of things. Research contribution towards this area has started from the year 2013 as per the fundamental keywords chosen in this survey. Thus makes the thrust discipline and emerging technology of research, also a trendy domain based on its recognized inception. Upon consideration of the selected keywords there was no work up to 2012 and all together 425 papers are obtained from 2013 onwards through Scopus website. Among these major contribution was in Computer Science Subject area with 308 in number and maximum articles were published in English Language with 421 and highest number of papers contributed were 128 by India. This study uses versatile Bibliometric analysis databases and methods resulting in Statistical and Network Analysis in terms of Authors, Organizations, Citations, Co- Citations etc.


I. INTRODUCTION
Internet of Things is better defined establishing Pervasive Communication between Physical World and Virtual World. This enables identity of advanced Information and Communication Technology with four different Personalized -P Healthcare factors (Schreier et al., 2014).Research growth is more in Internet of Things from the last ten years under various categories of application, advancements, design, monitoring, and analytics as futuristic research (Azana Hafizah Mohd Aman et al., 2020). Billions of devices are connected to internet and it is increasing day by day, in turn the integrity, storage, security, internal operations are the prime concern. These economical and physiological (Felix Uribe et al., 2018) kind of social impact is the base for identification and classification of various Internet of Things devices. Further the above mentioned factors are evidently addressed. Large scale of Sensors plays prominent role in connecting devices to each other creating smart environments an up hand over Ubiquitous Sensing capabilities which makes Internet of Things a revolutionary technology (Deepthi Sehrawat et al., 2019).An IoT state of art applications and smart sensing has created solutions for many real time problems in largemedium-low levels (Cleber M. de Morais et al., 2019) It is obvious with support of other concerned enabling technologies.Due to its stupendous growth in both Academia and Industry a great transformation has been made from IoT to IIoT meeting requirements in veracity of Business applications , Service applications, Enterprise applications and so on (Avish Karmakar et al., 2019). Understanding the current scenario and predicting the future need, more research is needed in Healthcare 4.0 in coupling with data gathering, enriching, storage and access, analysis and monitoring, predicting and learning etc. Massive amounts of data-termed as 'Big Data' can do wonders. Especially in Healthcare multiple versions and types of data viz. patient records, health records, hospital records, nutrition data and significant portions of public and private healthcare is generated and it should be effectively handled by Big data tools (Sabyasachi- Dash et al., 2019).Big data analytics will help in improving the personalized care of patients by employing different methods of data analysis to get rid of un necessary medical spending (Lidong Wang et al.,2019).

II. SURVEY OF INTERNET OF THINGS -HEALTHCARE -BIG DATA
Healthcare is the prominent way of diagnosing, maintaining, managing and organizing the health data of a human with various Healthcare systems. Historical evolution of Healthcare 1.0 to 4.0 ensures smart connectivity (Jingshan Li et al., 2021) under different Qualitative and Quantitative approaches. Ability to use the health devices and patients towards doctors and making heath analysis in a needy manner. Industry 4.0 started its transformation from manufacturing industry to all corners of technological changes with respect to the support of IoT, and Big Data Analytics for analysis and remote data storage with Cloud Computing and also allowing Fog Computing (Giuseppe Aceto et al., 2020). Digitization of Healthcare as a key valued embracer to give more care -(IoMT): the future generation medical care in hospitals and healthcare centre (siemens-healthineers) allows to consolidate the patient data, in turn enables better diagnosis in giving extreme results. Healthcare is undergoing a great technical change hand in hand with Big data that is raising some opaque result and interpretation issues will be solved by certain Machine Learning models (Yoo H.a et al., 2021).A new research with Collective Social Intelligence (CSI) creating new product development with effective capability for enabling technologies, online social networks and Collaborative Analysis in Healthcare Systems (Jones J et al., 2020). In the current pandemic COVID -19 scenario the short comings of Healthcare were clearly outraged and can be predicated with advancement in Internet of Things wearable technology by suggesting effective healthcare solutions using smart and connected world. On the other hand Industry 4.0 enables the communication and enabling technologies with different paradigms in relation to Healthcare 4.0 (Aceto G at al., 2020). A research says the Gynaecology departments are being supported with disruptive innovations of medical era with data collected from wet-labs and transformed as molecular big data, clinical big data, computational big data, digital big data, and physiological big data; in turn handling with proprietary methods for improving the reproductive female health (Khamisy Farah.R et al., 2021). Some studies propose an architectural framework for giving more value to the field of e-health in assisting powerful challenges like continuous monitoring, smart decisions, data processing (Babar.M et al., 2018). Adopting different branches of philosophy, inspiring and involving in versatile technological changes, taking part in advancements of era is the best quality of habituating to research work. Similarly a branch of philosophy studying the being, existence, becoming; shed a ray on internet of things and Healthcare. Ontology based understanding of specific risks like security and privacy on Healthcare information systems have been studied (Abhinaya et al., 2015). Even Big data supports as an analysis method for risks and precautionary measures and a use case driven approach for certain vaccination process to predict the further benefits in Healthcare domain (Liyanage H.et al., 2014).
At every stage the sensors are vital in detecting the data and gathering the data, it is very peculiar and sensitive in healthcare sector. Massive streams of data is being generated form health sensors and the challenges faced in perspective of user identities in analysing bith big data technologies is sports related applications (Cortes. R. et al., 2015). As it is expected that billions of devices connected to Internet are it is rapidly growing for every unit of time, distinguished Artificial Intelligence and Data mining Algorithms have been imposed to generate better accuracy in less time for Smart Healthcare Systems (Alam. F., 2016). Some countries are encouraging best practices to inculcate the understanding of health data generated in crisis situations that can understand the problems in health systems as part of the academic study itself instead of Industry involvements. In Brazilian Aeronautics Institute of Technology: a crisis approach for healthcare systems has been proposed that use an agile testing methos to validate and verify the health data. (da Silva.D.A., 2018).

III. METHODOLOGY
Amongst many databases across the globe for Research Articles, Manuscripts, Research Papers, Short Surveys, Literature Surveys; Scopus is the most populated database in giving search results in a better and multifaceted way. Multiple keywords can be used for searching the papers in view with Organizations, periodical intervals of time along with the usage of Fundamental keywords, Primary Keywords, Secondary Keywords and so on based on narrowing down the search output. In this work the narrowed result for search is 425 artciles based on the chosen fundamental and primary search keys.

Table 1: List of Search Keys
Search Key 1 Internet of Things Search Key 2 using (AND) "Health Care" AND "big data" The query proposed by Scopus for obtaining the articles is: ((TITLE-ABS-KEY("Internet of Things") AND TITLE-ABS-KEY(("Health Care" and "big data")))) Even though the above query infers the starting publication year is 2013, there is no research article pumped to Scopus database before this year as per the mentioned keywords.

IV. INITIAL SEARCH OUTCOMES
During the initial search the articles have been resulted under various type of Documents Access which are retrieved in different categories. Open Access type, Gold Access type, Green Access type etc. Amongst all, majority are available in Open Access document type with 108 articles.

B. ASSESSMENT BASED ON SOURCE TYPE
Multiple Sources of publication have been assessed based on the fundamental and primary search keys in the Scopus database, maximum number of articles among 425 have been published in 182 different Journals and in the next level 160 Conference proceedings were observed.

C. ASSESSMENT BASED ON LANGUAGE TRENDS
On the Scopus database, multiple keywords are used for the searching in view of the work proposed in the paper. Various papers were traced in different languages. Language is one of the parameter for analysis. Observations are that English language with good number419, followed by Chinese with 4.

D. ASSESSMENT BASED ON KEYWORDS
Besides the Fundamental keywords, a variety of keywords will be shown as the outcome form the assessments obtained. Among all "Internet Of Things" a proper way of using and writing the word is in the top priority 331 followed by "Big Data" with 328. Also the fundamental key word used as a part of the query is adopted in different ways in many research articles; like the way shown in the below table with Sl.No: 1,4,8,9,18.

V. ASSESSMENT PROCEDURE
To start with analysing the articles, Scopus database provides the best way of considering the search on fundamental keywords along with any additional keywords if necessary in accordance with logical operators like AND/OR. The search outcomes are generated under Years of publication, Authors contribution, Document type, Organization, Funding Sponsor etc. This is one way of analysis process termed as Statistical Analysis.
Another way is a Network Analysis of databases, performed using VOSviewer 1.6.16 very effectively. It has various assessment options in making relationships and allows to generate maps.

Major findings obtained in statistical Analysis via Scopus Database and Network
Analysis is obtained in VOS viewer 1.6.16.

A.1. Document Analysis by Year
Scopus Database generates analysis for various parameters among which the documents are generated from years 2013 to 2021. In this analysis 118 documents are highest position in the year 2019.

A.3. Documents Analysis by Year
Different subject areas took part in handling research across the years. As the Scopus database search keywords are in to multidisciplinary and multi-dimensional subject areas, the following graph shows the major contribution is made from Computer Science area with 34.7%.

A.4. Analysis by Document Type
Scopus database handles research work to be published and stored different kinds of documents like Books, Chapters, Conference Reviews, Short Surveys, Letters, and Articles etc. The diagram shown below depicts document type analysis with maximum 48.2% of Conference Proceedings.

Co-authorship to Organizations Analysis
Here the analysis method is Co-authorship to organizations under full counting by ignoring more number of authors per organization (20). Threshold levels are set as least number of documents per organization is 2 and least number of citations for organization is zero.

B.2.2. Co-occurrence to Author Keyword Analysis
To perform this analysis the least number of occurrences of a keyword is 3. Out of 1130 keywords 92 meet the threshold parameters and maximum number of occurrences is 158 and the key word is "big data".

B.2.3. Co-occurrence to Index Keywords Analysis
For this analysis the threshold value is mentioned like minimal number of occurrences of a keyword is 3, of 2740 keywords 404 keywords match the threshold. Among all, "Internet of Things" is matching with 308 occurrences as co relation with Index Keywords.

.3. Bibliographic Coupling to Authors Analysis
Choosing full counting for Bibliographic coupling and Authors with ignoring documentshaving 25 maximum number of authors. Alongside threshold parameters are set as 2 for minimum number documents of an author and citations of an author is 2. Of 1380 authors 136 meet the threshold and the same is shown in the network diagram below. In this paper Bibliometric analysis of the role of big data in Health care and Internet of Things is carried out using AND logic operator. A total of 425 documents were obtained from Scopus database from 2013 to 2021 as on 3 rd June 2021. Major observation is the work is not existed before 2013 as per the search out come given by Scopus database.It is observed that maximum articles were published in English language followed by Chinese. Research went more in Computer Science subject area across different countries and organizations with major publications in the year 2019. Statistical analysis of documents is made under different parameters like keywords, funding sponsor, organizations, year, source title, document type etc. using Scopus database.
On these same lines Network Analysis is made using VOSviewer 1.6.16, of course with the support of data generated by Scopus database.The analysis is performed under Type of analysis, Unit of analysis and counting method for Co-authorship, Co-occurrence, Citations, and Bibliographic coupling in terms of Authors, Organizations, Countries, Keywords, Author keywords, Index keywords and Sources. Analysis outcomes were clearly generated and showed in form of Network visualization graphs. It can be concluded that a good amount of work is expected in future as per the statistics.