Empowering Elderly Health with IoT and Cloud Computing

V. Jyothi, Karra Ashwini, Arravapa Mahendar and Gora Prudhwi Raj

Department of ECE, Vardhaman college engineering, Kacharam, Shamshabad, Telangana, India

Keywords: ESP8266, Cloud Computing, IoT, Blood Pressure, Pulse Rate, Fall Detection and Oxygen Saturation

Abstract: The number of elderly individuals living alone is rising, especially those with restricted mobility, so it’s

important to keep an eye on their health with the ability to track vital indications like heart rate, blood pressure,

pulse rate, and oxygen saturation. These health monitors of elderly people at home are necessary. This

information enables elders and those close to them to recognize possible health issues early on, enabling

preventive measures and enhancing general well- being. IoT consists of physical devices, such as sensors and

monitoring devices for elderly peoples (blood pressure, heart rate, pulse rate, oxygen saturation and activity

monitoring, etc) to connect to the ESP8266 and Cloud computing. This work proposes a home healthcare

system for elderly people. It keeps track of the health status of elderly people, alert about their health condition

to us. It has been evaluated for three tasks 1) position estimate and activity tracking 2) fall detection and 3)

medical advice.

1 INTRODUCTION

The growing number of elderly people living

independently, especially those with limited mobility,

creates a challenge in ensuring their well-being. The

consequences of loneliness in this age group are far-

reaching. It can lead to a decline in mental well-being,

with increased risk of depression, anxiety, and regular

health issues. Physically, loneliness can weaken the

immune system, making seniors more susceptible to

illness. Additionally, social isolation can exacerbate

feelings of helplessness and decrease the likelihood

of timely intervention for health issues. This system

utilizes Internet of Things (IoT) technology, which

includes sensors and monitors for vital signs like

heart rate, blood pressure, and oxygen saturation.

These devices connect to a central hub and potentially

utilize cloud computing for faster data processing.

There is a rising number of old-age homes, where

constant care and monitoring are required for elderly

residents. This proposes a solution: a smart home

healthcare system by the system sensors take the

input of patient’s health parameters like temperature,

heartbeat etc. The camera is placed in front of the

patient side so we can observe patient condition

whenever they want to over the internet by accessing

and identifying falls and sending alerts for assistance.

remote monitoring, and timely medical interventions

that can empower older people. This proposes a

solution: a smart home healthcare system, which uses

system sensors to take input of patients' health

parameters like temperature, heartbeat, etc. The

camera is placed in front of the patient’s side so we

can observe the patient’s condition whenever they

want to over the internet by accessing and identifying

falls and sending alerts for assistance. This research

Paper IoT based elderly Health Monitoring System

uses Temperature Sensor, Heart Rate Sensor, and

Accelerometer Sensor & Respiratory sensor along

with the Camera and NodeMCU Model. All these

sensors are attached to the patient’s body. The

collected data is sent to the server in an encrypted

format through the NodeMCU. A family member or

doctor can see the real-time data on their system or on

their smartphone at any-time and anywhere.

2 LITERATURE SURVEY

The concept behind our project, "Empowering

Elderly health with IoT and Cloud Computing,” is not

very new. Numerous attempts were consistently made

in the past by researchers in different fields at

different times.

FEEL: Federated L Earning Frame work for

Elderly (Ghosh and Ghosh, 2023) Health care Using

Edge-IoMT was One of the major problems in IoMT

domain is scarcity of labelled data and diverse need

Jyothi, V., Ashwini, K., Mahendar, A. and Prudhwi Raj, G.

Empowering Elderly Health with IoT and Cloud Computing.

DOI: 10.5220/0013623300004664

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 3rd International Conference on Futuristic Technology (INCOFT 2025) - Volume 3, pages 513-521

ISBN: 978-989-758-763-4

513

of users. It is to develop collaborative healthcare

model by combining and clustering users based on

their habitual preferences and health status. FEEL is

suitable for old age homes where constant healthcare

support is required.

Junaid Mohammed et al used an IOIO-OTG

Microcontroller to analyse the patient’s ECG and

track readings from anywhere in the world (Al-

khafajiy, et al., 2019) A reading monitoring

application for electrocardiograms was created for

Android smartphones. The data can be transferred to

the Android mobile via the IOIO (Input Output Input

Output)-On the Go microcontroller via Bluetooth,

NFC, or USB connection. After being gathered, the

data is moved to the smartphone’s Android

application.

Mohammed S. Jasses et al's method is based on

using a Raspberry Pi motherboard coupled to a cloud-

based system to monitor a person’s body temperature

((Mohammed, Lung, et al., 2014)). The Raspberry

Pi’s sensor recorded the temperature of the human

body, and wireless sensor networks (WSN) are used

to transmit.

The C8051F020 microcontroller was used by

Karandeep Malhi et al. to assess heart rate and body

temperature. The developed sensors were designed to

be worn, receiving data and sending it to

microcontrollers connected to Zigbee modules, which

then sent it to the nearest available receiver.

This integration of modern IoT technology and

AI, the Health Monitoring System provides a solid

solution for maintaining the health of the elderly

(Prasad, Mhnv, et al., 2019). Through the constant

monitoring of vital signs including blood pressure,

heart rate, and oxygen saturation, the system

guarantees real-time monitoring and the early

identification of possible health problems. The

prompt intervention made possible by this proactive

strategy improves the general well-being and safety

of older people who live independently.

Its efficacy is increased by the addition of

functions like environmental monitoring and fall

detection.

Quar care - IoT Based Patient Health Monitoring

System, recommends concentrating on using Internet

of Things (IoT) technologies into the monitoring of

patient health (Visvesvaran, Shankar, et al., 2021).

The majority of the literature on this subject examines

developments in Internet of Things (IoT) applications

for the healthcare industry, with a focus on wearable

device integration, real-time data collecting, and

remote monitoring.

MHNV Prasad and P Munaswamy’s article

(Prasad, and, Munaswamy, 2013) Remote Health

Monitoring and Security System for Elderly People

using Raspberry” describes a system that uses the

Raspberry Pi to keep an eye on the wellbeing and

safety of senior citizens. The system probably has

sensors to monitor security aspects (like intruder

alarms or fall detection) and

vital indications (such blood pressure, pulse rate,

etc.). Remote data monitoring enables caregivers to

get emergency alerts and real-time information. The

Raspberry Pi provides an affordable option for elder

care by acting as the main controller for data

processing and communication.

Interoperable End-to-End Remote Patient

Monitoring Platform (Clarke, et al., 2017) by

Malcolm Clarke, Joost de Folter, Vivek Verma, and

Hulya Gokalp. In order to ensure that data from

different medical devices can be shared, processed,

and incorporated into healthcare information systems,

this standard makes it easier for medical devices and

health monitoring platforms to communicate. The

platform’s primary goal is to facilitate end-to-end

remote monitoring, which involves gathering patient

data at home and sending it to medical professionals

for evaluation.

Patient Monitoring System Using GSM

Technology describes a medical system (Rachana, ,

et al., 2016) that uses GSM (Global System for

Mobile Communications) technology to remotely

monitor patient health data. This device uses sensors

to gather vital signs including blood pressure,

temperature, and heart rate. It then sends the data to

healthcare providers over GSM networks, allowing

for real- time monitoring and emergency alerts. It

provides these readings. In this way, the data is

transmitted to a cloud-based website so that it can be

monitored. practical and effective means of patient

monitoring, particularly in isolated or rural locations

with limited access to medical facilities.

IoT-based health monitoring and tracking system

designed for soldiers (Iyer and Patii, 2017). This

system, worn on the soldier’s body, monitors health

metrics and tracks location using GPS, sending data

to a control room via IoT. Equipped with small,

wearable sensors and transmission modules, the

system offers a cost-effective way to enhance soldier

safety on the battlefield.

Design and Implementation of a Feasible Model

for the IoT Based Ubiquitous Healthcare Monitoring

System for Rural and Urban Areas Real-time health

monitoring systems powered by the Internet of

Things (IoT) (Bhuiyan , et al., 2022) have greatly

improved human wellbeing in both urban and rural

locations. Because there is often no reliable

communication infrastructure in underdeveloped

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nations like Bangladesh, many of these ideas are not

really applicable. In this work, we offer a real-time,

Internet of Things (IoT)-based health monitoring

system that can test, track, and report people’s health

conditions from anywhere at any time.

Our suggested Internet of Things-based system

has the ability to instantly send sensitive health data

to caregivers and medical facilities. The suggested

system measures body temperature, pulse rate,

oxygen saturation, room temperature, and air quality

in a smart home environment using Arduino UNO,

Nodemcu, and GSM modules. Historical medical

records for the patient may also be accessed by the

system. We tried our solution using a few test

scenarios, and it functions flawlessly and accurately.

There is a lot of promise for both rural and urban areas

in developing nations with the suggested method.

The difficulty of striking a balance between job

and health in a society that moves quickly, pointing

out problems including lengthy hospital stays and the

requirement for ongoing medical monitoring (Gupta,

Saeed, et al., 2017). It draws attention to the need for

a health system that can monitor heart rate and other

everyday health parameters and use GSM technology

to send this information to the appropriate people.

Numerous health monitoring systems have been

made possible by technological advancements, which

have improved user convenience. In order to

determine areas for improvement and strategies to

improve system performance, this study compares

and evaluates current systems and examines new

research and development in health monitoring.

The COVID-19 pandemic and the growing

significance of healthcare technology, particularly

IoT-enabled solutions (Reddy, Naik, et al.,

2021).Continuous patient monitoring is difficult

because of hectic schedules, particularly for elderly

patients. To automate this, a novel method is

suggested that would enable ongoing monitoring of

vital health indicators such as blood oxygen levels,

body temperature, heart rate, and humidity. The

design and functionality of a patient monitoring

system that collects critical health data from patients

using sensors connected to a micro-controller are

described in this study.

This paper discusses the design of an IoT-based

health monitoring system (Masud, Serhani, et al.,

2015) using temperature and pulse rate sensors to

continuously track a patient’s condition. The system

allows doctors to remotely monitor patients via a

computer. In case of abnormal readings, an email

alert is sent to the doctor for immediate action. This

enables timely diagnosis and potentially life-saving

interventions. The primary goal is to provide real-

time health updates and facilitate prompt medical

response.

Smart Healthcare (Khan, Manju, et al., 2017) is

important for people who need continuous

monitoring which cannot be provided outside

hospitals. It is also important in rural areas or villages

where nearby clinics can be in touch with city

hospitals about their patient's health condition. This

work presents a smart health monitoring system that

uses biomedical sensors to check a patient's condition

and uses the internet to inform the concerned. The

biomedical sensors here are connected to an Arduino

UNO controller to read the data which is in turn

interfaced to an LCD display/serial monitor to see the

output. Data is uploaded to the server to store and

converted into JSON links for visualizing it on a

Smartphone. An android application has been

designed in order to easily see the patient's

information by their doctors and family members.

Objectives achieved:

To design a health monitoring system that can

accurately identify falls, reducing the time it takes to

contact for assistance and immediately informing

family members. To Continuously monitor breathing

patterns to identify potential ap-nea events and

Trigger alerts for abnormal breathing patterns

requiring attention. To Monitor pulse rate and to track

temperature and humidity levels to ensure a

comfortable and safe environment. Generate alerts if

pulse rate, temperature, or humidity readings fall

outside pre-defined safe ranges.

3 DESIGN AND PRINCIPLE OF

OPERATION

3.1 Methodology

The workflow for this system begins with the central

processing unit is the ESP8266. It collects all the data

from the linked sensors, as well as direct inputs

(camera, temperature, humidity, and breathing data)

and processes inputs (humidity, temperature, and

respiratory data) from the Arduino NANO. It can

deliver messages or alerts based on the data collected

by the sensors. Through the use of theESP8266

microcontroller, the system keeps an eye on

Empowering Elderly Health with IoT and Cloud Computing

515

Figure 1: Block diagram of elderly health monitoring

system

physical safety (falls), environmental factors, and

vital signs. It then uses this information to send real-

time notifications to medical facilities and family

members.

The ESP32cam’s addition makes visual

monitoring possible. The NodeMCU board provides

the central processing unit for this health monitoring

system. It functions as a mini-computer, collecting

information from two vital sensors: an accelerometer-

based fall detection sensor and a heart rate sensor that

tracks your pulse. The device activates if the

accelerometer notices an abrupt shift in movement

that could be the result of a fall.

3.2 Hardware Components:

3.2.1 ESP8266 Wi-Fi Module

Figure 2: ESP8266 Module

The ESP8266 is a unique microcontroller in the

field. This tiny chip has strong Wi-Fi, so you can

connect your projects to the internet right away. It

offers a variety of programming options, is capable of

running programs, and uses less energy for battery-

powered applications. It is also less priced in

comparison to other Wi-Fi microcontrollers. Even

while its processing power might not be enough for

very demanding tasks, its affordability, versatility,

and ease of use make it a viable option for developing

a variety of internet connected devices.

3.2.2 Arduino-Nano

Figure 3: Arduino-Nano

The Arduino Nano is a small, compact, powerful

device. Due to its breadboard-friendly design, this

little microcontroller is often used for prototyping and

experimentation. Its small size makes it ideal for

projects requiring a lot of room, and you may realize

your creative electronics projects thanks to its

interoperability with a variety of sensors and

actuators. The Nano is particularly user-friendly for

novices, with onboard programming that eliminates

the need for a separate programmer. With the Arduino

Nano, you can explore electronics and programming

at a reasonable price. The Arduino Nano boasts 30

pins, 22 of which cater to input and output functions.

Among these, 14 digital IO pins (D0-D13) can be

customized using pinMode(), digitalWrite(), and

digitalRead() functions.

3.2.3 DHT11 Sensor

Figure 4: DHT11 Sensor

The DHT11 sensor is a reliable, affordable, and

basic tool for measuring temperature and humidity.

This digital sensor’s signal can be easily interpreted

by a microcontroller, like an Arduino, to provide

environmental measurements. It generates an analog

signal that needs to be processed by digitally

formatting it. However, keep in mind that the DHT11

has a limited operating range, so it might not be

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suitable for very sensitive readings. DHT11 is a 4-pin

sensor, these pins are VCC, DATA, GND and one pin

is not in use shown in fig4.

3.2.4 Accelerometer sensor

Figure 5: Accelerometer sensor

Digital signals are output by the ADXL-335. This

digital sensor’s capacity to provide data that

microcontrollers can easily grasp opens up a wide

range of possibilities. The ADXL335 Module 3-axis

Analog Output Accelerometer measures acceleration

with a minimum full-scale range of ±3 g. It can

measure the static acceleration of gravity in tilt-

sensing applications, as well as dynamic acceleration

resulting from motion, shock, or vibration.

3.2.5 Pulse Sensor

Figure 6: Pulse Sensor

The pulse sensor measures variations in the

volume of blood in your fingertip, which can be used

to calculate your heart rate. The microcontroller can

read the analog signal that is usually output by it.

Their heart rate is then calculated using this

information, giving you important details about your

general health and level of exercise. The pulse

sensor’s price, usability, and capacity to deliver heart

rate data.

3.2.6 ESP32Cam

This camera module is an add-on for the system. To

connect it to the microcontroller, most likely, a

connector intended for camera modules would be

utilized. Video or image data can be recorded by the

ESP32cam.The camera takes pictures or movies,

Figure 7: ESP32Cam

but the ESP32 core handles application processing

and Wi-Fi connection establishment. Along with the

other health and environmental sensors (pulse, fall

detection, respiratory monitoring), the ESP32-CAM

adds an extra layer of security by visually confirming

the elderly person’s status.

3.2.7 LCD (Liquid Crystal Displays)

Figure 8: Liquid Crystal Display

LCDs, or liquid crystal displays, are a widespread

technology seen in a wide variety of everyday items.

This flat panel display uses backlighting and liquid

crystals to control light to create the images you see.

LCDs control light flow to produce images, as

opposed to their relative, the LED (Light Emitting

Diode), which emits light directly. Their low cost,

low power consumption, and small profile make them

a popular choice for TVs, computer screens,

calculators, and many other electronic devices.

3.3 Flow Chart

The health monitoring system sensors are used to

track vital indicators and identify possible medical

emergencies. System initialization is the first step,

which makes sure all software and hardware are

prepared.

The oxygen saturation sensor tracks blood oxygen

levels, and the ADXL-335 accelerometer detects falls

or instability. In order to detect hypothermia or

hyperthermia, which both need to be treated right

away, a temperature sensor measures body

temperature.

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517

The device transmits information to the cloud if it

detects anomalous conditions such as falls, irregular

heartbeats, or low oxygen saturation. For caretakers

or medical professionals, cloud storage guarantees

safe data access. For improved health forecasts, it also

permits sophisticated analysis through manual review

or machine learning.

Figure 9: Flow Chart of elderly health-monitoring

This device continuously monitors vital indicators

in an effort to protect users. It warns caretakers or

family members about emergency, guaranteeing

timely medical attention. The ultimate objective is to

use real-time health tracking to promote wellbeing

and safety. Cloud storage provides secure, remote

access for caregivers and enables machine learning or

professional review for advanced analysis.In order for

the system to protect health, it continuously monitors

and quickly alerts caregivers if there is an emergency.

This holistic approach focuses on improving user

safety and well-being.

4 SIMULATION RESULTS AND

DISCUSSION

Firstly, connect the accelerometer and respiration

sensor to the microcontroller of the ESP8266

(NodeMCU) and Arduino Nano to build a dependable

and efficient fall detection and respiration monitoring

system. To ensure reliable data interpretation,

calibrate the sensors and create baseline values. Read

sensor data continuously, then apply filters to lower

noise and boost signal quality. Create an algorithm

that uses predefined thresholds and time-based

criteria to search accelerometer data for patterns that

point to a fall, such as sudden free fall or impact.

Simultaneously, measure the breathing rate by

analyzing respiration sensor data, and use algorithms

to identify irregular breathing explain the prosses of

the dht11 sensor and respiratory sensor ,pulse sensor,

accelelometer are connected to the node mcu and

arduino nano also connected patterns like 19

tachypnea or apnea. When a fall or unusual breathing

is detected, send an alert notification to predesignated

contacts over a cellular network or WiFi. Think about

saving sensor data as well for future research and

system enhancement. A reliable and efficient

monitoring system will be created by adhering to this

structured development procedure.

Figure 10: Hardware implementation for empowerig

elderly health-monitoring

A wearable health monitoring device that tracks,

analyses, and reports a person’s vital health indicators

continually using Internet of Things (IoT)

technology. A body area network’s sensors use

accelerometers to gather information on motion, body

temperature, and heartbeat. For instant visibility,

these measurements are shown on a worn LCD panel.

Wi-Fi is used to send the data to an IoT cloud

platform, where it is processed and stored. Users can

perform different tasks by using services provided by

the data centres of the cloud through the internet and

access the virtualized resources (hardware and

services) provided by the cloud anytime and

anywhere as long as there is active internet

connectivity. It improves the capacity to track

recovery, manage chronic illnesses, and guarantee

preventative care through ongoing monitoring and

timely alarms. This technology shows how

continuous, connected care from wearable IoT

devices can revolutionize healthcare.

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The system first records accelerometer data while

the device is kept at a 90° angle and the person is

stable. This data serves as a baseline for typical

activity. This calibration stage helps differentiate

between normal movements and potential falls.

Figure 11: Output of normal state on LCD

An accelerometer keeps an eye on movement

patterns all the time. The device sounds an alert if the

sensor notices a sudden change in acceleration that

could be the sign of a fall. Family members who have

been pre-designated receive an alert message

informing them of a possible fall occurrence.

Figure 12: Unstable alert message

The purpose of the device is to keep an eye on and

control the user’s vital signs, particularly their

breathing rate. It tracks the user’s breathing rate.

Continually using a respiratory sensor and sets a

threshold (e.g., 50 breaths per minute). The

technology alerts family members to the anomaly if

the measured breath rate surpasses this threshold,

suggesting possible respiratory problems. The system

can be equipped with extra sensors to track

temperature and pulse rate, among other vital signs.

The system sends out a warning message if these

sensors pick up on a high pulse rate or rising

temperature that is above typical values. Family

members are prompted to check on the user or seek

medical assistance if needed after receiving this alert,

which may indicate a potential health risk.

Figure 13: Respiratory alert message

The technology alerts family members to the

anomaly if the measured breath rate surpasses this

threshold, suggesting possible respiratory problems.n

order to improve its monitoring capabilities, the

system incorporates extra sensors to monitor vital

signs including temperature and heart rate.

The sensor detects anomalous readings, like an

elevated temperature or a rapid pulse rate, and the

system sends out a warning message. In order to

address any possible health dangers, this alert asks

family members to check on the user or, if required,

seek medical attention. The system enables

authorized individuals to visually examine the user’s

condition in real-time for increased safety and

monitoring. In addition to addressing urgent safety

issues, this system supports ongoing health research

and monitoring. This methodical approach guarantees

that the system will not only work efficiently but also

have the capacity to grow and adapt in the future to

meet new demands for health monitoring.

5 CONCLUSIONS

In conclusion, Health has become one of the global

challenges for humanity. The design and

implementation of a health monitoring system are

presented in this study. Users can use this method to

find their health indicators, which could help them

manage their health in the long run.A significant

advancement in real-time Seniors’ safety, wellbeing,

and quality of life can all be significantly improved

by integrating IoT (Internet of Things) and cloud

Empowering Elderly Health with IoT and Cloud Computing

519

computing into healthcare. Healthcare systems are

able to measure environmental conditions, detect

crises (such as falls), and continually monitor vital

signs through the use of a linked network of sensors,

microcontrollers, and cloud platforms. Immediate

action is made possible by real-time data collecting

and processing, including alerting loved ones or

medical professionals to potentially life threatening

situations. Elderly people can be watched over by

family members and caregivers from anywhere,

allowing for rapid action without requiring their

physical presence all the time. Vital signs, such as

heart rates, breathing issues, or fall detection, can

send out instant alerts to family members or medical

specialists. Large- scale health data can be stored and

analyzed over time with cloud computing, allowing

for more precise and individualized healthcare

decisions based on patterns and trends. Elderly people

feel more secure and independent thanks to IoT and

cloud solutions, which also lessen the strain on

caregivers by guaranteeing appropriate monitoring.

By reducing needless hospital visits and enabling

early diagnosis of health issues, the capacity to

automate monitoring and communicate remotely can

lower healthcare expenses. Overall, Healthcare for

the elderly is being revolutionized bIoT and cloud

computing, which is making it more efficient,

individualized, and responsive. We can guarantee that

elders live longer, healthier lives with more freedom

by using these technologies.

By encouraging independence, lowering

healthcare expenses, and facilitating early health

issue identification and treatment, smart home

healthcare solutions help the aged. By remotely

monitoring well-being, they improve caregivers'

peace of mind. Accuracy in fall detection and health

monitoring is increased by integrating data from

sensors such as gyroscopes, accelerometers, and

bioimpedance devices. This data is analyzed by

machine learning algorithms to anticipate and stop

possible health issues. Better health outcomes and

more effective senior care are guaranteed by this

proactive strategy.

ACKNOWLEDGEMENTS

The author extends sincere thanks to Jyothi mam,

Ashwini, Mahender, and Prudhwi Raj for their

financial support for the conference and for their

valuable contributions in discussing the results and

providing feedback.

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