IoT in Healthcare Industry: Literature Review and Analysis

This report is a comprehensive literature review and annotated bibliography that explores the applications and impact of the Internet of Things (IoT) in the healthcare industry. It examines several research papers and studies, including those by Ullah et al. (2016), Gupta et al. (2016), Gope and Hwang (2016), Ingole et al. (2015), Ibhaze et al. (2016), Abdullah et al. (2015), Khoi et al. (2015), Yi et al. (2016), and Aslam & Saniie (2016). These works propose various models and systems leveraging IoT for patient monitoring, data collection, and improved healthcare delivery. The review covers different aspects such as sensor technologies, communication protocols (e.g., ZigBee, 6LoWPAN), security considerations, and the integration of IoT with mobile devices and platforms. The report highlights how IoT enhances patient engagement, enables preventive care, and improves the efficiency of healthcare operations. The annotated bibliography provides concise summaries of each paper, offering insights into their methodologies, findings, and contributions to the field. The report also addresses the benefits of IoT in healthcare, emphasizing its potential to transform healthcare practices.

Running head: IoT IN HEALTHCARE INDUSTRY
IoT in Healthcare Industry
[Name of the Student]
[Name of the University]
[Author note]

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Literature Review and Annotated Bibliography:
Ullah, Shah and Zhang (2016), proposed a new model known as the “k-healthcare”
which was associated with the usage of the four different layers. The model included four
layers, this are network layer, sensor layer, service layer and the internet layer. Along with
this, various kind of sensors were also used which includes the Aurduino, RTX-4100 and
many more. Besides this, communication standards like the IEEE 802.15.4, ZigBee and many
more were used for establishing communication between the different layers. Various type of
protocols like the HTTP, RESTful, and HTTPs as well as the JavaScript web services are also
supported by the new system proposed by them.
In the paper by Gupta et al. (2016), another system was proposed which is considered
to be intelligent and was smart enough for monitoring the various parameters of a patient’s
body. The hardware of this new system was made up of 2nd generation Intel Galileo, a 32-bit
Intel Pentium processor system which acted as the brain of the proposed model. The Linux
platform provides high computing as well as processing power which makes this preferable
over the Arduino. Ethernet is used for uploading the data that has been collected from the
patient’s body by the sensors. Different type of sensors were used like the XD-59C for pulse
monitoring and LM-35 for temperature monitoring.
According to the author Gope and Hwang (2016), Body sensor technology is also
known as the BSN. This new technology consists of a wearable biosensors, which can also
be implemented and this mainly incudes EMG, Blood pressure and many more. Wireless
communication was used by the BSN by utilization of the 3G, CDMA or the GPRS
technology. Authors of this paper also described the various key security requirements of the
system which includes integrity of the data, privacy of the data and many more. A
lightweight anonymous authentication protocol was proposed for the purpose of achieving

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the key security requirements and this proposed protocol is associated with the utilization of
the OCB or the offset code.
According to Ingole, Ambatkar, and Kakde, (2015), it is possible to monitor the basic
health parameters without the usage of any kind of heavy or bulky systems. In the paper the
authors have discussed the fact that a minicomputer of size similar to a credit card can be
placed beside the bed of patient and once they are supplied with power he results can be
viewed in the screen of the computers that exists in the same network. This would be helping
in monitoring the heart beat as well as the temperature of the body and for that the DS18B20
sensor is used which works on the principle of light modulation once the values are detected
they are uploaded in the webpage which is created by writing of codes in the HTML.
According toIbhaze, Eleanor, and Idachaba, (2016),measuring of the basic health
parameters is very important for the elderly peoples in order to eliminate the risk of falling ill
and dying as well. Authors have been associated with designing a system based upon the
microcontrollers so as to monitor the basic body conditions like the heart beat and the
temperature. The system is associated with sending of text messages to the mobile phone
whenever any kind of abnormal readings are detected. This device is made by making use of
the sim808 GPRS/GSM/GPS which is associated with sending of the reports related to the
health of the patient and the location of the patient as well to the healthcare providers.
According to Abdullah et al. (2015), an Arduino shield can be used for the purpose of
creating a connection between various type of sensors which would be including the
temperature LM-35 sensor, blood glucose sensor and blood pressure sensor. The authors of
this paper made use of the LabVIEW software as well so as to show that, it is possible to take
reading regarding the different kind of parameters of a patient body. Besides this the data
which are being displayed in the LabViewfrongt panel can be updated by making use of the

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Data Dashboard Application and along with this the information related to the biometrics can
be sent by making use of the ZigBee.
According to the author Khoi et al. (2015), architecture known as the IReHMo is
being evaluated in their paper. This is the architecture that is having the capability of
operating various kind of home automation sensors along with the IoT devices associated
with healthcare present in the various sensing layers. Different type of protocols likes the
HTTP, MQTT, CoAPare used for the purpose of communicating the various kind of IoT
devices. The CoAPprotocol is associated with reducing the requirements related to the
bandwidth and the volumes of the data that has been generated. This mainly happens due to
the reason that about 56% of the required bandwidth is reduced in case of healthcare system
based upon remote monitoring. Along with this the authors have also been associated with
providing a qualitative analysis. In addition to this , authors have compared the various IOT
protocols in accordance to the architecture that they are having, the security mechanisms used
by them, the Quality of service schemes and the pattern of their communication.
The authors Yi et al. (2016), have been associated with presenting forward an
architecture for the fall detection system which has been paired with the Wireless Intelligent
Personal Communication Node (W-iPCN) and Android smartphone. In this the data which
have been received are from the accelerometer and gyroscopes which are associated with the
detection of falls by making use of the W-iPCN. The major reason behind the usage is that
Bluetooth consumes more battery power. The 6LoWPAN which has been used in this
architecture is mainly based upon IEEE 802.15.4 MAC layer, which is associated with
providing flexibility so as to work with some other packet switched network. The process
involved the usage of one accelerometer which is present on the thigh of the patient. All this
sensor data can be accessed by making use of the W-iPCNso as to verify if the patient has
fallen or is lying down or sitting down or is in upright position.

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In the paper by Aslam&Saniie, (2016), they have been associated with having a
discussion about the design flow as well as the architecture of a Tele-Health observation
(THM). This in turn is associated with the usage of the computational amd the other inbuilt
periphrals present in the STM32 microcontroller in an efficient way. There exists three major
sections in the design which includes the Biometric Data Acquisition; Data Processing
andcommunication; Notification Panel and User Interface.

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References:
Abdullah, A., Ismael, A., Rashid, A., Abou-ElNour, A., &Tarique, M. (2015). Real time
wireless health monitoring application using mobile devices. International Journal of
Computer Networks & Communications (IJCNC), 7(3), 13-30.
Gope, P., & Hwang, T. (2016). BSN-Care: A secure IoT-based modern healthcare system
using body sensor network. IEEE Sensors Journal, 16(5), 1368-1376.
Yi, W. J., Sarkar, O., Gonnot, T., Monsef, E., &Saniie, J. (2016, May). 6LoWPAN-enabled
fall detection and health monitoring system with Android smartphone. In Electro
Information Technology (EIT), 2016 IEEE International Conference on (pp. 0174-
0178). IEEE.
Ingole, A., Ambatkar, S., &Kakde, S. (2015, April). Implementation of health-care
monitoring system using Raspberry Pi. In Communications and Signal Processing
(ICCSP), 2015 International Conference on (pp. 1083-1086). IEEE.
Khoi, N. M., Saguna, S., Mitra, K., &Ǻhlund, C. (2015, October). Irehmo: an efficient iot-
based remote health monitoring system for smart regions. In E-health Networking,
Application & Services (HealthCom), 2015 17th International Conference on (pp.
563-568). IEEE.
Ullah, K., Shah, M. A., & Zhang, S. (2016, January). Effective ways to use Internet of Things
in the field of medical and smart health care. In Intelligent Systems Engineering
(ICISE), 2016 International Conference on (pp. 372-379). IEEE.
Gupta, P., Agrawal, D., Chhabra, J., &Dhir, P. K. (2016, March). IoT based smart healthcare
kit. In Computational Techniques in Information and Communication Technologies
(ICCTICT), 2016 International Conference on (pp. 237-242). IEEE.

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Aslam, S. K., &Saniie, J. (2016, May). Architecture and design flow of Tele-Health
Monitoring system using STM32 platform. In Electro Information Technology (EIT),
2016 IEEE International Conference on (pp. 0287-0291). IEEE.
Ibhaze, A. E., Eleanor, E. C., &Idachaba, F. E. (2016, August). E-Health Monitoring system
for the Aged. In Emerging Technologies and Innovative Business Practices for the
Transformation of Societies (EmergiTech), IEEE International Conference on (pp.
298-299). IEEE.