IoT Based Health Monitoring System Research Articles

Health Monitoring and Prediction Using Non-invasive Sensors in IoT Environment

Introduction: IoT's blend with non-invasive sensors has made health state prediction possible and constant real-time monitoring transformed healthcare. Using photoplethysmography (PPG) and electrocardiograms (ECG), this device evaluates important parameters including heart rate, blood oxygen saturation, and blood pressure. As healthcare systems face increasing demands, this technology provides a patient-centered and efficient method for long-term health tracking—needed for early intervention and management of chronic diseases. Objectives: The main goal is to evaluate using time-series data from PPG and ECG sensors the efficiency of an IoT-enabled health monitoring system coupled with machine learning models in predicting health conditions including arrhythmias and hypoxia. Methods: This system detects events based on temporal pattern recognition by use of Long Short-Term Memory (LSTM) networks and Random Forest classifiers. Noise reduction is preprocessed and wearable device data is labeled for training of machine learning models. The design combines wearable sensors, a smartphone app, and cloud-based analysis for continuous monitoring and real-time input. Results: Experimental data shows that the LSTM model attained a 95% accuracy while the Random Forest classifier attained a 92.5% accuracy. Both models displayed remarkable accuracy and recall even while the LSTM model excels in identifying anomalies in time-series data and the Random Forest classifier skillfully detects health events depending on certain criteria. Conclusions: This study demonstrates the capability of IoT-based health monitoring systems to enhance patient outcomes through continuous, non-invasive monitoring and predictive analytics. Despite its potential, difficulties persist, including data security, sensor reliability, and energy efficiency, necessitating additional research for broad use and clinical integration.

Iot Based Health Monitoring System for Human

Iot Based Health Monitoring System for Human

IoT-Based Health Monitoring System

Wireless body area networks, known as body sensor networks, are wireless networks of wearable computing devices. In this case, the wireless network deployed is the Internet of Things or IoT. This special WBAN will allow nurses and doctors to have a real-time view of the patient's physiological data and thereby detect unusual activities in the patient's health. This is achieved by having a device that allows the patient to collect physiological data using sensors controlled by an Arduino microcontroller board. Doctors can then log into the website and monitor the patient's health status in real-time and over some time.

IOT Based Health Monitoring System Using FPGA

IOT Based Health Monitoring System Using FPGA

IoT-Based Solutions for Monitoring Cattle Health: A Comprehensive Review

The integration of Internet of Things (IoT) technologies in agricultural practices has revolutionized livestock management, particularly in the realm of health monitoring for cows. This review paper presents a comprehensive analysis of existing IoT-based health monitoring systems for cows, aiming to compare their features, performance, and potential contributions to the agricultural landscape. The review highlights the strengths and weaknesses of each system, providing a nuanced understanding of their practical implications in diverse farming environments. Furthermore, challenges faced by existing systems are discussed, and opportunities for improvement are identified. The paper concludes with insights into emerging technologies that may shape the future of IoT-based health monitoring for cows, emphasizing research gaps and proposing avenues for future investigation. This comparative analysis serves as a valuable resource for researchers, practitioners, and policymakers seeking to enhance the health and productivity of livestock through advanced IoT solutions.

Real-time Vital Signs Monitoring and Data Management Using a Low-Cost IoT-based Health Monitoring System

This study describes the creation and evaluation of a low-cost internet of things (IoT)-based health monitoring system for the continuous monitoring of vital signs such as temperature, pulse rate, oxygen saturation (SpO2) and blood pressure (BP) (both systolic and diastolic). Along with an organic light-emitting diode (OLED) display and an ESP8266 microcontroller, the system includes BP, non-contact temperature, SpO2 and electrocardiogram (ECG) sensors. Using the visual programming tool, Node-RED, the data from these sensors are gathered, processed and transmitted to the Google Cloud platform for archival and visualisation. The process involved mounting the sensors and microcontrollers on a special printed circuit board and designing the circuit with EasyEDA. The device measures systolic, diastolic and pulse rates from the BP sensor, as well as temperature, ECG and SpO2 values. The system works by using three push switches to read and display these values on demand. The gathered data are simultaneously shown on the OLED and sent to the Node-RED dashboard, where it is then sent to a Google Spreadsheet for archiving and analysis. This research article gives a thorough overview of the health monitoring system, the way it was implemented, and how it was successfully validated in a real-time setting. This study examines certain vital signs but additional health measures, such as respiration rate or glucose monitoring, could be included. Machine learning algorithms could also be used for predictive analytics. This would uncover data anomalies and trends early, improving healthcare management.

Design and Development of IoT based Health Monitoring System

Abstract: With prospects for developing technology, patient health monitoring is a significant and quickly expanding topic nowadays. Various designs for patient healthcare monitoring systems have been developed by numerous researchers in accordance with technological advancements. The devices in the suggested business plan, which include web-based sensors and mobile applications, communicate over a network to improve the efficiency of the system designed to record and monitor patient health information. In order to precisely analyze a patient's health status, a health system comprising sensors and monitoring devices has been built. These devices are able to collect medical data from patients and then send alarms via GSM module to specialized doctors. In order to gather health-related data, this project will connect patients via the Internet to an appropriate monitoring system that will improve medication care for both local patients and patients who live in remote areas without hospitals nearby. The devices will be able to record the patient's temperature, heart rate, and the oxygen levels in their blood.

Designing Integrated IT Architecture for Health Monitoring Internet of Things: Findings Exploratory Study

IT integration with healthcare, mainly through Internet of Things-based health monitoring systems, is crucial to improving healthcare management in the digital age. However, challenges remain in the design of an integrated IT architecture that can support the sustainability and effectiveness of IoT health monitoring systems, which still need to be addressed. The shortcomings in the literature related to the application of a holistic IT architecture framework to address these challenges indicate a knowledge gap that needs to be filled. Through the application of the TOGAF methodology, this research seeks to design and analyze an integrated IT architecture for IoT-based health monitoring systems in Indonesia, taking a qualitative approach through case studies, in-depth interviews, and document analysis. The main findings show that the application of the TOGAF framework successfully addresses the challenges of interoperability, data security, and system scalability by effectively integrating IoT technologies in the healthcare environment and considering the local social and infrastructural context. The implementation of the IT architecture developed based on the TOGAF methodology demonstrated improved coordination between IoT devices and backend systems, facilitated secure and real-time data flow, and accommodated the scalability and sustainability needs of the system. The findings have significant implications in supporting the development of more efficient and effective health monitoring systems, offering strategic guidance for system developers, policymakers, and IT practitioners within the healthcare sector.

Opportunities and Challenges in the Implementation of IoT Applications for Health Monitoring of Elderly People in the Indian Scenario

The Internet of Things (IoT)-based health monitoring has emerged as a transformative paradigm in healthcare, especially when it comes to tracking the health of senior citizens. The aging population in India is on the rise, necessitating the development of effective and scalable solutions to address the healthcare needs of the elderly. In this regard, IoT applications present promising prospects by facilitating early identification of medical problems, timely intervention, and continuous, real-time health monitoring. IoT applications can be customized to suit the varying needs of rural and urban population. However, the implementation of IoT applications in the healthcare sector in India comes with its own set of challenges. Issues related to infrastructure, data security, and the privacy concerns need to be carefully addressed to ensure the successful deployment and sustained effectiveness of these technologies. The majority of the Indian population resides in villages; therefore, cost effectiveness is also a major concern for rural population. This paper explores the opportunities and challenges associated with the implementation of IoT applications for health monitoring and aim to provide insights for policymakers, healthcare professionals, and technologists to design and implement IoT-based health monitoring systems tailored to the specific needs of the elderly population in India.

Wellness - IoT based Health Monitoring System Using Blynk Application

Wellness - IoT based Health Monitoring System Using Blynk Application

IoT Based Health Monitoring System

Abstract: The rapid advancements in the Internet of Things (IoT) have paved the way for revolutionary healthcare solutions. This paper proposes an IoT-based health monitoring system aimed at providing continuous and remote monitoring of patients' vital signs and physiological parameters. This real-time data collection and analysis empowers proactive healthcare, enhancing patient safety and quality of life.

IoT-Based Health Monitoring System: Design, Implementation, and Performance Evaluation

The Internet of Things (IoT) technology's rapid improvements have opened the door for creative solutions across a range of industries, including healthcare. An IoT-based health monitoring system that aims to revolutionise patient care and healthcare administration is described in this study along with its design, implementation, and performance evaluation. To continuously gather and send health-related data, our system makes use of a network of wearable sensors and gadgets that are seamlessly incorporated into a patient's daily life. Vital indicators like heart rate, blood pressure, temperature, and activity levels are tracked by these devices. To enable real-time analysis and storage, the data is safely sent to a centralised server. Both patients and healthcare professionals can access this information through a user-friendly smartphone application, enabling proactive healthcare decision-making. An effective and scalable architecture is used in the implementation of this system to guarantee the confidentiality, accuracy, and reliability of the data. The data is analysed using machine learning algorithms, which enables the early identification of abnormalities and trends that could portend serious health problems. The system can also produce warnings and notifications, ensuring prompt intervention when it's necessary. Our IoT-based health monitoring system's performance review indicates how well it performs in terms of enhancing healthcare outcomes. The solution gives healthcare professionals immediate access to crucial health information, allowing them to personalise treatment regimens, offer remote consultations, and make educated judgements. Continuous monitoring benefits patients by allowing for early intervention, fewer hospital stays, and an improvement in general health. Additionally, the system's scalability and versatility make it appropriate for a variety of healthcare settings, including small-scale home care and extensive hospital networks.

IoT-based health care system for emotional and heart rate monitoring

An IoT-based remote health monitoring system helps patient’s especially older adults and non-communicable disease (NCD) patients to get medical assistance or advice without being physically present in the hospital or medical centre. This system provides regular health monitoring from anywhere by having access to the Internet. One of the important elements is the physiological parameters which indicate the health status of the monitored patients. Literature study shows that most of the previous works monitor blood pressure, respiratory rate, temperature, ECG, blood oxygenation, diabetes, and hypertension. There have been little works paid attention to measuring the emotional level of the patient. Therefore, this paper explains the development of an IoT-based health monitoring system that measures the emotional level of the patient apart from other essential physiological parameters. The system consists of a microcontroller, two sensors, a wireless communication module, and an IoT cloud display, focusing on measuring the heart rate, body temperature, SpO2, and emotional level. For the heart rate and body temperature readings, the measurements acquired from the developed system show a close agreement with those of the established brand ROSSMAX with an error of less than 5%. For the emotional level test, there are 83.3% out of twelve subjects agree that the GSR value shows her feeling.

Retracted: IoT-Based Health Monitoring System Development and Analysis

Retracted: IoT-Based Health Monitoring System Development and Analysis

Development and Implementation of Transformer Breather Health Monitoring System Using IoT

Abstract: The reliable and efficient operation of power transformers is crucial for maintaining a stable electrical grid. One critical aspect of transformer maintenance is monitoring the health of the transformer breather, which plays a vital role in preventing the ingress of moisture and contaminants. This paper proposes an innovative approach for health monitoring of transformer breathers using the Internet of Things (IoT). By integrating IoT technologies with transformer breather systems, real-time monitoring and analysis of breather conditions can be achieved, enabling proactive maintenance and optimizing the lifespan of the transformer. The proposed IoT-based health monitoring system consists of interconnected breather units equipped with sensors to capture relevant data such as humidity levels, temperature, color of the silica gel, and gas concentrations. These sensors continuously gather data and transmit it to a central monitoring system via wireless communication protocols. The IoT-based health monitoring of transformer breathers offers several advantages over conventional methods. It enables continuous, real-time monitoring, eliminating the need for manual inspections and reducing the risk of unexpected failures.

IOT Based Health Monitoring System

Abstract: In India, close to regarding two hundredth of the whole population loses their lives because of interrupted health observance system i.e., in most of the hospitals, doctor visits patients either in morning shift or in evening shift or in each shift. What happens if patient's health becomes important in between that interval or once a doctor isn't on the market with a patient. the solution is a patient could lose her\his life. thus, to avoid this important situation; we tend to area unit proposing a sensible embedded system device that monitors patients’ health ceaselessly. This project introduces the structure and usage of an IoT based patient observing framework, utilizing different sensors and NodeMCU as the MCU (Master Control Unit). The framework can be utilized to constantly screen the wellbeing parameters of a patient. ECG Monitoring with AD8232 ECG Sensor and MAX30102 BPM sensor is used forsensing temperature and heartbeat rate can be measured from anyplace on the globe utilizing IoT (Internet of Things). IoT is executed, utilizing an ESP-8266, which enables the data to be transmitted flawlessly over the web and mobile app

IOT Based Remote Health Monitoring System for Discharged Patients

Abstract: In this automated world, biomedical field is not superior.But the rapid advancements in engineering have proven their importance in the biomedical field.Rapid development of technologies such as the Internet and Internet of Things has brought improvements in healthcare. IoT-based health monitoring system has been widely studied and developed in recent years, as they can improve the quality and accessibility of health care services, especially for patients with chronic diseases or in rural areas.The existing IoT-based health monitoring systems have some similarities and differences in terms of their hardware and software components,features, performance, etc. All the systems use sensors to measure the vital signs of patients but they use different types and models of sensors with different specifications and accuracy. This paper presents multiple improvements to the current approach by introducing a system that provides remote and continuous monitoring of patients' health status and enables early detection and intervention of potential health problems. This system utilizes Arduino nano and Wemos D1 Mini, two popular microcontrollers, collect data from various sensors attached to the patient's body and transmit it wirelessly to a central monitoring station. Moreover, the cost of this system is substantially reduced as compared to previous systems.

An IoT based health monitoring system for cancer treatment

An IoT based health monitoring system for cancer treatment

The IoT Based Health Monitoring with Alcohol Detection And Control System

Accidents caused due to drunken drive are increasing tremendously in this modern world. To prevent these kinds of accidents, we propose an IoT based health monitoring system with alcohol detection and control. The proposed project is designed to reduce accidents caused due to drunken driving. Globally the cases of accidents are increasing due to this aspect. In order to prevent these accident cases, in this project an IoT based method has been designed. In that Arduino, Alcohol Sensor, Heart beat rate sensor, Global System for Mobile communication, Wi-Fi modem, are utilized. Once the alcohol rate and heart beat rate are exceeding the specified limit, the command will be given to the ignition system of the vehicle to stop the operation of the vehicle.

A Linear Quadratic Regression-Based Synchronised Health Monitoring System (SHMS) for IoT Applications

In recent days, the IoT along with wireless sensor networks (WSNs), have been widely deployed for various healthcare applications. Nowadays, healthcare industries use electronic sensors to reduce human errors while analysing illness more accurately and effectively. This paper proposes an IoT-based health monitoring system to investigate body weight, temperature, blood pressure, respiration and heart rate, room temperature, humidity, and ambient light along with the synchronised clock model. The system is divided into two phases. In the first phase, the system compares the observed parameters. It generates advisory to parents or guardians through SMS or e-mails. This cost-effective and easy-to-deploy system provides timely intimation to the associated medical practitioner about the patient’s health and reduces the effort of the medical practitioner. The data collected using the proposed system were accurate. In the second phase, the proposed system was also synchronised using a linear quadratic regression clock synchronisation technique to maintain a high synchronisation between sensors and an alarm system. The observation made in this paper is that the synchronised technology improved the performance of the proposed health monitoring system by reducing the root mean square error to 0.379% and the R-square error by 0.71%.