Noise Monitoring System for Healthcare Facilities

Using Internet of Things: Enhancing Acoustic

Environment Management
James Paul Degamon1, Christopher Olvis2, Bryle Nino Amarille3
jdegamon@ssct.edu.ph, colvis@ssct.edu.ph, bamarille@ssct.edu.ph
Surigao del Norte State University, Philippines

I. INTRODUCTION impact of noise on patient outcomes and suggested the need for
innovative solutions and the right precautions, including IoT-
based noise monitoring, to address the necessary issues for the
Noise pollution in facilities especially in Health care ongoing noisy environment. Some proposed a framework for
centers and Hospitals has been identified as a significant implementing an IoT-based noise monitoring system in
challenge that can negatively impact the well-being of patients, healthcare facilities, outlining the key components and
staff, and visitors. However, excessive noise in healthcare considerations for mitigating the impacts of noise pollution.[6]
settings can have detrimental effects on patients, staff, and
visitors, including increased stress, impaired communication, Having insights into these works, the present research aims
disrupted sleep, and compromised patient outcomes, it also to design and implement a noise monitoring system with the
creates a huge impact on the well-being of visitors to the said help of the Internet of Things to make use of the advancement
facility.[1] Therefore, effective management of the acoustic of technology for healthcare facilities to enhance acoustic
environment is one of the most crucial to promote healing, environment management. By leveraging IoT technologies, this
patient comfort, creating a healthy and sound environment, and research seeks to provide real-time data on noise levels and
staff well-being in healthcare facilities. Excessive noise levels sources and facilitate evidence-based decision-making for noise
can contribute to patient stress and can alter their emotion to the reduction strategies in healthcare facilities. The findings of this
extent that they just want to get out in the place, hinder research can contribute to the development of effective noise
communication between healthcare providers and patients, management strategies in healthcare facilities and potentially
disrupt sleep patterns, and compromise the overall quality of improve patient outcomes and satisfaction.
care. Therefore, effective management of the acoustic
environment in healthcare facilities is vital for ensuring patient 1.1 Review of Related Literature
comfort and safety, as well as promoting a peaceful The acoustic environment in healthcare facilities plays
environment for healing.[2] a crucial role in patient well-being and recovery. A well-suited
With the advent of Internet of Things (IoT) technologies, noise environment can greatly enhance the recovery system of
there has been growing interest in utilizing IoT-based solutions patients in health facilities.[7] Excessive noise levels can
for noise monitoring in healthcare facilities. IoT-enabled negatively impact patient comfort, sleep quality, stress levels,
sensors and data analytics offer the potential for real-time, anxiety, depression, and even clinical outcomes. Therefore,
continuous monitoring of noise levels, allowing for data-driven effective management of the acoustic environment is vital for
decision-making in managing the acoustic environment. IoT- healthcare facilities to provide optimal care to patients. With the
enabled sensors and data analytics can provide real-time advent of the Internet of Things (IoT) technology, noise
monitoring of noise levels, sources, and patterns, allowing for monitoring in healthcare facilities can be enhanced and
data-driven decision-making in managing the acoustic automated through the integration of IoT-based solutions,
environment. Several authors have contributed to the allowing for real-time monitoring, analysis, and management of
understanding of noise monitoring in healthcare facilities and noise levels. This will also allow the incorporation of the
the potential benefits of IoT-based solutions.[3] [4] embedded system for creating necessary parameters.[8]

Other research that involves monitoring noise quality in This study aims to explore the use of IoT-based noise
different facilities emphasized the importance of continuous monitoring systems in healthcare facilities and their potential to
noise monitoring in healthcare facilities and highlighted the enhance acoustic environment management and create a noise
potential of IoT technologies for real-time data collection and pollution-free environment. The review will focus on the
analysis.[5] Others contributed and conducted a study on the current state of the literature, including recent research studies,
reviews, and relevant publications related to the topic. To create In conclusion, the literature review highlights the
an effective and efficient system to meet the requirement to potential of IoT-based noise monitoring systems to enhance
lessen and mitigate noise. acoustic environment management in healthcare facilities and
to facilitate and potentially mitigate noise. These systems offer
The literature review reveals that noise is a pervasive real-time, continuous, and remote monitoring capabilities,
problem in healthcare facilities and it’s crucial to take with it, along with data-driven insights and analytics for facilitating
with numerous studies highlighting its negative impact on noise, which can aid in identifying and managing excessive
patient outcomes. Excessive noise levels in healthcare facilities noise levels. Further research and development in this area are
are often caused by various sources, including medical needed to address the challenges and optimize the
equipment, alarms, staff activities, and patient conversations. implementation of IoT-based noise monitoring systems in
Therefore, effective noise management strategies are essential healthcare facilities for improved patient outcomes and reduce
to reduce noise levels and create a conducive acoustic noise pollution.
environment for patients.[9]
1.2 Theoretical Framework
IoT-based noise monitoring systems have emerged as
a promising solution for healthcare facilities to actively monitor Noise is a major problem that is somewhat disregarded
and manage noise levels and make automation processing of all by everyone. Many existing pollutions in the environment and
the data. These systems typically consist of IoT sensors noise are one of them that deteriorate patients' physical and
deployed in various locations within healthcare facilities-indoor mental health. The onset of the Internet of Things can enhance
and outdoors of the building, such as patient rooms, hallways, noise monitoring by simply automating the monitoring system
and common areas, that capture real-time noise data. The in health facilities.[13] The use of sensors and real-time
collected noise data is then transmitted to a central server or monitoring devices can give necessary information and even
cloud-based platform for analysis and processing and react for mitigate the ongoing noise in the facilities. Health centers can
a certain specification.[10] now use this system for their own and patients' benefits. The
orange Pi is a device that can be connected to peripherals and
The literature review highlights that IoT-based noise will be the brain of the system.
monitoring systems offer several advantages over traditional
noise monitoring methods. Firstly, they provide real-time and 1.3 Conceptual Framework
continuous noise monitoring, allowing for immediate detection
of noise spikes or excessive noise levels, and necessary Figure 1 represents the Input, Process, and Output
situations that occur in a place like a crowd and transportation diagram of the study. The input block shows the materials
noise. This enables healthcare facilities to take prompt actions, needed to create a system that can monitor different intensities
such as issuing alerts, adjusting equipment settings, or of sound and noise and store data such as the microcontroller,
deploying staff to manage noise levels or noise signals and TV IoT sensors, simulation software, and electronic hardware. The
monitors as a sign to indicate silence. Secondly, IoT-based process block involves the design, Simulation, decision-
systems offer remote monitoring capabilities, allowing making, and testing of the device to secure that it met the
healthcare facilities to monitor noise levels across multiple necessary parameters, this block shows the procedure for
locations simultaneously, precisely and accurately providing a making the system. The third block which is the Output
holistic view of the acoustic environment within the facility. represents the producing system which is an IoT-based
Thirdly, IoT-based systems can generate data-driven insights monitoring system for noise in health facilities. The last block
and analytics, which can be used to identify patterns, trends, and represents the determination of the performance of the system
potential sources of noise, leading to targeted interventions and which involves the iterative improvement to optimize
long-term noise management strategies.[11] effectiveness and achieved desired outcomes. It also represents
the quantitative data based on the output readings of the system
The literature review also discusses various features and qualitative data based on the perception of the user which
and functionalities of IoT-based noise monitoring systems, such are health facilities.
as data visualization, analytics, and integration with other
healthcare systems and parameters to create a holistic approach 1.4 Objectives
to noise. Some studies have reported the successful The main objective of this study is to create a noise
implementation of IoT-based noise monitoring systems in monitoring system that can detect noise in specific areas or
healthcare facilities, resulting in reduced noise levels, improved locations inside the health facility.
patient comfort, and enhanced patient satisfaction.[12]
However, challenges such as data privacy, security, and Specific Goals:
interoperability need to be addressed to ensure the successful
1. To collect real-time noise data for accurate and precise
implementation and adoption of IoT-based noise monitoring
monitoring and predictions of noise pollution in
systems in healthcare facilities.
Health facilities.
 2. To create a Noise Monitoring system using the Internet a mobile app specifically designed for the operation of the
of Things (IoT). project
3. To implement it in Health facilities for testing.

II. METHODS

2.1 Research Design

The study employed an observational type of research

that involves observation and proper documentation of the
behavior and characteristics without intervening or altering
their natural specifications. The project aims to observe real-
time noise pollution in a healthy environment and interpret it if
it met in the requirements. Through careful observations of the
recorded data, the health workers in the said area and
researchers can acquire a more comprehensive understanding of
the ongoing noise in the place, enabling them to make informed
decisions regarding the acoustic environment.

EVALUATION
PROCESS OUTPUT
INPUT -Iterative
Planning Improvement
Decision Making -Quantitative
-Microcontroller
Evaluation
-IoT sensors -Design
-Qualitative
-Simulation Software -Simulation -IoT-based noise
Evaluation
monitoring system
-Electronic Hardware -Testing
-Acoustic
-Production Environment
Management
2.2 Project Design
Figure 1. The IPO of the project
Noise Level Parameter Start

(Sound Level Intensity)

Microcontroller
Cloud
Orange Pi PC
Power (Microcontroller)
Supply Data
Cellular Collection
Phone

Figure 2. Block Diagram of the Project

Data Storage
Figure 2 presents the connections of the power supply and the
noise parameter for data collection. It also linked the connection
of the cloud for data logging. After collecting the data, the Cloud Server
connection to the database server is to store the incoming data
in the MQTT broker within the database. This process is
facilitated by an IoT system that uses MQTT technology for
managing data attributes and flow. It also depicts the connection User
Interface End
of a cellular phone for the ongoing monitoring of the system by

Figure 3. Flowchart of the system

 As illustrated in Figure 3, when the system is in its activation 2.4 Project Implementation
mode the sensors are in phase to all functions. The program
subsequently executes, and the microcontroller will This project will be implemented in health facilities
successfully acquire sensor data, assuming smooth sensor wherein each sensor will be placed in every primary noise
detection. In the event of any complications during the contributor place to enhance the ongoing noise in the said place.
initialization process, the program halts and is programmed to Each sensor will be connected to the brain of the system which
do it again. The microcontroller then locally processes the raw is the orange pi one. The researchers will run a survey regarding
sensor data, converting it into a piece of useful information. the behavior of the system and its benefits to health workers and
Subsequently, the cloud server saves data with the requisite patients. They will be the ones who can determine if the system
noise level intensity parameters. The cloud server serves a dual is well-suited for their facilities. If the project will not yield the
role: firstly, giving and facilitating visual representation of the necessary outcomes the researchers will make corrections to
data, and secondly, enabling advanced analytics to optimize the meet the requirements.
prediction accuracy of current noise conditions. 2.5 Project Evaluation
2.3 Project Development The assessment approach employed in this research is
referred to as applied quantitative evaluation, which involves
Planning utilizing numerical measures derived from formal and objective
data collection techniques, carefully planned research design,
and controlled observation. To consistently track noise intensity
and level data, this measure is the most appropriate approach to
Pilot Testing the study

2.6 Participants of the Study

The participant of the study will be invited to become part of

Data Gathering
the study. They are chosen using purposive sampling
techniques. Table 1 presents the profile and number of
participants.
Data
Analysis Table 1. Participants of the study

Participants F(n=20) %
Health patients 15 40
System Health personnel 4 30
Implementation
Adviser 1 30

Programming 2.7 Instruments

• Power supply: It is used to give power to the system.

The necessary components to give a DC source to the
Prototype Testing microcontroller.
• LM393: A sound detector device that can operate up
to 5 meters. This device is used by the researchers to
help to measure the noise and intensity level of sound
Evaluating
in the area.
Figure 4. The flow of Project Development • Microcontroller (orange pi pc): it is an open-source
component used for a lot of complex applications and
The first step of this study is to plan how to create and it will be used by the researchers to read and operate
implement, and by pilot testing to secure if the system will be the functions necessary for the project.
managed well. The next is to gather data for to exploration of • Zigbee: This device can be used as a fully functional
the necessary parameters to be created in the system. Next is to device or a reduced functional device. It is used for
analyze for creating a criterion in the system and decide to wireless communication purposes and it will be part of
implement it in the system. Creating the system will be the next the system for the project to communicate to the
followed by programming to create a prototype to be tested and microcontroller.
evaluated.
• SD card Module: A device that stores memory. It will
be used for storing and data logging.
 • Mobile Phone(User Interface): It is a device used for 2.11 Statistical Tool
many applications including entertainment but in the
case of the study, it will be used as a user interface to The mean will be used as a method to have
monitor the ongoing noise and monitor the calculations for the data in the responses and make necessary
maintenance of the system. conclusions based on the results. The percentage of patients'
• MQ Telemetry Transport.: It will be necessary to responses and health workers' responses will be determined and
provide a constrainer that will be used in the system aggregates all the scores in the survey in a measure of central
for communication but with a lower bandwidth tendency. Mean is the average of all inputs which can be
requirement. determined by dividing by how many inputs have been taken
into account.
2.8 Project Setting

The system will be appropriate in crowded hospitals

and more percentage of patients that are coming in a place. The REFERENCES
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