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Content uploaded by Erdal Erdal
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All content in this area was uploaded by Erdal Erdal on Jan 30, 2020
Content may be subject to copyright.
The impact of technology trends on
healthcare systems: A study on
opportunities and threats
Erdal Erdal
Assistant Professor, Department of Computer Engineering, Kırıkkale University, Kırıkkale,
Turkey
ABSTRACT
The importance of health in human life is enormous.
The technologies developed and the studies in this
field have caused differences in the field of health as
in all areas. The aim of this study is to examine the
needs in the field of health and to set the criteria for
determining the most appropriate technology. In the
study, three new technology trends in literature are
examined. The concepts of edge computing, fog
computing and cloud computing were evaluated
within the scope of the study. The literature of these
three concepts has been examined and the areas
where they can be preferred in the field of health
services are presented. In addition, at the end of the
study, the necessity of Futurist Healthcare systems,
which will cover all health services, is stated.
Keyword: Healthcare, Information and
communication technologies, Infrastructure, Cloud
computing, Fog computing, Edge computing
I. INTRODUCTION
The importance of health in people's lives is
undisputed. With the development of technology,
great changes and developments have started in the
field of health. Together with these changes,
technology has taken its place among the
indispensable elements of the health field.
Applications and systems which are revolutionary in
health have been developed. In this way, changes
that have touched the lives of people have occurred.
However, it is inevitable for the health sector to
adapt to these developments with the advancing
technology. In the technological field, classical and
traditional data centers have been used decades ago.
This phenomenon is still working and serving the
technology infrastructure. However, with the
deficiencies and technological developments, the
traditional data centers have been replaced by
different technological infrastructures. Traditional
data centers nowadays appear to have been replaced
by cloud computing, fog computing and edge
computing. The main reasons underlying this need
for change are listed below.
Increased amount of data to be stored
The need to share and transmit stored data
The requirement to analyze stored data
The aim of this study is to examine the technologies
that can be used in health systems and health
infrastructure. As a result of the examination,
suggesting the most suitable infrastructure for the
target will provide great improvements in health
services.
However, prior to the determination of the
infrastructure that is most suitable for the needs, it is
necessary to identify the substructures that come
with technological developments and to identify
their advantages and disadvantages.
II. LITERATURE REVIEW
Before the detailed study of the studies to be carried
out, it should be mentioned in the studies conducted
in the past period in the literature.
In order to reveal the effects of technological
developments on the health field clearly, the studies
have been examined by giving a date range to
technological concepts. At this stage, the surveys on
the adaptation of Information and Communication
Technologies (ICT) to the field of health services
were evaluated in order to list more systematic and
clear studies.
It will not be wrong to start with cloud computing,
which is the most commonly heard technology
concept in this field. As seen in the literature studies,
cloud computing is of great importance in the field
of health services. In addition, cloud computing is
still the preferred and used infrastructure [1-5].
Another popular technology developed in parallel
with technological developments is the Internet of
Things (IoT) [6]. On the basis of IoT there is the
creation of a global network structure with data from
physical devices. In this way, it is aimed to connect
the physical devices to each other via this network.
Although it was initially restricted by radio
frequency recognition (RFID) technology, the
currently spoken IoT has reached different stages.
Nowadays, when the concept of IoT is talked about,
not only RFID technology, but also global
positioning devices (GPS), mobile devices and all
devices connected to the network actually come to
mind [6]. As mentioned before, no progress can be
left unresponsive to technological developments,
and the healthcare field has not been indifferent to
this development. Studies in the field of healthcare
services and studies on IoT are available in the
literature [2, 7-11].
Another subject in the literature is big data. Today,
the importance of large data has increased. One of
the main reasons for this importance is the described
IoT technology. Considering data from patients,
doctors, diagnoses, treatments and hospitals in the
field of health, the big data issue in this area is
undisputed. Therefore, studies on the management of
big data in the field of health have been conducted in
the literature [2, 12-15].
In addition, there are a lot of concepts used in the
field of healthcare with technological developments.
Wireless body area networks (WBAN) [16],
Wireless Sensor Network (WSN) [17], Machine-to-
Machine communication (M2M) [8], Network
technologies [2], 3D printing [18], robotics [19],
social networks [20] and artificial intelligence [21]
issues are out of scope.
In addition to cloud computing, there are solutions
which are an alternative to cloud computing and the
deficiencies in cloud computing are eliminated. The
concepts of edge computing and fog computing will
be studied in this study. There are also investigations
and investigations on these issues in the health care
literature [2, 22-24].
The concepts of cloud computing, which has become
a phenomenon in this field with the fog computing
and edge computing in the field of health services,
have been determined as the scope of this study.
III. TECHNOLOGY TRENDS
Cloud computing, fog computing and edge
computing topics will be examined in this heading.
The architectures, advantages and disadvantages of
these three concepts will be described. In order to
select the most appropriate service type in the field
of health, these concepts need to be detailed.
A. Cloud Computing
Cloud computing is the general name of Internet-
based IT services for computers and other devices,
providing computer resources that can be used at any
time and shared between users [25]. In the literature,
there are studies related to cloud computing-based
applications and services in the field of health
services [3, 4, 25-27].
The studies in the literature have been examined and
the highlights are listed are below [3, 4, 25-27].
Using cloud computing can develop and
improve healthcare sector, also bring
important opportunities.
The transmission of all data over the
internet causes concerns about the safety
and confidentiality of the patient data and
data management. Studies are still
continuing in this area.
Cloud computing power can be used in
decision support mechanisms in healthcare.
Cloud computing makes it easier to process
big data analyzes in the health field.
High bandwidth requirements due to data
transfers required.
Another hot topic in the literature is IoT and
cloud computing is insufficient on this
technology which is a big problem [28].
Cloud computing is a disadvantageous in
terms of integrating with the types of
services it provides such as Software as a
Service (SaaS), Platform as a Service
(PaaS) and Infrastructure as a Service
(IaaS) [29].
Storing files in the cloud in a distributed
storage systems [30].
Difficulties in analyzing large data due to
distributed file or data structure [31].
B. Fog Computing
Fog computing is the architecture that suggests that
smart devices should be analyzed first at a local point
and sent to central servers, as opposed to the
architecture that allows the data to be sent and
processed to a central server [32, 33]. The approach
based on fog computing is filtering, processing and
storage operations by establishing an intermediate
layer just before all data is kept on the cloud.
As of 2020, the number of IoT devices in the world
is estimated to be 5.63K [34]. As can be seen in the
estimates, it is certain that IoT will remain a hot topic
for a long time. Developments in IoT technology
will make this technology preferred in health sector
as well. Therefore, it is imperative that the
technological trend, which will be the subject of
choice in the field of health, be in line with the IoT
technology. In response to IoT problems in cloud
computing, the proposed system provides solutions
to IT problems.
For a clearer understanding of the concept of fog
computing, an exemplary architecture from a study
is shown in Figure 1 [35].
Figure 1: Sample fog computing architecture [35]
The studies about fog computing in the literature
have been examined and the highlights are listed are
below [23, 36, 37].
Fog computing is suitable for real-time
applications in healthcare services with low
latency and high response time.
It is suitable for use with IoT technology
used in healthcare services and
applications.
It provides big data analysis with its
processing power and storage space with its
local architecture.
It offers better scalable architecture than
cloud computing.
More powerful distributed processing
thanks to local processing power.
Safer and fault tolerant architecture thanks
to local operations.
C. Edge Computing
Edge computing and fog computing have similarities
because they provide closer data processing and data
collection. However, although there are similarities
between these two concepts, they have very
important differences. The main difference between
these two new technology trends is where the
calculation and processing power are located. Sis
computing includes processing on the local area
network (LAN). In contrast, edge computing is
based on the placement of computing and processing
power into devices. In fact, fog computing uses edge
devices over LAN.
The need for the development of edge computing is
IoT technology, just as in the case of fog computing.
In the literature, the studies related to edge
calculation are examined and the important points
are listed below [22, 38, 39].
In e-healthcare or telemedicine applications
and services, intensive patient data is
received through wireless sensors. In such
cases, edge computing can respond to this
need.
It is fully compatible and suitable for IoT
technology.
Cost is higher than cloud computing.
It is suitable to be preferred in applications
with low latency period.
It is required to have the storage capacity
and processing capacity of the devices it
contains.
IV. SUGGESTIONS
The impact of technology trends on healthcare
systems has been examined. Cloud computing, fog
computing and edge computing fields, which are one
of the newest trends in technology, have been
included in the study. Apparently it is not possible to
talk about a single technology trend for every health
system. Therefore, health areas are categorized
according to their needs.
As a result of this study, the following suggestions
have been presented.
A. Traditional Health Systems
Cloud computing systems meet the needs of today's
traditional health systems. Cloud computing systems
are inherently more cost effective than traditional
data centers. Intensive data flow is available in the
systems used in health services. Therefore, the
bandwidth requirement of this system is enormous.
In the health care system, patient records, that is,
confidential information about the patients are
available. Storing these data in the cloud brings to
mind the safety issue. It is stated that there are studies
in the literature on this subject.
B. IoT Based Health Systems
IoT is one of the new trends of the technology. IoT
studies are also carried out in the field of health
services. The IoT technology is inherent in its logic
and it receives data from all edge devices. Given the
data flowing from these devices, the amount of data
reaches enormous dimensions. The use of edge
computing in such health applications is considered
appropriate. However, at all edge points, data
processing and storage needs cost.
C. Real-Time Application Based Health
Systems
Using cloud computing in health systems where real-
time services are available may not be considered
very appropriate as it may cause loss of time and
bandwidth compression. Real-time applications are
critical systems that are inherently in need of
immediate response. In such systems, fog
information or edge computing can be preferred
according to more detailed needs. In this way, it is
possible to transfer data independently from internet
and bandwidth.
D. Futurist Healthcare Systems
The issue mentioned in this category is to provide the
most optimal solution covering all health systems.
The targeted solution should include both fog
computing, edge computing and cloud computing
based on the infrastructure needed. Real-time
applications can communicate via cloud computing,
traditional health applications through fog and edge
computing. However, there is a need for an entire
architecture and framework that can meet this need.
V. CONCLUSION
In this study, new technology trends in health
services systems and applications are examined and
recommendations are presented. Developing
technology affects all areas of our lives. However,
every technological trend and concept may not be
good or appropriate for every application. Therefore,
fog, edge and cloud computing technologies which
can be used in health system are examined and
suggestions are presented as a result of
examinations. A useful research has been introduced
for new systems to be developed and new
applications to be developed in the field of health. It
was also determined that there was a need for a
framework where all these technologies were
brought together.
REFERENCES
1. Abbas, A. and S.U. Khan, A review on the
state-of-the-art privacy-preserving
approaches in the e-health clouds. IEEE J
Biomed Health Inform, 2014. 18(4): p.
1431-41.
2. Aceto, G., V. Persico, and A. Pescapé, The
role of Information and Communication
Technologies in healthcare: taxonomies,
perspectives, and challenges. Journal of
Network and Computer Applications, 2018.
107: p. 125-154.
3. Calabrese, B. and M. Cannataro, Cloud
Computing in Healthcare and Biomedicine.
Scalable Computing: Practice and
Experience, 2015. 16(1).
4. Ermakova, T., et al. Cloud Computing in
Healthcare – a Literature Review on
Current State of Research. in Proceedings
of the Nineteenth Americas Conference on
Information Systems. 2013. Chicago,
Illinois.
5. Pino, C. and R.D. Salvo. A Survey of Cloud
Computing Architecture and Applications
in Health in Proceedings of the 2nd
International Conference on Computer
Science and Electronics Engineering. 2013.
Paris, France: Atlantis Press.
6. Qi, J., et al., Advanced internet of things for
personalised healthcare systems: A survey.
Pervasive and Mobile Computing, 2017.
41: p. 132-149.
7. Darshan, K.R. and K.R. Anandakumar, A
comprehensive review on usage of Internet
of Things (IoT) in healthcare system. 2015:
p. 132-136.
8. Geng, W., et al., M2M: From mobile to
embedded internet. IEEE Communications
Magazine, 2011. 49(4): p. 36-43.
9. Laplante, P.A. and N.L. Laplante, A
Structured approach for describing
healthcare applications for the Internet of
Things. 2015: p. 621-625.
10. Riazul Islam, S.M., et al., The Internet of
Things for Health Care: A Comprehensive
Survey. IEEE Access, 2015. 3: p. 678-708.
11. Yeole, A.S. and D.R. Kalbande, Use of
Internet of Things (IoT) in Healthcare.
2016: p. 71-76.
12. Archenaa, J. and E.A.M. Anita, A Survey of
Big Data Analytics in Healthcare and
Government. Procedia Computer Science,
2015. 50: p. 408-413.
13. Ramesh, D., P. Suraj, and L. Saini, Big data
analytics in healthcare: A survey approach.
2016: p. 1-6.
14. Sun, J. and C.K. Reddy, Big data analytics
for healthcare. 2013: p. 1525.
15. Zou, Q., et al., Survey of MapReduce frame
operation in bioinformatics. Brief
Bioinform, 2014. 15(4): p. 637-47.
16. Filipe, L., et al., Wireless Body Area
Networks for Healthcare Applications:
Protocol Stack Review. International
Journal of Distributed Sensor Networks,
2015. 2015: p. 1-23.
17. Ko, J., et al., Wireless Sensor Networks for
Healthcare. Proceedings of the IEEE, 2010.
98(11): p. 1947-1960.
18. Malik, H.H., et al., Three-dimensional
printing in surgery: a review of current
surgical applications. J Surg Res, 2015.
199(2): p. 512-22.
19. Ciuti, G., et al., Frontiers of robotic
endoscopic capsules: a review. J Microbio
Robot, 2016. 11(1): p. 1-18.
20. Griffiths, F., et al., Social networks--the
future for health care delivery. Soc Sci
Med, 2012. 75(12): p. 2233-41.
21. Kassahun, Y., et al., Erratum to: Surgical
robotics beyond enhanced dexterity
instrumentation: a survey of machine
learning techniques and their role in
intelligent and autonomous surgical
actions. Int J Comput Assist Radiol Surg,
2016. 11(5): p. 847.
22. Chen, M., et al., Edge cognitive computing
based smart healthcare system. Future
Generation Computer Systems, 2018. 86: p.
403-411.
23. Kumari, A., et al., Fog computing for
Healthcare 4.0 environment: Opportunities
and challenges. Computers & Electrical
Engineering, 2018. 72: p. 1-13.
24. Rahmani, A.M., et al., Exploiting smart e-
Health gateways at the edge of healthcare
Internet-of-Things: A fog computing
approach. Future Generation Computer
Systems, 2018. 78: p. 641-658.
25. Ali, O., et al., Cloud computing-enabled
healthcare opportunities, issues, and
applications: A systematic review.
International Journal of Information
Management, 2018. 43: p. 146-158.
26. Al-Ruithe, M., E. Benkhelifa, and K.
Hameed, Current State of Cloud
Computing Adoption – An Empirical Study
in Major Public Sector Organizations of
Saudi Arabia (KSA). Procedia Computer
Science, 2017. 110: p. 378-385.
27. Bayramusta, M. and V.A. Nasir, A fad or
future of IT?: A comprehensive literature
review on the cloud computing research.
International Journal of Information
Management, 2016. 36(4): p. 635-644.
28. Díaz, M., C. Martín, and B. Rubio, State-of-
the-art, challenges, and open issues in the
integration of Internet of things and cloud
computing. Journal of Network and
Computer Applications, 2016. 67: p. 99-
117.
29. Souri, A., N.J. Navimipour, and A.M.
Rahmani, Formal verification approaches
and standards in the cloud computing: A
comprehensive and systematic review.
Computer Standards & Interfaces, 2018.
58: p. 1-22.
30. Leavitt, N., Storage Challenge: Where Will
All That Big Data Go? Computer, 2013.
46(9): p. 22-25.
31. Talia, D., Clouds for Scalable Big Data
Analytics. Computer, 2013. 46(5): p. 98-
101.
32. Aazam, M., S. Zeadally, and K.A. Harras,
Offloading in fog computing for IoT:
Review, enabling technologies, and
research opportunities. Future Generation
Computer Systems, 2018. 87: p. 278-289.
33. Zhang, P., M. Zhou, and G. Fortino,
Security and trust issues in Fog computing:
A survey. Future Generation Computer
Systems, 2018. 88: p. 16-27.
34. Research, G.V., Fog Computing Market
Analysis By Solution, By Hardware, By
Application, By Region, & Segment
Forecasts, 2018 - 2025. 2017. p. 100.
35. Al Hamid, H.A., et al., A Security Model for
Preserving the Privacy of Medical Big Data
in a Healthcare Cloud Using a Fog
Computing Facility With Pairing-Based
Cryptography. IEEE Access, 2017. 5: p.
22313-22328.
36. Mutlag, A.A., et al., Enabling technologies
for fog computing in healthcare IoT
systems. Future Generation Computer
Systems, 2019. 90: p. 62-78.
37. Yassine, A., et al., IoT big data analytics for
smart homes with fog and cloud computing.
Future Generation Computer Systems,
2019. 91: p. 563-573.
38. Alam, M.G.R., et al., Edge-of-things
computing framework for cost-effective
provisioning of healthcare data. Journal of
Parallel and Distributed Computing, 2019.
123: p. 54-60.
39. Olaniyan, R., et al., Opportunistic Edge
Computing: Concepts, opportunities and
research challenges. Future Generation
Computer Systems, 2018. 89: p. 633-645.