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A Review of Real-Time Health Monitoring System using Wearable IoT Devices and Cloud Storage

Priya Pal1, Deepshikha2

1Master of Technology, Computer Science and Engineering, Lucknow Institute of Technology, Lucknow, India

2Assistant Professor, Department of Computer Science and Engineering, Lucknow Institute of Technology, Lucknow, India

Abstract - Integration of wearable Internet of Things (IoT) devices and cloud storage revolutionized the real time health monitoring field which open new horizon for personalized and proactive healthcare. In this review paper, we explore the state of the art, issues, and future directions of such real time health monitoring systems using wearable IoT devices and cloud based data management. Continuous collection of vital health parameters including heart rate, blood pressure, temperature, and oxygen saturation are supported from wearable IoT devices (i.e. smartwatches, fitness bands, biosensors). Robust comunication protocols like Bluetooth, Wi-Fi and Zigbee used to trasfrom data in a reasonable linear seasion therefore without losing any at all in the air, Data trasfered to the cloud, which is where the data is collected, processed and analysed. Health data can be stored with scalable, secure, and available solution for cloud storage for managing enormous tonnes of data, advanced analytics and remote access for healthcare providers. Nevertheless, there are many reasons behind implementing such systems, such as data privacy concerns, power consumption, latency, and interoperability issues. In the view of deploying wearable IoT devices with cloud storage, real-time health monitoring, this paper reviews the architecture of the real time health monitoring system and discusses the technical and ethic challenges of the deployment in the system. Challenges that real-time health monitoring systems are facing, and the application of emerging technologies can lead to successful real time health monitoring systems that will change the ways of delivering healthcare, and improve patients’ outcomes and reduce the burden on the healthcare system. Finally, we hope this review helps gain a comprehensive understanding of the current status of the art and drives innovation in this rapidly growing field.

Key Words: IoT, Wearable Devices, Cloud Storage, RealTime Health Monitoring, Healthcare, Data Privacy, ArtificialIntelligence,MachineLearning.

1.INTRODUCTION

1.1.Background

Realtime health monitoring has become a very critical innovation area in the healthcare industry and the technology continues to advance in speed, changing the

way healthcare providers offer their services. Health monitoringsystems thatare real – time,allowcontinuous monitoring of vital health parameters and helps in early detection of abnormalities and timely medical intervention. As the stakes are particularly high when it comes to chronic diseases, postoperative care and elderly health monitoring, where small time differences can generate significant improvement in patient outcomes, this capability of epidemiology appears to be very important. The need for such systems arises from the demand for personal, available, and efficient healthcare solutions to alleviate the burden on existing healthcare infrastructure and improve the quality of life of the individuals.

1.2.Importance of IoT in healthcare

One of the strongholds of revolutionizing the healthcare by IoT is the enhanced connectivity between various devices such as sensors, data platforms, all through the Internet of Things (IoT) enabling seamless connectivity between devices, sensors, and data platforms. The development of wearables using the Internet of Things (IoT) devices like smart watches, fitness bands, and biosensors, has gained a great momentum for the purposes of tracking the evolution of health metrics, including heart rate, blood pressure, temperature, and oxygen levels. These devices collect data in real time and send it to cloud based platforms for storage and analysis giving healthcare professionals data to work with. IntegrationofIoThealthcaregoesbeyondprovidingbetter

Figure-1: Real Time Tracking.

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care to patients and can help in remote monitoring while minimizing the requirement of patients to visit the hospital very frequently or even proactively carry out theirhealth.

Figure-2: Importance of IoT in healthcare

1.3.Challenges in traditional health monitoring systems

However,actualhealthmonitoringsystemsarechallenged by a number of difficulties that hinder their effectiveness. The conventional methods generally involve periodic inspecting and by hand taking data, which can result in delayfordiagnosisandtreatment.Also,thesesystemsare often costly and require specific equipment and human support, cutting them off from a large part of the population, especially from those living in remote or underserved areas. In addition, due to the limited real time data processing and the inability to integrate with modern technologies, the service is unable to deliver timelyandaccuratehealthassessment.Itisforthisreason that there is an urgent demand for novel solutions employingIoTandcloudcomputingthatcircumventthese limitations.

1.4.Objectives

of the Review Paper

The major aim of the review paper is to summarize the health monitoring systems using wearable IoT based devicesandcloudstorage.This paperattemptsto explore the architecture, functionality and benefits of these systemsandthetechnicalandethicalchallengesregarding its implementation. Furthermore, it aims at identifying future research lines, by considering, among others, the development of energy efficient wearable devices and the integration of artificial intelligence (AI) and machine learning(ML)forpredictiveanalytics.

1.5.Scope

and Organization of the Paper

In this paper, we organize this topic in order to have a complete understanding of the topic starting from review on existing literature and the evolution of wearable IoT

devices in healthcare. It then explores how cloud storage helps to manage health data, and then goes into the architectureoftherealtimehealthmonitoringsystems.In addition, the challenges and future directions in this field arealsodiscussedinthe paper aswell asthesummary of main findings and some recommended future research. This review intends to add to the literature on how technology can be used to improve healthcare delivery and enhance patient outcomes through its focus on addressingtheseaspects.

2.LITERATURE REVIEW

2.1.Overview

of Existing Research on Health Monitoring Systems

In the past few decades, there has been a tremendous growth in the field of health monitoring systems due to growth in sensor, wireless communication, and data analytics. The power of real time health monitoring systems to transform healthcare is already well depicted by existing research in which essential vital signs can be continuously tracked and health issues sought to be detected at an early stage. These systems have been studied to show they are effective at managing chronic diseases such as diabetes, cardiovascular condition and post surgical care and elderly health monitoring. While researchers have taken on many different ways of integrating wearable devices with cloud based platforms, they have chosen to focus on real time data processing with remote accessibility. Yet, though progress was made in this work, a thorough review integrating the conclusionsofthesestudiesstillremainstobeconducted, togetherwithrecognitionofpointsforadditionalavenues ofresearch.

Figure-3: Patient Monitoring System.

2.2.Evolution of wearable IoT devices in healthcare

The significant progress in technological advances and increasingadoptionof wearableIoTdevices in healthcare

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

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over the years signifies the evolution of the concept of these devices. Initially, early wearable devices were strictly limited in functionality, the availability of single parameter such as, step counting, heart rate monitoring. These devices are much more sophisticated than they were over time, having included multiple sensors to measure a lot of health metrics such as blood pressure, oxygen saturation, and even truly electrocardiogram (ECG) readings. The integration of IoT connectivity has enabledtheirdatatransmissioncapabilitytosmartphones and cloud platforms. It has been driven by the increasing need for personalized healthcare solutions and for continuous monitoring beyond clinical settings. This, therefore, led to the adoption of wearable IoT devices which have since been indispensable tools both for the patientsandthehealthcarepersonnel;providingrealtime healthconditioninsightsandtimelyinterventions.

2.3. Cloud Storage Management of Health Data

Managing the vast amount of data generated by wearable IoT devices can no longer live in the cloud and cloud storage has become a key part in this process. It has revolutionized the way healthcare is used, being able to store, processed and analyzed health data in the cloud allows for remote monitoring and use of data driven decision making. The scalability of large datasets is ensured with the help of cloud platforms as these offer solutions that are secure enough for handling such datasets and also providing access for healthcare professionalsto patient informationat any time and from any place. It also provides cloud based analytics tools whichsupport extractionofmeaningfulinsightsfromraw dataforearlydiagnosisandpersonalizedtreatmentplans. However, the use of cloud storage in healthcare has brought up issue about security and the protection of privatedataasconfidentialhealthinformationoperatesto befreefromunwantedaccessibilityaswellasbreaches.In order to diffuse the use of cloud based health monitoring systemsthesechallengesmustbeaddressed.

2.4.Comparative Analysis of Different Real-Time Health Monitoring Systems

Different approaches and technologies are taken up in a comparative analysis of different real time health monitoring systems. Some systems are used to monitor specific health parameters, e.g. heart rate, glucoses levels, while others cover wide range of many parameters. However, the router systems choices of the communicationprotocols,suchasBluetooth,Wi-Fi,Zigbee etc., also varies in terms of its performance and usability. Moreover, the AI and machine learning algorithms integration gave birth to more advanced data analysis through predictive analytics and anomaly detection. However, the usefulness of these systems depends on accuracy,reliabilityandthe user-friendliness.Thisreview compares strengths and limitations of different systems and provides a clearer picture of the space we are in and what would constitute it as a good real time health monitoringsolution.

3.WEARABLE IOT DEVICES FOR HEALTH MONITORING

3.1.Types of wearable IoT devices (e.g., smartwatches, fitness bands, biosensors)

Nowadays,wearableIoTdeviceshavebeenwidelyusedin the field of modern healthcare as a powerful tool to monitor and manage the real time health. The format of these devices can include smartwatches, fitness bands, biosensors, or even smart clothing. How about smartwatches and fitness bands, which are equally popularandoffertheusercontinuoustrackingofphysical activity, heart rate and sleep patterns. On the other hand, biosensors are most frequently constructed to function in certain medical applications, such as glucose monitoring for the diabetic and ECG monitoring for the cardiac patient. Considering the wearables, there is a newer segment of them which is Smart clothing, which are the clothes embedded with sensors to capture the physiological signals without the additional device. The variety of wearable IoT devices caters to the diverse needs,andhencecanbeusedasversatiledevices,toggling itsgeneralwellnessandspecializedmedicalcareneeds.

3.2.Key features and functionalities

It is the essential attributes and features of wearable IoT devices that make them inevitable part of health monitoring. These devices have extremely advanced sensorsthatcantakeanumberofdifferenthealthmetrics: heart rate, blood pressure, body temperature, oxygen saturation (SpO2), and even an electrocardiogram (ECG). GPS is also usually part of the feature set of many wearables for tracking physical activity, as well as environmentalsensorssuchasUVexposureorairquality. In addition to data collection, such devices are normally packaged with a companion mobile application, which is

Figure-4: Role of cloud storage in managing health data

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 12 Issue: 04 | Apr 2025 www.irjet.net p-ISSN: 2395-0072

designedtoprovideuserswithknowledgeontheirhealth based on the collected data, by recommendations and alerts.Evensomeadvancedmodelscanbeintegratedwith telemedicine platforms so that users' health data can be shared directly with healthcare providers for remote consultations.

3.3.Used sensors for wearable devices (heart rate, temperature, SpO2, ECG)

Within wearable IoT devices, the functionality of these devices is based around the sensors used. Blood flow measurement through the heart rate sensors, which are generally based on photoplethysmography (PPG), and body temperature measurement using the temperature sensors for detecting the fever or other abnormal conditionsareassessed.Usually,itisusefulforpatientsto haverespiratoryconditions.Thesesensorsuselight-based technologytomeasurebloodoxygenlevels.Somehighend wearables have ECG sensors which give a deep dive into cardiac activity to detect arrythmias and other heart related problems. Both these sensors work together to createacompletepictureofthehealthoftheuserandhelp inearlydiagnosisofproblemsandpromptmedicalaction.

3.4.Communication protocols (e.g., Bluetooth, Zigbee, Wi-Fi)

The task of communication protocol in the wearable IoT devices is to allow data being acquired by them to be transmitted efficiently & securely to other devices or to cloud platforms. Most commonly used protocol is Bluetooth for low power consumption and support for widely available smartphones and tablets. It is often the case that Wi-Fi is used for faster data transmission, more so when a large number of data needs to be uploaded to the cloud. Another low power protocol is Zigbee and it is used in some specialized applications where multiple devices have to communicate in a network. The reason of choosing the communication protocol depends on the various factors like data volume, transmission range and power efficiency etc., whichsignificantlyaffect theoverall performanceofthewearabledevice.

3.5.Differing power consumption, accuracy, and user comfort problems in wearable IoT device design.

However, wearable IoT devices come with several advantages and are considered a real challenge to design. Theinherentconcernistheirpowerconsumptionasthese devicesareusuallybatterypoweredandrequirehavingto operateforhourswithoutmuchrecharging.Toensurethe user convenience, designers should strike the balance between the functionality and energy efficiency. It is also critically important because getting wildly inaccurate readings could result in giving the wrong health assessment and even bad decision making. This means

user trust is dependent on the reliability and correct calibration of sensors. Further, the presentable and comfortable design, wearing it with a relatively lightweight, ergonomic, and nonintrusive item is another major consideration to encourage dynamic user involvement. As these challenges exist, innovative engineeringsolutionsandwellunderstooduserneedsare needed to see wearable IoT devices provide both performanceandusabilityintherealworld.

4.CLOUD STORAGE FOR HEALTH DATA MANAGEMENT

4.1.Overview of cloud storage technologies

The cloud storage technologies has been a staple solution forhealthmonitoringrelatedmodernsystemsduetotheir highly scalable and efficient nature for handling the very largedatageneratedbywearableIoTdevices.Healthdata can be stored remotely, on servers of a third party provider of cloud storage with no need for local storage infrastructure. As it utilizes distributed systems to guarantee availability of data, reliability, and fault tolerance, this technology is a suitable choice for processing important and sensitive health information. Cloud storage made it possible to store terabytes of data and to allow real time access that enabled health data to bemanageddifferently,withseamlessintegrationtoother healthcaretechnologiesandplatforms.

4.2.Advantages

of cloud storage in health monitoring systems

Its important characteristic characteristic is the ability of the cloud storage in health monitoring systems to be scalable. The proliferation of wearable devices that are connected and, consequently, the amounts of health data that are being generated, will only increase. This increasing data load is easily scalable for cloud storage, which staff and patients can still easily access without interruption. Moreover, cloud storage facilitates remote accessfromanywhereforaccessingthedata,whichmakes healthcare professionals monitor patients in live, where they are at the moment wherever in the world. This is most helpful for telemedicine and remote patient monitoringusecaseswheregettinghealthdataasquickly as possible is important for the best outcomes. Additionally,cloudplatformstendtoofferalreadypresent data analytics tools for processing and visualization of healthdatathatcanaidintheprocessofmakingdecisions andpersonalizedcare.

4.3.Data security andprivacy concerns

Although cloud storage has many advantages, the use of cloud storage in healthcare brings up grave security and privacy issues. The health data is extremely sensitive and the exposure of it to unauthorized access or breach could cause serious implications to the patients and healthcare

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providers. Confidentiality, integrity and availability of stored health data in the cloud is of the highest concern. Data encryption is commonly used to prevent unauthorized access to data while in transit or at rest. Furthermore, since cloud storage services may be subject to various legal and regulatory frameworks, they must adhere to laws like the Health Insurance Portability and AccountabilityAct(HIPAA)ortheGeneralDataProtection Regulation (GDPR) to guarantee that cloud storage providers maintain strict security and privacy controls. These concerns should be addressed by a robust combination of technical measures, legal and ethical guidelines.

4.4.Cloud platforms used for healthcare (e.g., AWS, Google Cloud, Microsoft Azure)

There are several cloud platforms for the healthcare industry already emerged as leaders in health monitoring systems, with their peculiar services specifically adapted tosuchpurposes.Therearemanydifferentplatformsthat arecommontotheusercommunity,andofthese,Amazon Web Services (AWS), Google Cloud, and Microsoft Azure are the largest and most commonly used with data storage, processing, and analytics tools available. In fact, these platforms have such healthcare specific solutions in hand like HIPAA compliant storage and machine learning tools for predictive analytics. For instance, Amazon HealthLakeisaserviceofferedbyAWStostore,transform, and analyze health data at scale. In the same way, Google Cloud provides Healthcare API for integrating health data from different sources. The Microsoft Azure machine learningserviceandInternetofThings(IIoT)Hubarealso used quite widely for building scalable and intelligent health monitoring platforms. Health care platforms using thecloudallowhealthcareinstitutionstohavethepower of the cloud while guaranteeing data complacency and security.

4.5. Cloud for Data processing and Analytics

The modern health monitoring systems include data processingandanalyticsinthecloud.Afterthehealthdata isstoredinthecloud,advancedalgorithmscanbeusedto process this data and extract the valuable insights. For example, machine learning models can utilize the heart rate or blood pressure data to learn patterns and predict the potential arising health issues beforehand. Real time monitoring and visualization of health data by healthcare professionals also becomes possible with the help of analytics tools running on the cloud. Furthermore, the cloud enables combining of data from various sources including wearable devices, electronic health records (EHR’s)andlaboratoryresultsintoacompletepictureofa patient’s health. It enables more data processing and analytics in a holistic manner that enables the delivery of more personalized and proactive care leading to better patientoutcomesandreducedcostsofhealthcare.

5.REAL-TIME HEALTH MONITORING SYSTEM ARCHITECTURE

5.1.System architecture and components

A real-time health monitoring system is a complex yet a well organised framework of architecture to collect, transmit, process andanalysehealthdata seamlessly.The system is comprised mainly of three parts: wearable IoT devices, a communication network and cloud storage and processingplatforms.Thedata collectionlayerconsists of wearable devices like smartwatches, fitness bands, biosensors, etc. which collect data in the form of the mentionedvitalhealthmetrics-heartrate,bloodpressure, temperature, and the oxygen saturation values. These devicesarefullofsensorsandmicroprocessorthatpermit continuous monitoring and preliminary data processing. The wearable devices use communication network that is protocols such as Bluetooth, Wi-Fi and Zigbee to act as a bridgeforthewearabledeviceswiththecloudsothatthe data is will be transmitted safely and securely. Lastly, the cloud platform acts as the core system of the system as it possesses storage, advanced data processing, and analytics capabilities. These elements are stitched together to create a unified architecture capable of collecting user and provider actionable insights in realtime.

5.2.Data gathering and sending from the wearable devices to the cloud storage.

In a real time health monitoring system, the data flow starts from the wearable devices where the same are continuously collecting health related data from the user. Short range communication protocols like Bluetooth are used to transmit this data to a gateway device which can be a smartphone or a dedicated hub. This allows the gateway to serve as an intermediary, collecting data from many wearables and sending it to the cloud over the internet. After that, the data is put into a large server calledcloudwhereitisstoredinsafedatabaseswhichare processed using advanced algorithms. Data processing in realtimeisanimportantcomponentofthesysteminthat it allows for the instantaneous discovery of abnormal or critical health conditions. For example, when a wearable device spots an irregular heart rate, the system can immediately reach out to the user and/or to their healthcare provider to address it immediately. However, such a smooth flow of data from wearable devices to the cloud allows for continuous and responsive health monitoring.

5.3.Real-time data processing and analysis

At the core of the system’s capabilities are real-time data processing and analysis supported by the delivery of actionableinsightsanddecision-makingcapabilities.Once dataisputinthecloud,afterthatitpassesthroughvarious

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

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stages of handling containing filtering, normalization and analysis. Often data is ‘crunched’ by machine learning algorithms and/or artificial intelligence (AI) tools to identify patterns, trends, and anomalies in the data. For instance, predictive analytics can help predict future health issues from the historical data, and anomaly detection algorithms can raise suspicion when readings are abnormal. Real time processing also enables generationofalertsandnotificationsthatcanbepushedto users or healthcare providers via mobile or web application. Through this ability, important health situations are dealt with right away, thereby minimizing the possibility of complications and enhancing general results.

5.4.Integration with mobile and web applications

A key feature of real time-health monitoring systems is integration with mobile and web applications to enable easy access to health data and insights to users and healthcare providers. The primary interface for the users is via mobile applications by which they can look at their health metrics, get alerts and track their progress over time. They are popular because many apps tend to have features like goal setting, reminders and consequently personalized recommendations that increase the user engagement with the health plan. However, web applications are intended for healthcare providers and provideadeeperviewofapatient'sdataandsophisticated analyticstools. These applicationsare integrated with the cloudplatforminawaythatensuresthatwhenthedatais synchronized between these devices, all the stakeholders involvedhaveaccesstoit.Theseamlessconnectivitythese solution provide is improving user experience, and also ensureoptimalcollaborationwithpatientsandhealthcare providers.

5.5.Case studies of existing systems

Insights on the design, implementation and impact from existing realtime health monitoring systems are based on casestudies.WeknowthattheAppleWatchisonedevice that has been widely adopted for monitoring heart rate, detecting irregular rhythms, and even performing ECG readings. The Health app and cloud-based services integration also enables users to track their health data over time and share it with hospitals. An example of note is the Philips HealthSuite Digital Platform that makes use of cloud storage and analytics to derive personalized healthinsightsandremotemonitoringsolutions.Likewise, theFitbitecosystemiscomposedofwearables,mobileapp and cloud platform to provide end to end health and fitness tracking. Gleans from these case studies have proved that real time health monitoring systems can be usedtoimprove healthoutcomes, and canalso be further innovated. This examination of the examples can help researchersanddeveloperstozeroinonbestpracticesas well as hurdles that they can overcome to develop even moreadvanced,moreuserfriendlysystemsinthefuture.

6.CHALLENGES AND FUTURE DIRECTIONS

6.1.Technical challenges (e.g., latency, scalability, interoperability)

Despite the substantial progress toward developing such real time health monitoring systems there are still a few technical issues that need to be addressed before their wide use and effectiveness. Latency is one of the primary challenges because real time systems imply that a system should process and respond to the data in real time, instantaneously. For example, delays of transmission or analysisofdatamayinterferewiththesystem’scapability to issue timely alerts in cases that are of critical health importance. Another big issue is scalability while the amount of interconnected devices continues to grow and the health data volume rises, the infrastructure must be abletoscaletomanylargeoperations.IfDHTsdonothave interoperability then they can be unable to communicate with one another without polymorphous protocols and data formats. In recognizing that there are technical challenges to overcome in order to make the above a reality, new technologies and methods have to be developedtohelpsolvetheseexistingissues.

6.2. Data privacy / consent / legal and ethical issues

However real time health monitoring system poses some ethical or legal issues in its implementation especially relatingtodataprivacyandconsent.Sincethehealthdata is sensitive by nature, its misuse or unauthorized access could have severe ramifications to individual people. Without a doubt, cryptography provides the appropriate encryption methods of this data that must be considered sensitive and the need for strict access controls to ensure the confidentiality and security of such data. Aside from that, the ethical issue of obtaining informed consent from usersfordata collectionandsharingisalso acomplicated one, especially for vulnerable populations like the elderly or those with cognitive impairments. Addressing these concernsinvolvescomplyingtoregulationsliketheHealth Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation (GDPR) which in turn, adds layers of complexity to system design and implementation. To approach this critically, there is the need to balance the benefits of usage of real time health monitoring with the upkeep of user privacy and autonomy.

6.3.Wearable IoT devices. We can analyze future trends in the wearable IoT devices and cloud storage as soon as possible.

Wearable IoT devices and cloud storage regarding health monitoring are ready for further development in the future provided that technology is evolving to meet the

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

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ever growing needs of the user. The sensors in wearable devices will become more sophisticated while offering a greater amount of health metric measurement and batteries will improve, allowing for greater usage. Also, the creation of wearables based on flexible and biocompatible materials might result in a new type of wearables,whicharemorecomfortableandlessintrusive. Advances in edge computing and fog computing on the cloud storage front are most likely to make data processing efficiency faster and latency reduced, making real time monitoring possible faster and more reliably. Furthermore, blockchain technology adoption could also make the data more secure and transparent thereby resolving some of the privacy issues relating to cloud storage. In this light, these trends account for a future when wearable IoT devices and cloud storage will work more harmoniously together for providing more personalized,proactive,andhomebasedhealthcare.

6.4.Potential advancements in AI and machine learning for health monitoring

The purpose of artificial intelligence (AI) and machine learning (ML) is to revolutionize health monitoring systems by making more in depth data analysis and prediction of the situation possible. By analyzing huge amounts of health data, AI algorithms are able to detect patterns and trends that are not obvious to human observers, thus making it possible to detect diseases in their earliest stages and map individual treatment plans. Users and healthcare providers can then assess health outcomes based on these predictions or use the predictions to make decisions based on prior data. For instance, AI systems might be able to tell whether it’s at risk for having a heart attack or stroke based on actual data from wearable devices at that moment in time and prevent it from occurring. In addition, with the incorporation of AI and ML into health monitoring systems, these systems can likewise serve as a means for automated decision making and remote diagnosis, improving efficiency and effectiveness of healthcare delivery.

7.CONCLUSION

The conclusion of this review paper therefore discusses the disruptive nature for health monitoring systems that relyonwearableIoTdevicesandcloudstorage.Important points that were noted are the effectiveness of wearable devicesingatheringcontinuoushealthdata,significanceof cloud storage in managing and analyzing the data, and integration of these technologies for users and healthcare providers to find actionable insights. The advanced communication protocols and real time data processing help these systems architecture to support timely detection of health anomalies and can facilitate proactive healthcare interventions. But these systems face challenges including latency, scalability, data privacy, and

interoperabilitybeforethefullpotentialofthesystemcan be embraced. Health monitoring is further augmented by the integration of AI and machine learning to provide predictionsandpersonalizedcaresolutions.

In modern healthcare, real-time health monitoring systemshavetheresponsibilityofsavingmanylives.They offer these systems that enable an individual to manage his or her wellbeing by being continuously informed and personalized about his or her health and the associated states. For healthcare providers, they are powerful tools for remote patient monitoring, allowing to reduce the need for recurrent trips to the hospital and to take action attheearlieststagesofcriticalsituations.Realtimehealth monitoring system is a gap bridging system between patients and healthcare professionals with the ability for improvementofhealthoutcomes,reductionofhealthcost and improvement of the quality of healthcare. As a result of their role in the management of chronic diseases, support of elderly care as well as their use in delivering preventive healthcare, they are necessary to tackle the problemsofthemodernhealthcaresystems.

REFERENCES

1) Al-Fuqaha, M. Guizani, M. Mohammadi, M. Aledhari, and M. Ayyash, "Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications," IEEE Communications Surveys & Tutorials, vol. 17, no. 4, pp. 2347–2376, 2015. DOI: [10.1109/COMST.2015.2444095](https://doi.org/10 .1109/COMST.2015.2444095).

2) S.Movassaghi,M.Abolhasan,J.Lipman,D.Smith,and A. Jamalipour, "Wireless Body Area Networks: A Survey," IEEE Communications Surveys & Tutorials, vol. 16, no. 3, pp. 1658–1686, 2014. DOI: [10.1109/SURV.2014.012214.00007](https://doi.org /10.1109/SURV.2014.012214.00007).

3) M. R. Yuce, "Implementation of Wireless Body Area Networks for Healthcare Systems," Sensors and Actuators A: Physical, vol. 162, no. 1, pp. 116–129, 2010. DOI: [10.1016/j.sna.2010.06.004](https://doi.org/10.101 6/j.sna.2010.06.004).

4) P.K.Sahoo,S.L.Mohapatra,andS. P.Wu,"Analyzing HealthcareBigDatawithPredictionforFutureHealth Condition,"IEEEAccess,vol.4,pp.9786–9799,2016. DOI: [10.1109/ACCESS.2016.2647618](https://doi.org/1 0.1109/ACCESS.2016.2647618).

5) A. J. Jara, M. A. Zamora, and A. F. Skarmeta, "An Internet of Things–Based Personal Device for Diabetes Therapy Management in Ambient Assisted Living (AAL)," Personal and Ubiquitous Computing,

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056

Volume: 12 Issue: 04 | Apr 2025 www.irjet.net p-ISSN: 2395-0072

vol. 15, no. 4, pp. 431–440, 2011. DOI: [10.1007/s00779-010-03531](https://doi.org/10.1007/s00779-010-0353-1).

6) S.R.Islam,D.Kwak,M.H.Kabir,M.Hossain,andK.-S. Kwak, "The Internet of Things for Health Care: A ComprehensiveSurvey,"IEEEAccess,vol.3,pp.678–708, 2015. DOI: [10.1109/ACCESS.2015.2437951](https://doi.org/1 0.1109/ACCESS.2015.2437951).

7) M.Chen,S.Gonzalez,A.Vasilakos,H.Cao,andV.C.M. Leung, "Body Area Networks: A Survey," Mobile Networks and Applications, vol. 16, no. 2, pp. 171–193, 2011. DOI: [10.1007/s11036-010-02608](https://doi.org/10.1007/s11036-010-0260-8).

8) A. Zanella, N. Bui, A. Castellani, L. Vangelista, and M. Zorzi, "Internet of Things for Smart Cities," IEEE Internet of Things Journal, vol. 1, no. 1, pp. 22–32, 2014. DOI: [10.1109/JIOT.2014.2306328](https://doi.org/10.11 09/JIOT.2014.2306328).

9) R. Ramakrishnan, S. Gaur, and S. C. Sharma, "IoTBased Smart Health Monitoring System for Remote Locations,"IEEEInternetofThingsJournal,vol.6,no. 3, pp. 4885–4892, 2019. DOI: [10.1109/JIOT.2019.2903198](https://doi.org/10.11 09/JIOT.2019.2903198).

10) M. A. Rahman, M. S. Hossain, and G. Muhammad, "A Secure and Privacy-Preserving Smart Healthcare System Using IoT and Cloud Computing," IEEE Internet of Things Journal, vol. 6, no. 5, pp. 8289–8301, 2019. DOI: [10.1109/JIOT.2019.2923841](https://doi.org/10.11 09/JIOT.2019.2923841).

11) S.Baker,W.Xiang,andI.Atkinson,"InternetofThings for Smart Healthcare: Technologies, Challenges, and Opportunities,"IEEEAccess,vol.5,pp.26521–26544, 2017. DOI: [10.1109/ACCESS.2017.2775180](https://doi.org/1 0.1109/ACCESS.2017.2775180).

12) A. M. Rahmani, T. N. Gia, B. Negash, A. Anzanpour, I. Azimi, M. Jiang, and P. Liljeberg, "Exploiting Smart eHealthGatewaysattheEdgeofHealthcareInternetof Things: A Fog Computing Approach," Future Generation Computer Systems, vol. 78, pp. 641–658, 2018. DOI: [10.1016/j.future.2017.02.014](https://doi.org/10.1 016/j.future.2017.02.014).

13) D.Miorandi,S.Sicari,F.DePellegrini,andI.Chlamtac, "Internet of Things: Vision, Applications, and Research Challenges," Ad Hoc Networks, vol. 10, no.

7, pp. 1497–1516, 2012. DOI: [10.1016/j.adhoc.2012.02.016](https://doi.org/10.1 016/j.adhoc.2012.02.016).

14) G.Yang,L.Xie,M.Mäntysalo,X.Zhou,Z.Pang,L.Xu,S. Kao-Walter, Q. Chen, and L.-R. Zheng, "A Health-IoT Platform Based on the Integration of Intelligent Packaging, Unobtrusive Bio-Sensor, and Intelligent Medicine Box," IEEE Transactions on Industrial Informatics,vol.10,no.4,pp.2180–2191,2014.DOI: [10.1109/TII.2014.2307795](https://doi.org/10.110 9/TII.2014.2307795).

15) K. K. Patel, S. M. Patel, and P. G. Scholar, "Internet of Things-IOT: Definition, Characteristics, Architecture, Enabling Technologies, Application & Future Challenges," International Journal of Engineering Science and Computing, vol. 6, no. 5, pp. 6122–6131, 2016. DOI: [10.4010/2016.1482](https://doi.org/10.4010/2016 .1482).

16) J. Gubbi, R. Buyya, S. Marusic, and M. Palaniswami, "Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions," Future Generation Computer Systems, vol. 29, no. 7, pp. 1645–1660, 2013. DOI: [10.1016/j.future.2013.01.010](https://doi.org/10.1 016/j.future.2013.01.010).

17) M. A. Ferrag, L. Maglaras, A. Argyriou, D. Kosmanos, and H. Janicke, "Security for 4G and 5G Cellular Networks: A Survey of Existing Authentication and Privacy-Preserving Schemes," IEEE Communications Surveys&Tutorials,vol.20,no.1,pp.206–224,2018. DOI: [10.1109/COMST.2017.2762345](https://doi.org/10 .1109/COMST.2017.2762345).

18) A.Whitmore, A.Agarwal,andL.Da Xu,"TheInternet of Things A Survey of Topics and Trends," Information Systems Frontiers, vol. 17, no. 2, pp. 261–274, 2015. DOI: [10.1007/s10796-014-94892](https://doi.org/10.1007/s10796-014-9489-2).

19) S. Misra, M. Maheswaran, and S. Hashmi, "Security Challenges and Approaches in Internet of Things," Springer Briefs in Electrical and Computer Engineering, 2016. DOI: [10.1007/978-3-319-309279](https://doi.org/10.1007/978-3-319-30927-9).

20) P. P. Ray, "A Survey on Internet of Things Architectures," Journal of King Saud UniversityComputerandInformationSciences,vol.30,no.3,pp. 291–319, 2018. DOI: [10.1016/j.jksuci.2016.10.003](https://doi.org/10.1 016/j.jksuci.2016.10.003).

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21) C. Doukas and I. Maglogiannis, "Bringing IoT and Cloud Computing towards Pervasive Healthcare," 2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, pp. 922–926, 2012. DOI: [10.1109/IMIS.2012.26](https://doi.org/10.1109/IM IS.2012.26).

22) A.Al-Fuqaha,M.Guizani,M.Mohammadi,M.Aledhari, and M. Ayyash, "Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications," IEEE Communications Surveys & Tutorials, vol. 17, no. 4, pp. 2347–2376, 2015. DOI: [10.1109/COMST.2015.2444095](https://doi.org/10 .1109/COMST.2015.2444095).

23) M. Chen, Y. Ma, J. Song, C.-F. Lai, and B. Hu, "Smart Healthcare: Making Medical Care More Intelligent," Global Health Journal, vol. 2, no. 3, pp. 62–65, 2018. DOI: [10.1016/j.glohj.2018.07.001](https://doi.org/10.10 16/j.glohj.2018.07.001).

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