=Paper=
{{Paper
|id=Vol-3706/Paper20
|storemode=property
|title=Smart Hospital Setups with IoT-Enabled Connectivity of Artificial Intelligence System
|pdfUrl=https://ceur-ws.org/Vol-3706/Paper20.pdf
|volume=Vol-3706
|authors=Vella Satyanarayana,Mahesh Kumar Singh,Robin Varghese
|dblpUrl=https://dblp.org/rec/conf/icaids/SatyanarayanaSV23
}}
==Smart Hospital Setups with IoT-Enabled Connectivity of Artificial Intelligence System==
https://ceur-ws.org/Vol-3706/Paper20.pdf
Smart Hospital Setups with IoT-Enabled Connectivity
of Artificial Intelligence System
Vella Satyanarayana1,∗,† , Mahesh Kumar Singh1,† and Robin Varghese1,†
1
Department of ECE, Aditya Engineering College, Surampalem, India
Abstract
The widespread of the internet of things (IoT) like sensors, actuators, wearable devices play a vital part
in our daily lives as well as it will mainly help in hospitals also. It improves the quality of our life. It also
improves the quality of medical care and it improves the facilities in hospitals. We need an architecture
that connects all the intelligence of things that are made feasible in hospitals by Narrowband intelligence
of things (NB-IoT). Here proposed the architecture that is connected by the intelligence of things based
on NB IoT. IoT develops many various applications to support Wi-Fi and additional data gathering
approaches which probably collects the data and transfers the information to a cloud stage. It processes
to a secure connection that increases the users in the real-time interface. It implements the structure of
the design and made a small demonstration design and it tests the results. It develops a smart grid in our
lives.
Keywords
IOT, NB-IoT, Smart grid, Sensors, Actuators, Cloud platform
1. Introduction
As we know there is rapid use of the internet, the IoT, and wearable devices. many hospitals
have put it into implementation like they use mobile applications for a doctor appointment,
online consultancies,3G blood pressure meter, smart ECGs and many more [1, 2, 3]. These
devices are known as monitoring devices i.e. monitoring devices will send the information to
A framework for short- and long-range wireless connections between autonomous entities.
The support of modern technology like IoT and cloud computing it had created a smart grid
around us. By using IoT it results in rapid digitalization across the hospitals. This technology
follows up and connects with everyday objects such as sensors, actuators, and many more to
the IoT and increases the efficient use of hospital resources. We had a network that will monitor
the environment of the hospital with the NB-IoT [4, 5, 6]. For instance, there is a network
architecture for tracking patients’ behavior and environment in hospitals.
• we use the IoT smart gateway.
ACI’23: Workshop on Advances in Computational Intelligence at ICAIDS 2023, December 29-30, 2023, Hyderabad, India
⋆
You can use this document as the template for preparing your publication. We recommend using the latest version
of the ceurart style.
∗
Corresponding author.
†
These authors contributed equally.
Envelope-Open vasece[underscore]vella@aec.edu.in (V. Satyanarayana); mahesh.092002.ece@gmail.com (M. K. Singh);
20A91A04O4@aec.edu.in (R. Varghese)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
247
• It provides the data from terminals of smartphones using networks like 4G and 5G.
• NB-IoT is a smart protocol that works virtually everywhere.
Application scenarios: Tele-medicine monitoring: Patients who have been discharged
from hospitals are required to undergo thorough monitoring in their homes. We are able to
monitor or examine the patient’s conditions, even when such situations are atypical, thanks to
the use of wearable equipment [7, 8]. Therefore, the device notifies the members of the family,
allowing them to instantly make a trip to the physician [9]. Intelligent parking: Intelligent
parking means we can book our parking slot before going to the hospital. We can book parking
slots using mobile apps it will lock our parking slot until we arrive when we leave the hospital it
will auto-lock our slot using wireless communication [10, 11]. Access Control: Access control
means giving control to the staff of the hospital so when they arrive it will give control and
open the door using wearable devices. Other Applications: By using sensors wireless devices
and other networks they will help us to generate many facilities in hospitals and Medicare
hospitals. For example, water meters in hospitals [12]. As the number of people in the world
continues to rise, the healthcare sector is facing an increasing number of challenges. Following
an intensive review of the relevant literature, it was found that the most prevalent issues that
are related with healthcare include inadequate communication methods, insufficient staffing,
poor patient flow, and lengthy hospital stays. These are the most common concerns. In point of
fact, there is a necessity to address these concerns, and that is precisely what the objective of
this effort is to do. When it comes to the internet of things (IoT), the most significant concerns
for developers are not only the availability of resources but also the quality of security and the
networking. The combination of this factor with the possibility of basic impediments results in
a significant number of difficulties being encountered [13, 14].
A smart city is one that designs and implements smart solutions in order to create an
environment that is more conducive to positive outcomes. Smart cities are designed and
implemented when populations rise. In order to ensure that we maximise our productivity, it
is absolutely necessary that we have a solid healthcare sector. Because of this, people will be
able to perform their jobs with a level of worry that is much reduced. The plan that T. Alizadeh
developed for a smart city includes a patient record system that is integrated with a variety
of healthcare applications and is equipped with Internet of Things (IoT) devices and machine
learning (ML) protocols. Additionally, the plan calls for the integration of these technology
components. The technology and architecture of remote health monitoring (RHM) include a
patient record system that integrates well with the appropriate sensing mechanisms and collects
structured and unstructured data for machine learning analysis [15].
RHM is also known as remote health monitoring. There is another name for RHM, which
is remote health monitoring. In order to facilitate the transmission of data and signals across
the various devices, systems, and models that make up the Internet of Things, communication
protocols have emerged as an indispensable component. The individuals who live in smart
cities are afforded a good quality of life as a result of their residence. Blockchain technology has
the potential to be advantageous for smart cities because it enables the storage of transactions
in a ledger that is not only safe but also open, shared, and immutable within the network. It
is possible to categorise the technologies that constitute the communication systems of the
smart city as follows: proximity wireless, personal area networks, wireless local area networks,
248
wireless metropolitan area networks, and wireless wide-area network technologies. Numerous
technologies, such as radio-frequency identification (RFID), Bluetooth, near field communication
(NFC), 3G, 4G, 5G, Zigbee, and others, all comprise them. Among these technologies are also
others [16, 17].
Because of the rapid development of edge-assisted solutions in Internet of Things (IoT)
networks, connected healthcare is becoming increasingly dependent on these solutions. This is
because edge-assisted solutions are extremely useful. This is a reference to the systems that are
in place to ensure that all of the various players in the healthcare business are connected to one
another. Some of the cutting-edge technologies that are utilised by these systems include the
Internet of Things (IoT), edge computing, and artificial intelligence (AI) [13]. These technologies
are utilised in order to change conventional health care systems into intelligent systems that
are more effective, appropriate, and individualised. On the other hand, such systems are subject
to a significant number of restrictions and require innovative regulations to be implemented.
Fog computing is transformed into edge computing by the process of moving computation and
processing closer to the data sources and end-users [18]. Edge computing has the ability to
reduce latency, bandwidth utilisation, and energy consumption [19] expenses. Fog computing
is also known as fog computing. To the best of our knowledge, there is no research that is both
methodological and systematic, and that examines the studies that have already been conducted
while taking into consideration a wide range of factors that are significant and relevant [20].
Within the scope of this survey, the objective is to investigate the most recent research that
has been carried out in this particular field. After completing an in-depth examination of a
significant number of papers that deal to this topic, we have categorised them into two basic
taxonomies: approaches that are process-centric and procedures that are patient-centric. In
addition, key issues, such as the data sets that are readily available, as well as parameters like
as accuracy, mobility, and data rates, are discussed and studied [21, 22, 23, 24]. Our goal is to
bridge the gap between edge computing and linked healthcare solutions by participating in a
discussion of the difficulties that may arise in the future and by conducting an evaluation of the
trends that may emerge in the following years [15].
2. Related Work
In this paper, we are discussing the usage of IoT in hospitals for solving or detecting prob-
lems in hospitals. In hospitals, there is excessive usage of electricity so using Arduino board
equipped with micro-controller which has low power utilization. In this paper, we discussed the
construction and architecture with the combined implementation of IoT in smart hospitals.it
provides a concrete application scheme and changes the existing hospital model into a smart
hospital. In this research, the IoT and artificial intelligence are used to create a smart and safe
framework for the hospital environment. With the assistance of AI, it controls the use of a
wide variety of electronic components, including actuators, sensors, and more. The Internet of
Things and artificial intelligence working together will bring further benefits to many different
industries [1, 25, 18].
This paper contains information about the introduction of the system’s design, architecture,
and test results, both simple and complex. It develops an IoT system that is very much required in
249
hospitals for various requirements [20, 21]. The authors of this piece of writing presented the idea
of a ”smart community,” which is characterized by its use of the Internet of Things. In the subject
of cyber-physical systems, the communal networks of interconnected and communicative
electronic devices are referred to as ”smart communities.” It encourages a scenario in which
embedded sensors and actuators can self-configure and be controlled through the internet; this
topic will be deliberated in greater details in the approaching units of this article [2, 3, 4].
The use of tele-medicine and remote patient monitoring is becoming increasingly significant
as a means of avoiding physical contact with patients. The Internet of Things (IoT) and the
technologies that are connected to it, such as Artificial Intelligence (AI), Machine Learning
(ML), Blockchain technology, and Cloud Computing, are the resources that make this a reality.
Due to the fact that the Internet of Things (IoT) generates such a substantial amount of data in
a wide range of forms, there is a substantial demand for connection and streaming analytics.
Because of this, the 5G technology and its applications have been taken into consideration.
These applications include smart 5G connected ambulances and hospitals that are based on
5G technology. A further potential technology is long-range radio, which is becoming the
technology of choice for Internet of Things networks all over the world, particularly in regions
with inadequate network coverage [6, 7, 15].
This is due to the fact that long-range radio operates with a low amount of power and has
the ability to transmit data over long distances at faster speeds. In view of the fact that there is
a lack of suitable medical infrastructure all over the world, an evaluation of smart ventilators
that are based on the Internet of Things has simultaneously been carried out. This is because
there is a demand for qualified medical staff as well as ventilators in the modern medical field.
A smart healthcare model design is suggested as a potential solution to the problem of Internet
of Things (IoT) problems in the healthcare business at the conclusion of the paper. This model
design is proposed as a potential solution. The module also includes a UVC Disinfection box,
which would be of tremendous assistance in removing the chance of the virus infiltrating our
homes. This is in account of the current state of events about the COVID-19 Pandemic, which
is currently prevalent [8, 9, 16].
As an additional point of interest, the rapid use of blockchain technology results in a significant
contribution to the formation of a new ecosystem for digital smart cities. Therefore, the
confluence of blockchain technology with artificial intelligence technology is revolutionising
smart city infrastructures in order to establish sustainable ecosystems for Internet of Things
applications. This is a result of the convergence of these two technologies. However, these
technological innovations and advancements in technology also generate opportunities and
issues for the creation of applications that are sustainable for the Internet of Things. These
opportunities and problems affect the development of applications. Blockchain technology and
artificial intelligence are a singular force that is pushing technical innovation in applications
that are both intelligent and sustainable for the Internet of Things [7].
The purpose of this essay is to study the confluence of these two technologies. During our
chat, the primary focus was on the potential advantages of blockchain technology, which has
the ability to support the creation and development of Internet of Things applications that are
ecologically friendly. We were able to introduce a conceptual framework that is both clever
and sustainable thanks to the conversation that served as the basis for our presentation. The
processing and acquisition of the necessary information is accomplished by this framework
250
through the utilisation of cloud computing, devices connected to the Internet of Things, and
artificial intelligence. The system provides digital analytics and keeps the data in decentralised
cloud repositories utilising blockchain technology. This is done with the intention of supporting
a wide variety of applications. Furthermore, the layer-based design makes it possible to have a
sustainable incentive structure, which may be of aid in the development of smart city applications
that are secure and protected. This is because the design is built on layers [8, 9]. In this section,
we discussed the enhanced solutions and provided a summary of the most essential components
that may be utilised for the construction of a variety of systems that are based on blockchain
technology and artificial intelligence. In addition, we discussed the issues that have not yet
been resolved as well as our future research objectives, which may result in the creation of
novel ideas and future standards for applications of the Internet of Things that are accountable
for the environment [12, 25].
It is a conceptual paper we learn deficiencies of the IoT concept and how to analyze them and
to discover the issue behind the lack of reasoning and IoT concept.it concludes the benefits of
implementing a concept to solve real-world issues and solves a lot of issues and eases our daily
routine. The introduction of the IoT technology is followed by a suggestion for the creation
of a sensor system based on IoT gateways in this study [5, 6]. It concludes that in order to
achieve the information storage for sensor access, it has created an LAPD environment. This
paper used the IoT to build a real-world scenario of smart hospital management. It seeks to
describe in detail the technologies underlying the IoT and the modeling of health care data
for medical devices [8]. As IoT is gaining momentum for many devices and wireless systems
soon be adopting various IoT technologies. In IoT, every device is connected to the internet. It
provides a brief survey to security threats extent change to different IoT devices [10, 11].
3. Method and Methodology for Image Detection HELM-FSK
The NB-IoT standard is particularly designed for usage in low-power, stationary, heavily-loaded
applications with little tolerance for delay. The communication delay cannot be tightly controlled
with the NB-IoT protocol. The protocol was created with the network design in mind, which
demands for a lot of access points and a low minimum power consumption requirement. In
some use cases for smart hospitals, such as the intensive care unit where specific physiological
sign data of patients with serious conditions must be uploaded in real time, requiring a low
latency, this could be a concern shown in figure 1. Using NB-IoT in smart hospital has a number
of benefits, including the following:
• NB-IoT has the potential to facilitate billion of connection and link tens of thousands of
user in a single locality.
• It can effectively avoid the devices from accessing pseudo Bs.
• When compared to the already available mobile network, the link budget for NB-IoT is
increased by about 20 dB
Here, classifying the authentic and the annoyance picture using a novel HELM-FSK has
been proposed. The proposed techniques are the filter term with the median filter principle
and the overlapping units are discussed before processing. The function vector is extracted
251
Figure 1: Proposed NB-IoT standard
from the area indicated by the object boundary detection. The wavelet transformation is also
defined. With the use of this tool, the work expands the forgery detection. The similarities are
calculated by DBA between vectors. The flow graph of this proposed method is characterized
as demonstrated in figure 1.
• The clouds platform store and processed worldwide data with low latency requirements,
and it uses big data analysis to maintain control.
• A huge number of NB-IoT base station is deployed in the BS layer. These NB-IoT base
stations must be furnished with routing, congestion control, traffic scheduling, and data
encryption systems in order to guarantee the smooth integration and security of data
transfers.
• In the sensing layers, there are a significant number of terminals device that have NB-IoT
modules embedded into them. Data collection and processing are two of the functions
that these gadgets are capable of. attacked. The sensing layer needs to have security
methods such as data encryption, data verification, and access authentication in order to
maintain the confidentiality and safety of the data. Two-factor authentication is required
for access authentication, which must involve both the devices and the BS.
• Because the edge server is located quite close to the terminal, the amount of time it
takes for data to complete a round trip is relatively short, which significantly lowers the
latency. The monitoring that takes place in intensive care settings, for example, has a
high requirement for latency, and this can be of considerable help to that monitoring.
We have integrated the Internet of Things into our platform. The five levels that make up
this system are the sensing layer, the forwarding layer, the connection layer, the data storage
252
Figure 2: NB-IoT access method
layer, and the service layer. Each succeeding layer now has a name that accurately describes
the task it is responsible for carrying out. The sensing layer integrates support for a wide range
of wireless Internet of Things protocols in order to gather information. Heterogeneous data
from various devices will be treated uniformly at the forwarding layer before being delivered to
the cloud over a secure connection at the connection layer. Once the information reaches the
data storage layer, it will be permanently archived. This data is once again made available to
the user through the user interface that the service layer offers shown in figure 1.
In figure 2 shown that it links networks and smart sensors. ”Smart” healthcare, ”smart”
housing, ”smart” grids, and other fields employ the Internet of Things. A growing number
of governments are developing ”smart healthcare” pilot projects. Edge computing could help
IoT-enabled healthcare systems secure equipment and patient data. IoT-enabled healthcare
delivery systems also need edge computing. Edge computing offers low-latency, low-cost data
services. The technology improves healthcare IoT devices’ connectivity and processing speed.
Authorization of IoT devices is required prior to data transmission in IoT-enabled healthcare
systems. In order to swiftly process the authenticated data, it must be offloaded to powerful
computers at the edge. With the help of the SDN controller, which can create complete network
programmability, offloading to the Edge can be done in a planned manner. SDN’s smarts are
what meet the needs of Edge computing in terms of load balancing and allocating resources,
while a lightweight authentication method safeguards the security of sensitive information.
The SDN controller is in charge of handling data, ensuring that time-sensitive data is handled
properly, orchestrating the Edge, and ensuring that data flow is both fast and secure.
253
4. Results and Discussion
In this section, we simulate our design for safe healthcare systems to test its performance in real-
world settings. Here, the simulations are run on a computer. First, we’ll go over the simulation
and testing setup, describe some key performance measures, and analyze the simulation’s
output in light of these and other considerations. MATLAB was used to analyze the proposed
system’s robustness, and the resulting data was put into our model. The SDN controller, Edge
Server, and authentication protocol were all executed in parallel, but on separate simulated
threads. The Edge server thread is responsible for load balancing and resource efficiency,
while the authentication protocol thread is in charge of ensuring system security. Among
the responsibilities of the SDN controller thread is the periodic analysis of trending network
parameters. These settings allow you to fine-tune edge-to-gateway communication, edge-to-
edge collaboration, and task transfer shown in table 1 and table 2.
Table 1
Parameter analysis of IoT in smart hospital
S. No. Parameter Parameter of IoT in smart hospital
1 Connection Unified architecture to connect all IoT from smart hospi-
tal
2 NB-IoT Bandwidth 180 KHz
3 Latency Using Edge computing for reduction
4 Power consumption Low
5 Cost Low cost
6 Real time require- For ECG
ment
7 Mobility NB-IoT set for non-mobility
Table 2
Parameter analysis
S. No. Parameter Parameter analysis
1 Environment Relaying on digital environment
2 Network Collaborative network to improve
the efficiency, service capability,
and flexibility between smart
devices.
3 Privacy and security Collaboration process for privacy
and security
4 Complexity Connecting of multiple devices in
heterogeneous network
5 Large scale Numbers of devices connected
6 Maximum signal Rate of LAN, WAN
rate
Healthcare systems with IoT capabilities should use edge computing with software-defined
networks for security. Simple authentication verifies IoT devices’ legitimacy. The Edge server
254
processes patient data following authentication. Each Edge server includes a separate SDN
controller for intelligent decision-making and load balancing. SDN-based edge computing
improves collaboration and resource use by optimizing network design. The network’s reaction
time, packet delivery ratio, latency, throughput, and control overhead are improved. Three
independent simulations were conducted to verify the suggested method’s efficacy. Protecting
patients’ personal and medical data is one of our future goals. We suggest recording data
patterns in a dataset and using a machine-learning system to predict hostile network activity.
Data encryption and decryption can begin after system configuration. Extensive testing has
shown its effectiveness in encrypting and decrypting data at the sender and recipient.
5. Conclusion and Future Scope
Healthcare systems with IoT capabilities should use edge computing with software-defined
networks for security. Simple authentication verifies IoT devices’ legitimacy. The Edge server
processes patient data following authentication. Each Edge server includes a separate SDN
controller for intelligent decision-making and load balancing. SDN-based edge computing
improves collaboration and resource use by optimizing network design. The network’s reaction
time, packet delivery ratio, latency, throughput, and control overhead are improved. Three
independent simulations were conducted to verify the suggested method’s efficacy. Protecting
patients’ personal and medical data is one of our future goals. We suggest recording data
patterns in a dataset and using a machine-learning system to predict hostile network activity.
Data encryption and decryption can begin after system configuration. Extensive testing has
shown its effectiveness in encrypting and decrypting data at the sender and recipient.
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