An application overview of IoT enabled-big data analytics in Health sector with special reference to Covid-19

— Big Data analytics has come a long way since its inception. This field is growing day by day. With the advent of large handling capacity of computational analysis of modern computing systems as well as Internet of Things (IoT), this field has revolutionized the way we think about data. It has influenced the major domains such as healthcare, automobile, computing, climatology, and space communications. Of late, the health care sector has been largely influenced by this. This communication deals with the areas of healthcare where big data analytics has been largely influential. Encompassing the basics of Big Data Analytics (BDA) driven by IoT, the applications of it in healthcare sector are outlined, accompanied by future expectations. Additionally, it also presents a comprehensive analysis of recent application with special reference to Covid-19 in this sector.


INTRODUCTION
Literally, big data refers to voluminous information. However, when, we incorporate the term Big data in healthcare, and then there arises diverse definitions in this sector. However, the suitable definition can be given as the enormous data entailing biological, clinical, and environmental as well as lifestyle information concerning large individuals, which corresponds to their health and wellbeing along a time span. In nonprofessional's word, it refers to dataset whose enormity in size cannot be handled by single database software for capturing, storing and subsequent analysis. Accordingly, the stress goes to the parameters involving size and volume. Accordingly, it engages three V's. They are variety, veracity and velocity. The first term variety links to diverse types, sources and format. Again, veracity refers to quality and validity whereas velocity encapsulates availability in time. Moreover, reliability, data protection and privacy are also key points that have influence on big data. In order to give more impetus to the working of Big Data, Internet of Things (IoT) emerges out as a vital source. Of late, IoT has become a common technological term for big enterprises. With the advent of smart objects growing at a rate higher than the population of world, IoT has now become an indispensable part of the modern era. However, it goes with a caution of acceptability followed by adaptability [1][2][3][4][5][6][7][8][9]. In short, Big Data Analytics refers to effective integration and efficient analysis of various forms of data over a period of time, which has the ability to cater to some impending problems. This concise documentation will deal with the areas of healthcare where Big data analytics (BDA) has been largely influential.
Encompassing the basics of IoT driven Big data analytics, the applications of it in healthcare sector will be outlined, accompanied by future expectations. Additionally, this brief outline presents a comprehensive analysis of very recent applications in this sector with special reference to Covid-19.

IoT and its journey with BDA
IoT has evolved a long way. It is a common thread, which connects all assorted devices in a synergistic way. Modern house architecture is mostly IoT enabled. Starting form Thermistors, water heater, fridge and smart lighting system, these household applications are attached/connected to each other through IoT. With the advent of RFID technology [9,10], IoT evolves dramatically engaging several aspects and stakeholders spanning academia and industry. The whole concept can be generalized as a fusion of three perspectives, viz.; orientation with things, orientation with internet and lastly orientation with semantics. Each of the perspective goes with its own agenda. Meanwhile, the fastest growing IoT spans wide range of voluminous data, which stem from strategically distributed sensors/smart objects. This in turn gives rise to assorted analytics. Yet, there is a possibility of data analytics stemming from IoT to become ineffective as well as costly; in case, we habitually costly if we always stick to cumulative transfer and subsequent handling of data in a central storage system. In order to tackle this issue, researchers develop an innovative strategy of micro service oriented platform, which will decentralize the data tree. This platform is driven by software-defined infrastructure (SDI) which will disrupt the environmental monolith of IoBDA (IoT oriented Big Data Analytics) implementation.
Accordingly, SDI comprises of software-defined network (SDN) and software-defined storage (SDS) [10][11][12][13][14][15][16][17][18]. As such, the dissociation of data transmission from IoT nodes such as switches and routers is enabled by SDN. SDS that helps in decoupling management of data store form the entire unit further accompanies this. As a result, these two vital components emerge as an integral part in facilitating workload demands via OPI in case of heterogeneous hardware. Thus, microservice-oriented platform proves to be a boon in segregating business logics, which are domain specific, from resource control and management [10,13,[15][16][17][18].

Objective of BDA and working principle
The objective of Big Data analytics is towards developing new technologies such as capturing IoT oriented devices, sensors, and mobile applications with the following outlines.
a. Collection of genomic information became cheaper b. Increasing Patient social communications in digital forms c. Accumulation of more medical knowledge/discoveries The modus operandi of BDA has been illustrated in Figure 1. As can be seen, there are components spanning from lab to pharmacy entailing patient, physician and research & development. It is also accompanied by social networking data of the patient in order to build up a synergistic effort in resource optimization. The idea of BDA is to make healthcare accessible to all with the optimal output and simultaneously saving precious time and expenditure of patient. In terms of data analysis, IoTBDA uses Monte Carlo or Convergence Analytics as per expediency [9,10]. which can cater to associated specific care paths to produce an accurate estimate of expenditure incurred. In case there is a succinct connection of care processes as well as care paths with assistance from a huge database, empirical evidence based decision for specific therapies will be materialized. To do that, there is immediate necessity of standardized and authenticated methods.

e) Optimizing workflows in Healthcare
In industrial sectors, most of the things are predictive. Hence, priority, objectives are well defined.
Nevertheless, in healthcare sector, this is completely opposite. It is quite a volatile system. Influenced by patients and their need along with service providers, the productivity becomes a lot more challenging unless the stakeholders are well apprised of the functionalities of the healthcare domain. This calls for requirement of necessary tools, which will pave way for integrated multi stream flow of data spanning electronic health records, patient monitoring data, laboratory data, nursing operation data etc. for smoother functioning along optimal utility of resource utilization.

Privacy, ethics and security
These three words are very much essential in defining data. With advent of increasing data services, everyone has access to data from multiple sources where one has the liberty of combining all of them.
This has led to misuse of this. Accordingly, question arises like destination of data, user identification and motto behind use of data. Consequently, there is an utmost need of regulation. Good news is that there has been an updated General Data Protection (GDPR) replacing the old version. As per this, it is no longer required to have a national legalization. It will cater to both public and private sector bringing all organizational sectors under its domain.

Technical challenges
In the following, technical challenges and opportunities are discussed regarding the application of Big Data technologies in healthcare.

a) Data quality
As the term goes, quality of data is very much vital. Because of expensive processes involved in medical and pharmaceutical sector, the reliability and reproducibility are two stringent measures. Hence, it is dealt with caution that how data is generated, executed and transformed before readying them for storing.
With up gradation of analytical methods and complexity of operations, source of data is extremely important as they can significantly affect the conclusion.

b) Data quantity
After quality comes another vital part data quantity. As stated earlier, BDA is actually dependent on voluminous data. Since it spans clinical, genetic, behavioral, environmental, financial and operational data, hence, there should be effective mechanism to tackle such big wealth of information so as to retrieve valuable insights towards improvement of healthcare in terms of quality and efficiency. This will ensure not only optimization of existing products and services but also propositions of new rules.

Recent application of IoT driven BDA
Since the outbreak of Covid-19 in Wuhan, China, the pandemic as declared by WHO has shattered the global scenario. Most part of the world has been undergoing the lock down phase. The SARS-COV-2 virus has caused fatalities amounting to 150 K worldwide and the no. is increasing each day. Apart from that, most of the countries are also undergoing economic turmoil. All big organizations such as FDA, CDC, USA are at a fix to find out the best possible vaccine as well as effective medicine in order to combat this Covid-19 pandemic. In this context, IoT driven BDA has been widely used by health professionals to find out best remedies in the fight against Covid-19. Accordingly, we have complied two very recent application of IoT enabled BDA.

Supercomputer Taking part in data analysis part for Covid-19
We are all aware of the much hyped IBM' Blue Gene supercomputer. Such was the power of its computation skill that it efficiently surpassed the petascale barrier around sixteen years ago. Based on that, this supercomputer played a crucial role in analyzing the sequencing of human genome, thereby paving way for designing novel drugs and treatments. It has also successfully simulated one percent of the most complex machine of the earth; human brain. Ideally, this supercomputer has been destined for such complex computing process. However, the Covid-19 since its outbreak is spreading very fast and it has infected two million people globally. As a result, this pandemic situation has to be tackled efficiently.
Accordingly, the Dept of Energy of United States of America, which has been severely affected by this

Conclusions and Recommendations
Herein, the characteristics of IoT oriented BDA in healthcare are comprehensively highlighted. It can be seen that BDA helps in rendering far-reaching, targeted and cost-effective health care. It can be understood that BDA cannot be fully exploited until and unless there is any targeted research endeavor.
Proper access and quality of big data are some impending challenges. There is a need to explore appropriate and effective ways , which is in synergy with privacy and ethical principles, to monitor big data so that one can have a deeper insight in understanding the objectives of implementation and quality which will eventually lead to developed and optimized care processes, early diagnosis etc. Figure 3 shows a visionary approach for IoT, BDA and domain expertise. As can be seen, it is imperative to have a multidisciplinary field, which positions itself at the intersection of internet of things (sensors and networks), big data technology, and domain specific analytics. This will eventually lead to a combination of the tools and methods aiding transformational solutions for industries, government, and society.

Declaration of Competing Interest:
Author declares no competing interest.