This article has been accepted for publication in a future issue of this journal, but has not been

fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JIOT.2018.2802898, IEEE Internet of
Things Journal
1

Smart Health: A Novel Paradigm to Control the

Chickungunya Virus
1
Shalli Rani, 2,*Syed Hassan Ahmed, 3Sayed Chhattan Shah
1
Department of Computer Science , Guru Kashi University, Talwandi Sabo,Bathinda (Pb.)-
151001,India
2
Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL
32816,USA
3Department of Information and Communication Engineering, University of Foreign Studies,Seoul,
South Korea
E-mail: 1 shalli@ssdwit.org,2 sh.ahmed@ieee.org, 3shah@hufs.ac.kr


Abstract— Chikungunya is a mosquito instinctive disease been made still S-Health is in early stages and this concept is
which spreads hurriedly in various parts of the country. For the evolving corresponding to another concepts of IoT: smart
awareness and prevention measure of this disease a new transportation to help the people in finding out the quick and
paradigm in smart health required to be devised. The auspicious safe ways, smart cities to tackle the problems of the citizens,
prospective of evolving Internet of Things (IoT) technologies for e-governance, smart buildings etc. Still local administration of
interconnected heterogeneous devices and objects has played
the cities is investing the funds in information and
vital role in the next generation health care systems for eminent
patient care to protect the citizens from these types of diseases. communication technologies (ICT) to facilitate their citizens
Still there is need for real time health monitoring to analyze the with novel architectures of ICT to enable intelligent decisions
patients for early preventive measures and precautions for based on social accountability and reverence to the
healthy life. Smart Health care IoT has substantial impending for technological atmosphere. Grounded on these perceptions,
the cognizance of analogues monitoring. It includes the smart cities have unrestrained boundaries and companies like
interconnected apps, objects (devices & People), communication Intel, IBM, Google etc. are developing the new software to
technologies, tracking system and patients’ knowledge base. This merge their actions and leadership in the same sector.
article presents an IoT enabled model where data collected from Numerous pertinent zones are identified where role of smart
the sensors, objects and people will be gathered at the cloud to
cities is vital such as smart health care, energy utilization,
take the preventive actions by healthcare professionals.
Precautionary measures will be taken by collecting the economy of the country, education etc. However, all the
information about causes of growth of mosquitoes. The suitability applications of smart cities are based on the sensors which
of the approach is validated at the base layer of IoT and data is update information of all the parameters comprising
transmitted to the cloud with the help of edge nodes. From temperature, humidity, pollutions, weather, traffic etc.
simulations, it is endorsed that proposed approach is better over Current devices such as iPhone, Android Phones etc. are
ME-CBCCP protocol. furnished with various sensors like front camera, location
aware, voice synthesis, and microphone etc. for accessing the
Index Terms- Smart health, Internet of Things, multimedia data through internet. However, According to
Chickungunya, IoT framework, Edge computing. Hossain et al. [1], it is still difficult to provide the quality
services to the patients due to, i) severe constraints on
resources and architectures ii) dynamic configurations of
I. INTRODUCTION portable/mobile devices iii) real time
The healthcare sector has adopted the latest technologies to monitoring/processing/storing of the patients’ data iv)
implement the concept of electronic health (Smart Health). It resource voracious client side processing. There is need of
has increased the efficiency of the healthcare system at cheap developing the new scalable architectures for the collaboration
cost. The widespread use of mobile phones with global of techniques at cloud using the new protocols, web services
positioning system (GPS) enabled capabilities has unlocked and collaboration of the servers with various portable devices.
the way to the notion of Smart Health (S-Health), which is
considered as the delivery of healthcare amenities by mobility Understanding of these parameters in healthcare system can
communications which is ensuing the S-Health alliance. S- help us to create a quality environment for citizens where
Health has an astonishing potential since it has increased the patients could be monitored through system which lasts to
exploitation of electronic health care system and all the work for extensive time. By accurate use of this information,
benefits related to the portable/mobile devices (GPS citizens and patients can be provided with smart healthcare
capabilities, contiguity, service availability 24x7 hours etc.). applications that can automatically adapt the change in the
Many advances in the field of medical services have already behavior and environment. The prime objective of this artifact
is to establish the S-Health concept on the devices which

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JIOT.2018.2802898, IEEE Internet of
Things Journal
2

could gather the data on the cloud for real time processing. S- save energy in cloud computing [4]. They proposed the time
Health will help in bridging the gap between the electronic and flow based energy consumption models for unshared and
heath and e-governance in smart cities from the perceptions of shared network devices and compared the energy computation
society and individuals. We categorize the main problems using centralized data servers using the cloud computing with
and advantages obscured by the novel concept of S-Health and applications by Nano data hubs used in Fog computing. A
converse its feasible implementation practically. novel framework of health fog for Health and Wellness
Applications was proposed in 2016 [5] and it is based on the
Rest of the article is organized as follows: 2nd section presents processing of health related data gathered from multiple
the brief overview of the prime research areas which will play resources. To reduce the cost and latency time a middle layer
a primary role in the expansion of S-Health. In this section, we was proposed between the cloud and end users. Different
define our idea of S-Health in curing the Chickunguya disease, sensing and wearable devices were reviewed to develop the
its effectiveness, relevance and feasibility. 3rd section effectual prevalent healthcare systems in [6].
describes the network design which will be used in the sensors
of mobile devices to gather the data of Chickungunya virus.
Results and discussions are provided in the 4th section tracked
with 5th section i.e. concluding observation. Big Data Processing: Many applications of IoT such as
environment monitoring, decision making, security generating
huge data, and reference applications are known as big data
II. FRAGMENTS OF S-HEALTH RIDDLE processing applications. These applications require accurate
data delivery within specific time. Authors proposed a
S-Health is a complement to the healthcare departments in framework which surfaces the simplification of the difficulty
smart cities which function in context aware atmosphere. It is in topic detection and track the monitoring of any type of
difficult to mention the state of art facts for S-Health as possibility of interest whose performance can be determined
research is still going on this field. Due to this fact, we have by analysis of tweet stream. They used fuzzy concept to
divided this riddle into five sections: Chickugunya infection, analyze time relations and sematic connotation of their
edge computing and IoT in healthcare, big data processing, content. A decision support system for customers’’ opinion to
Interoperation of Body Area Networks and Sensor Networks adapt the well-known association among obligation,
and confidentiality of data. A brief review of causes and faithfulness, quality of service (QoS), and customer
effects of Chickugunya outbreaks, use of edge computing in satisfaction, was implemented. A big data gathering algorithm
IoT based healthcare systems, big data processing of gathered was proposed to raise the need of scalability and energy
data via sensor nodes, and sharing of subtle data on the cloud efficiency for the applications of IoT in [8]. Use of
in secure method, is provided here. heterogeneous cluster for big data stream can lead to
inconsistency of data and it was demonstrated using Yahoo!S4
Chickugunya Infection: It is a mosquito borne disease and its by authors [9]. Besides the challenge of huge amount of data,
first evidence was found in southern Tanzania in 1952. Big Data poses the challenges of scalability and throughput in
Afterwards it spread across the countries and more recently to real time data processing.
India. According to Weaver [2] et a. it is found that it hit the
Kenya before spreading into Ocean Islands and India where it Interoperation of Body Area Networks and Sensor
initiated fiery epidemics including millions of people. Networks:
According to the reports mentioned by Weaver, its strains
were found in island of St. Martin in October 2013, it spread Prime component to facilitate the S-Health in an individual
throughout the Caribbean and Central America as well as into way is the opportunity of gathering heterogeneous data from
northern South America and Florida where tens of millions patients and the atmosphere. Due to the various advantages
unexposed persons were at risk. Recently, in 2015, it spread and elasticity, wireless systems are excellent candidates to be
quickly in Delhi, India. The study revealed that diagnosis of the communication medium from the users to the cloud
this disease is usually clinical, due to the association of infrastructures. However, due to heterogeneity of objects, it is
arthralgia and dire fever is prognostic in extents where it is difficult to get the advantage of interoperability. Radio-electric
prevalent and where epidemics have arisen. interference is required to be avoided during its deployment.

Edge computing and IoT in Healthcare: Authors presented

a novel intelligent value stream-based food traceability cyber Security and Data Privacy: Data protection and privacy is
physical system approach integrated with enterprise fundamental right that is mandatory to be reflected. In
architectures, EPCglobal and value stream mapping method healthcare systems, it is even more crucial than in other
by Fog computing (Edge computing) network for traceability milieus. For example, the unremitting monitoring of patients
cooperative proficiency. In this methodology, authors can be perceived as the incursion of privacy and it should be
evaluated how IoT based cyber physical system can extend the sensibly considered to discontinue patients, resisting from use
efficacy of food traceability system by means of extremely of monitoring. Information accession privately and
value aided visible process by value stream mapping anonymous methods will play prominent role in S-Health.
technique. Authors reviewed the conservation of energy Security protocols are required to be developed based on
techniques and proposed a new way that is fog computing to public key cryptography. Biometric features (fingerprint,

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2327-4662 (c) 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JIOT.2018.2802898, IEEE Internet of
Things Journal
3

ECG, iris etc.) are widely implemented. To identify the people cities, where data between the patients’ and doctors’ is
and physical objects radio technologies like frequency exchanged with the help of mobile phones. On the top of the
identification (RFID) are used. Secure communication, two, third part of architecture is offered where new protocols,
authentication and recognition is paramount for S-Health. big data techniques, decision making policies will be
Cloud based architecture for medical Wireless Sensor implemented and these communication techniques will give
Networks (WSNs) is proposed in [10] and it provides integrity rise to the S-Health i.e. where data will be exchanged in quick
and confidentiality of medical data using different and reliable way. From this architecture the definition of S-
mechanisms. Health can be professed as:

Other Interrelated Areas “Smart health is the establishment of health facilities by

In addition to the above discussed segments used in S-Health , context aware and intelligent framework of smart cities.”
there are many other areas which are linked with S-Health
[11]. However, to elaborate all of them here is beyond the S-Health is quite different from e-health, because S-Health can
scope of this article. Still we enumerate the patients’ be facilitated by static sensors and it might not use the mobile
supervision, remote care, data handling and mining, databases sensors. Healthcare system can be identified by the following
and knowledge acquisition, cloud privacy and security, scenario examples.
telemedicine etc.
1. Traditional Health: In this system, patient visits the doctor
for routine checkup /in case of illness and doctor uses the
III. SMART HEALTH CARE SYSTEM
basic tools for the same or vice versa.
2. E-health: It is the subset of communication technologies;
Concept of S-Health is perceived as the complement of e- involves the mobile apps and database servers to store the
health (Mobile Health) in the framework of smart cities. Local records of patients.
and state governments are trying to foster the development and 3. Tele-health: it encompasses a wide group of technologies
deployment of smart cities where citizens could enjoy the and strategies to transport virtual medical, education and
quality and healthy life with minimum risks to health. The health services. It is a collection of methods to extend the
adaptation of e-health and smart cities are trendy and health care and medical education.
converged in to communal point. Communication 4. S-Health: To obtain the information from the interactive
technologies and new architectures of smart cities can be more device and to check and capture the cause of diseases for
influential with the inclusion of telemedicine and e-health for pretreatment purposes, is S-Health. The patient can evade
pervasive idea i.e. S-Health. S-Health is related to telehealth areas which could be harmful or virus infected. Patient
(t-health) concept which includes the remote care of the can opt for the better route for himself and precautionary
patients by telecommunication technology. By adding the measure action can be taken in the virus infected areas by
intelligent decisions making policies, energy conserving Municipal Corporation.
techniques, fast communication, and fast delivery of data t- 5. E-health and T-health extended with S-Health: A person
health can be converted into S-Health. wearing ring with accelerometers and dynamic parameters
monitoring proficiencies has met with an accident. The
body sensor network will detect the unusual activity and
will report to the S-Health architecture. Appropriate
actions like dispatch of ambulance will be taken. In other
example, when the epidemic is spread throughout the
country, the causes and the most affected areas with this
epidemic can be monitored. Medicine spray can be done
in those areas on priority basis. The main objective of
the S-Health is to promote the healthy life within society
in a secure, secretive, proficient and viable way by
merging the principles and techniques of t-health and e-
health in novel paradigm of pervasive health.

With the provision of new protocols, new policies and

Figure 1: Smart Health Conceded from Tele-health, E-health and Operating strategies novel concept of S-Health can be extended from
Protocols and New Intelligent Communication Techniques coverage of health in traditional manner to modernization with
new framework of healthcare. In this paradigm, sensors will
play am important role of gathering the data of patients and
Figure 1 represents our concept of S-Health driven from the areas which are highly infected. The development of new
combination of e-health, t-health and new techniques. In the models and network design will help in implementing the
first part, doctors’ and patients’ communication is presented idea. In this article we have proposed a new design to gather
where they communicate with each other with the help of the data of the Chickungnya patients and the areas where it is
internet database clouds. In the second part, (e-health) is spreading quickly. It will contribute to the collection of data
shown which is emerging technology to be used in smart

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2327-4662 (c) 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JIOT.2018.2802898, IEEE Internet of
Things Journal
4

for research at reduced cost and will help in the global metrics. Edge servers will be deployed at the predefined
advancements of society. locations in the city and they will collect the data from the
users and process it before transmitting to the cloud. They
will collect the symptoms of Chickungunya virus and will
IV. PROPOSED ARCHITECTURE AND PERFORMANCE ANALYSIS be capable of tracing the location and will transport it for
further analysis at cloud. Edge servers can be extended to
As it is shown in figure 1, in T-health section, data is gathered cover a state, or country. Edge servers are used to monitor
at the cloud (backend), and in e-health section data is collected the problem of Chickungunya virus.
from the mobiles (front end) and it is stored in the sensors, it is
transmitted by the novel techniques and protocols which is the 3. Data Assemblage
middle layer and helps is transporting the data with
conservation techniques. Cloud storage and processing Once the information about the users is collected at the edge
section composed of data gathering, information shielding, servers and is transported to the cloud, analysis of data is
GPS based categorization and risk computation, and health performed at the cloud. Data is shared with the hospitals,
care data transmission. The mobile phones and mosquito healthcare departments, and doctors in secure way. The
sensors [12] are used for data retrieval and transportation to information shown in table 1, will be saved at the servers
the cloud. The cloud server is connected to the middle layer (about personal details, location and virus details) and will
i.e. protocols layer and which transmits the data from the be used for the analysis. This information will be updated
sensors and mobile phones. The following subsections throw time to time.
light on the proposed model.

1. Data Accession and Transmission

Each user is registered with the system by entering

personal details through the mobile app installed on the
cell phones. They are provided with the ref. no. generated
from the system. The mobile phones will check the
Chickugunya symptoms time to time and will update the
information on the cloud. The personal details of the users
as well as their location information will be updated,
because main motive is to find out the most affected areas Figure 2: Communication of Edge Servers with Cloud
of mosquito breeding. Highly dense mosquito areas and TABLE 1: DATABASE AT THE CLOUD SERVER
breeding will be captured through the sensors placed on Personal Location/Mosquito Symptom Existence of
the locations of smart city. Along with this information, Attribute Information Parameters the
sensors will also examine humidity, temperature and other Symptoms
values which help in the growth of mosquitoes. These Ref. No. Mosquito dense Join Pain Y/N
environmental attributes are captured and stored in the Area
cloud which helps in predicting the mosquito sites. The Name Breeding location Fatigue Y/N
locations where sensors are not deployed, the information
Age Humidity Lower Back Y/N
can be transmitted through the images of locations being
Pain
captured by the users and transmitted through the mobile
Sex(m/f) Temperature Nausea Y/N
app. With the help of global positioning system (GPS),
Cell Location Image Fever Y/N
coordinates of the images will be automatically
reorganized and will be stored with other details of Number
images. This information can be accessible to the Address Mosquito density Skin Rashes Y/N
hospitals, doctors and various healthcare departments for
the preventive measures. 4. Security

2. Edge Computing Prime concern of the cloud servers is to protect the

information of the users and from the above table coulmn1
Sensor nodes and cell phones are used to sense and gather represents the sensitive information about the users which is
the data. This data is processed before transmitted to the protected and will not be shared unless or until it is
cloud. It is difficult to process all the data at the cloud, and required.
it will take more time to transmit the raw data, as it is
collected. Edge computing acts as the bridge between the 5. Network Design
storage cloud and the end users (figure 2). Services of the
cloud computing can be extended to edge objects of the As in the figure 1, we have shown the middle layer where
network. It can offer computation, storage and processing new protocols will be required to implement for the fast
services to the users in less time and at cheap cost with QoS transmission of data with network stability. If the network
will be stable, only then the real time data can be gathered

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This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JIOT.2018.2802898, IEEE Internet of
Things Journal
5

accurately. Concentrating on this point, we have design a In the testing of the proposed model the steps which are
network where area is divided into four equal parts, and followed are: i) data generation, ii) testing of FKNN and iii)
each part has one sink deployed in center of the location. It testing at the cloud and risk assessment [12]. Along with all
has unlimited power supply and they are responsible to these steps, network design is proposed in this paper for
transmit the data to the cloud. Data will reach to the sinks stable working of sensors and edge server. The protocol is
with the help of cluster heads (CHs) as shown in figure 3. implemented in MATLAB which is QoS protocol for IoT.
Design of this protocol is changed (shown in figure 3) as
6. GPS-based Hazard Evaluation compared to previous work i.e. ME-CBBCP [13] and
algorithm of transmission and modules are same. With the
Chickungunya virus is spread by the mosquitos’ bites and is help of this protocol on the middle layer of (figure 1) data is
spread out in the human body through the blood. It is picked transmitted in realistic way. The data should be transmitted
by the other mosquitoes’ bite and injected in to other human to the cloud in real time manner and in fastest ways which
beings’ body. For the information of mosquitoes dense area, require a stable and scalable network. With the proposed
required breeding parameters and infected people, GPS will scheme, network is achieving these properties and can be
collect the precise data. This type of information is crucial observed from the figures (4-5):
for the healthcare departments and it is very difficult for
them to get this data. Risk prone areas are identified by the
geographic location of the infected persons.
Proposed Protocol
4
x 10 ME-CBCCP
EESAA
10 Mod-LEACH
ERP
8

Time in Seconds
6

0
6000
1500
4000
1000
2000
500
Number of Rounds 0 0 Number of Alive Nodes

Figure 3: Network Design for Edge Server Protocol Figure 4: Stability of Network With Reference to the Alive
Sensors
Once these areas are identified, the alert messages can be
issued to the citizens for safety measures. Edge servers will Figure 4, shows the stability of network in terms of alive
continuously monitor the patients and the mosquitoes nodes after 5000 rounds of data transmission. The proposed
breeding sites and will operate and update in real time. The protocol has 11 nodes alive after these simulations as
probability of risk prone areas can be represented on the compared to the other protocols (where all the nodes are
Google map. It will help the government to control the dead). This graph shows the comparison according to two
epidemic before it becomes severe. The FKNN method and parameters time and nodes. According to both parameters,
algorithm as proposed in [12] will be used to track the proposed approach is performing well. It is taking less
record of patients. execution time and some nodes are alive after data
transmission which is much required property in smart
7. Communication Regarding Preventive Measures applications.
This module will help in transmitting the alert messages to To make the things more clear for efficient communication of
the users for Chickungunya virus. These messages will help data in smart health application, comparison is done on the
in preventing the development of mosquitoes and text basis of dead nodes (figure 5) along with alive nodes. It shows
message will be sent to the users to make them aware of the the persistence of the network and validates the proposed
risk prone areas and precautionary steps. These types of approached in terms of energy and time.
messages will be sent as the warning or reminder to make
citizens aware of the epidemic. Messages will also be useful
for the concerned departments (healthcare agencies,
hospitals etc.).

8. Performance Analysis

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2327-4662 (c) 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JIOT.2018.2802898, IEEE Internet of
Things Journal
6

A new methodology is devised to transmit the data to the

Proposed Protocol cloud and new approach is validated over existing
4
x 10 ME-CBCCP protocols ME-CBCCP, EESAA, Mod-LEACH and ERP,
EESAA
10 Mod-LEACH in terms of stability, energy and time. It also proves that
8
ERP edge computing is the best way to handle the data at the
cloud side. Security implementation at the edge node will
Time in Seconds

6 be considered in future work.

4
Acknowledgement: This work is supported by Hankuk
2 University of Foreign Studies Research Fund of 2017 and
0 National Research Foundation of Korea
6000 (2017R1C1B5017629)
1500
4000
1000
2000
500
Number of Rounds 0 0 Number of Dead Nodes REFERENCES

Figure 5: Stability of Network With Reference to the Sensors [1] M. S. Hossain, & G. Muhammad, “Cloud-assisted industrial internet of
with Depleted Battery things (iiot)–enabled framework for health monitoring”. Computer
Networks, vol. 101, pp. 192-202, 2016.

The proposed protocol is working better in terms of network [2] S.C. Weaver, & M. Lecuit, “Chikungunya virus and the global spread of a
stability as compared to IoT protocol ME-CBCCP [13] and mosquito-borne disease” . New England Journal of Medicine, vol. 372(13),
other traditional protocols. pp. 1231-1239, 2015.

[3] R.Y. Chen, “An Intelligent Value Stream-Based Approach to

Collaboration of Food Traceability Cyber Physical System by Fog
V. CONCLUDING OBSERVATION Computing.” Food Control, vol. 71, pp. 124–136,
doi:10.1016/j.foodcont.2016.06.042, 2017.
One of the fatal insect that blowouts several pathogens like
Chickungunya, Dengue etc. is mosquito. It is predominant [4] F. K. Jalali, R. Hinton, T. Ayre, Alpcan, and R. S. Tucker, “Fog
in various parts of the world and day by day affecting many Computing May Help to Save Energy in Cloud Computing.”, IEEE Journal
on Selected Areas in Communications, vol. 34 (5), pp. 1728–1739.
citizens. In this article, a cloud based system is presented doi:10.1109/JSAC.2016.2545559, 2016.
which collects the data from the mobile phones and sensors
via edge servers. It uses the Wireless Communication [5] M. Ahmad, M. B. Amin, S. Hussain, B. H. Kang, T. Cheong, and S. Lee.
Technology and Edge computing. The prime objective of 2016. “Health Fog: A Novel Framework for Health and Wellness
Applications.”, The Journal of Supercomputing. doi:10.1007/s11227-016-
the article is to introduce the new framework to implement 1634-x.
the smart health system and can be beneficial to take the
preventive measures before the severe spreading of [6] Y.L.Zheng, X.R. Ding, C. C. Y. Poon, B. P. L. Lo, H. Zhang, X.L. Zhou,
Chickngunya epidemic. The proposed framework is G.-Z. Yang, N. Zhao, and Y.-T. Zhang, “Unobtrusive Sensing and Wearable
Devices for Health Informatics.” IEEE Transactions on Biomedical
designed to handle the huge data of patients with stability Engineering, vol. 61 (5), pp. 1538–1554. doi:10.1109/TBME.2014.2309951,
protocol at the edge servers for realistic communication. 2014.
Proposed methodology offers the following benefits:
[7] C.D. Maio, G. Fenza, V. Loia, and F. Orciuoli, “Unfolding Social Content
Evolution along Time and Semantics.” Future Generation Computer Systems
 Helps in the improvement of Patients’ quality life. vol. 66, pp. 146–159. doi:10.1016/j.future.2016.05.039, 2017.
 Timely recognition of Chickugunya infection
accompanying with patients and reducing the spread [8] S. Rani, S.H.Ahmed, R.Talwar, & J.Malhotra, “Can Sensors Collect Big
Data? An Energy Efficient Big Data Gathering Algorithm for WSN”. IEEE
of infection.
Transactions on Industrial Informatics, vol 13(4), pp. 1961-1968, 2017.
 Enhancements in the analysis process, handling and
future verdicts concerned with patients’ health. [9] Xhafa, F., V. Naranjo, L. Barolli, and M. Takizawa, “On Streaming
 Monitoring the huge number of patients regardless Consistency of Big Data Stream Processing in Heterogenous Clutsers”. In
Proc. of 18th international conference on Network-Based Information Systems
of their location (NBiS), pp. 476– 482. doi: 10.1109/NBiS.2015.122, 2015.
 Supports healthcare departments and other agencies
for early preventive measures to control Chickugunya [10] A. Lounis, A. Hadjidj, A. Bouabdallah, and Y. Challal, “Healing on the
Virus. Cloud: Secure Cloud Architecture for Medical Wireless Sensor Networks.”
Future Generation Computer Systems, vol. 55, pp. 266–277. doi:10.1016/j.
 Stability achieved at the edge servers help in the future.2015.01.009, 2016.
realistic communication.
 Benefit for the doctors and physicians to work [11] Solanas, Agusti, et al. "Smart health: a context-aware health paradigm
efficiently and for logical/precise decisions. within smart cities." IEEE Communications Magazine, vol. 52(8), pp. 74-81,
2014.

*Corresponding Author
2327-4662 (c) 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/JIOT.2018.2802898, IEEE Internet of
Things Journal
7

[12] S. Sareen, S.K.Gupta, & S.K.Sood, “An intelligent and secure system for [13] S.Rani, R. Talwar, J. Malhotra, S.H.Ahmed, M.Sarkar, & H. Song, “A
predicting and preventing Zika virus outbreak using Fog novel scheme for an energy efficient Internet of Things based on wireless
computing”. Enterprise Information Systems, pp. 1-21, 2017. sensor networks”. Sensors, vol. 15(11), pp. 28603-28626, 2015.

Shalli Rani received the MCA degree from Maharishi

Dyanand University, Rohtak in 2004 and the M. Tech. degree
in Computer Science from Janardan Rai Nagar Vidyapeeth
University, Udaipur in 2007. Later she completed her Ph.D
degree in Computer applications from IKG Punjab Technical
University, Jalandhar, in 2017. She is an Associate Professor
at Guru Kashi University, Talwandi Sabo(Pb.), India. She
served as an Assistant Professor at the S.S.D Women’s
Institute of Technology, Bathinda (Punjab), India for 10 years.
She has published more than 15 papers in international
journals, International and national conferences and one book
at international level. Her main area of interest and research is
on Wireless Sensor Networks, Cyber Physical Systems ,
Internet of Things and Ad-hoc networks. She received a young
scientist award in February 2014 from Punjab Science
Congress, in the same field.

Syed Hassan Ahmed(S'13, M'17) received his B.S in

Computer Science from Kohat University of Science and
Technology, Pakistan. Later, he completed his Masters
combined Ph.D. in Computer Engineering from School of
Computer Science and Engineering, Kyungpook National
University (KNU), Republic of Korea in 2017. In summer
2015, he was a visiting researcher at the Georgia Institute of
Technology, Atlanta, USA. Dr. Ahmed authored/co-authored
over 100 International Journal, Book Chapters and Conference
articles in addition to two Springer brief books. From year
2014 to 2016, he consequently won the Best Research
Contributor award in the workshop on Future Researches of
Computer Science and Engineering, KNU, Korea. In 2016, he
also won the Qualcomm Innovation Award at KNU. Currently
Dr. Hassan is a Post Doctoral fellow in the department of
Electrical and Computer Engineering, University of Central
Florida, Orlando, USA, where his resaerch intrestes include
Sensor and Ad-hoc Networks, Cyber Physical
Systems,Vehicular Communications, and Future Internet.

Sayed Chetan Shah is an assistant professor of computer

science in the department of information communication
Engineering at Hankuk University of Foreign Studies, Korea.
He is also Director of Mobile Grid and Cloud Computing
Laboratory. His research interests lie in the fields of parallel
and distributed computing systems, Mobile Computational
clouds and Ad-hoc networks. He received his Ph.D in
computer science from Korea University in 2012and his M.S.
in Computer and Emerging Sciences in 2008. Prior to joining
HUFS, He was a senior researcher at the Electronics and
Telecommunications Research Institute, South Korea and
Engineer at the National Engineering and Scientific
Commission, Pakistan. He also held faculty positions at Seoul
National University of Science and Technology, Korea
University, Dongguk Univsersity, Hamdard University and
Isra University.

*Corresponding Author
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