IOT based Health Monitoring Bot (original) (raw)

Health Care Patient Monitoring using IoT and Machine Learning

IOSR Journal of Engineering (IOSR JEN), 2019

Security and privacy is the most essential thing in Big Data environment, there are many algorithms have been proposed in existing approaches for data privacy as well as security. In many applications like Healthcare are banking applications having available data where third party attacker can easily access the privacy of victims. In Internet of Things (IoT) environment there is the major issue of data security. In this paper we proposed high dimensional Healthcare big data security as well as disease prediction using machine learning approach. Basically the system has categorized into two sections first we implement IoT based environment which generates the data of patient body. This section be used some wearable devices like ECG sensor, BP sensor temperature sensor heart rate sensor etc. Once data has generated from various sensors it will upload on cloud database. In the second phase we monitor the data which is generated by various sensors. Here we have generated Android base graphical user interface with monitors the data 24 by 7. Where machine learning algorithms are has used to predict the disease of patients. The authentication mechanism will achieve role based access control for specific users and proposed machine learning algorithms provides the patient disease probability according to given parameters. The experiment analysis has done based on the partial implementation of system which provide proposed system is more effective than some existing IoT systems..

Patient health monitoring using IoT with machine learning

2019

Health aspects of human being need to be monitored with utmost care and must be treated with appropriate drugs. Several diseases can be reduced by proactive monitoring of one's health. In the recent decades, technological development is at its peak due to which several wearable devices and health monitoring gadgets are available at the market. Even expert doctors find it challenging to estimate the health issues from the symptoms observed from the diseased. Using modern technological tools such as Internet of Things (IoT), machine learning and Artificial Intelligence along with Big data makes the job of physicians much easier in digging out the root cause of disease and predicting its seriousness using modern algorithms. In this research work, the machine learning algorithms are used to monitor the health conditions of the humans. Initial training and validation of machine learning algorithms are performed using the UCI dataset. Testing phase is carried out by collecting heart rate, blood pressure and temperature of the person using IoT setup. Testing phase estimates the prediction of any abnormalities in the health condition from the sensor data collected through the IoT framework. Statistical analysis is performed from data accumulated into the cloud from IoT device to estimate the accuracy in prediction percentage. Also, from the results obtained from the K-Nearest Neighbor outperforms other conventional classifiers.

IOT based Patient Health Monitoring System using ML

International Journal of Engineering and Advanced Technology, 2019

The project focuses on the usage of sensing and analysis with the help of relevant sensor technologies in order to record the health conditions of people. The best way to understand this is with an example. A practising doctor who is not equipped with such technology can check the patients’ health only when the patient pays a visit to the clinic. Now, with the application of the proposed technological measures, the doctor would have a complete record of the patient whether at home, office or on the road, and this would enable him to prescribe medication in a much more efficient and effective manner. Also, it is important to appreciate that on the basis of patient data recorded in the past, a prediction model could help the doctor see irregularities and predict if a patient suffers from commonly occurring ailments hence saving time in an initial diagnosis. This method for Healthcare Data Analytics using Support Vector Machine (SVM) Algorithm helps improve accuracy when it comes to ch...

REAL TIME HEALTH MONITORING USING IOT WITH INTEGRATION OF MACHINE LEARNING APPROACH

IAEME PUBLICATION, 2020

Healthiness is the base for every human being. It is directly or indirectly influencing the mental ability of the person. It gives them the confidence to each action of the human. Sound health is necessary to do all our day to day works with the fullest hope. Nowadays all people are having more health- conscious than in the past years. Because of these reasons, there are different types of health check- ups, monitoring clinics are evolved, and they do a lot of monitoring processes like daily, monthly, and master check-ups. To provide multiple services, options, and facilities to their clients the technologies play a vital role in the current era. The rapid development of information technology influences every person's life and health consciousness. These technologies are helping to monitor the status of a person and provide necessary tips then and there. Different methods of check-ups and monitoring process are available to get the information about a person. There are several IoT enabled sensors available to sense the patient complete details about a particular person's behavior, human anatomy, and physiology. This will lead the Big data. The Data gained over the sensors are uploaded to the internet, and connected to the cloud server. The affected person records could be saved in the web server and physicians can get right of entry to the data anywhere in the world. Anyun expected variation in the data of the patient who is using the healthcare system, inevitably the data of the patient will be uploaded to the concerned doctor with immediate notification. This type of health care system will be most useful in rural and remote areas. In this chapter, discussthe Machine learning techniqueswhich are important to the build analysis models. Then howthis model isintegrated with IoT Technology and provide accurate data of individual person and also discuss the Cardiovascular problems based on real-time input data

E-Healthcare Monitoring System using IoT with Machine Learning Approaches

Internet of Things (IoT) is an emerging technology that is drastically improving with many new enhancements in medical and health domains. IoT Health wearable devices are taking new challenges by upgrading with innovative technology and resources. Using health wearable devices, in/out patient's health status can be monitored periodically and regularly. This paper introduces an IoT application framework E-Healthcare Monitoring System (EHMS) integrated with Machine learning (ML) techniques to design an advanced automation system. Using this system it will connect, monitor and decisions making for proper diagnosis.

Advanced Patient Monitoring System with Diseases Prediction System using Machine Learning

Middle East Journal of Applied Science & Technology, 2022

IoT and machine learning (ML) are becoming increasingly efficient in the medical and telemedicine areas all around the world. This article describes a system that employs latest technology to give a more accurate method of forecasting disease. This technology uses sensors to collect data from the body of the patient. The obtained sensor information is collected with NodeMcU before being transferred to the Cloud Platform "ThinkSpeak" through an ESP8266 Wi-Fi module. ThinkSpeak is a cloud server that provides real-time data streams in the cloud. For the best results, data currently saved in the cloud is evaluated by one of the machine learning algorithms, the KNN algorithm. Based on the findings of the analysis and compared with the data sets, the disease is predicted and a prescription for the relevant disease is issued.

Smart Healthcare System Using IoT, Cloud, and AI/ML

Journal of Engineering Science and Technology Review, 2023

This survey presents various insights on the IoT system and its architecture used to implement a smart health-care system, along with the implementation of the latest technologies such as Cloud Computing for storing data, Machine Learning for predicting various diseases. These technologies are also used to improve the existing management and administration system in hospitals. Various solutions for tackling the health-care crisis have been proposed most of them sound promising but a practical low-cost implementation and feasibility of IoT and ML integrated system is yet to be designed. The present chapter also deals with the standard protocols designed for body area networks for health monitoring applications. The IEEE 802.15.6 standard is used for the body area network which provides high data rate and low-range communication. The integration of the standard body area network protocols with 5G technology can be used for high throughput real-time reliable operations.

Intelligent Healthcare Monitoring in IoT

— The developing of IoT-based health care systems must ensure and increase the safety of the patients, their quality of life and other health care activities. We may not be aware of the health condition of the patient during the sleeping hours. To overcome this problem. This paper proposes an intelligent healthcare monitoring system which monitors and maintains the patient health condition at regular intervals. The heart rate sensor and temperature sensor would help us analyze the patients' current health condition. In case of major fluctuations in consecutive intervals a buzzer is run in order to notify the hospital staff and doctors. The monitored details are stored in the cloud "ThingSpeak". The doctor can view the patient health condition using Virtuino simulator. This system would help in reducing the random risks of tracing a patient medical highly. Arduino UNO is used to implement this intelligent healthcare monitoring system. Keywords— Arduino UNO, Heart Rate Sensor, Temperature Sensor, Buzzer, ThinkSpeak, Virtuino simulator.

Health Monitoring System of Patient Using IoT

International Journal of Scientific Research in Science, Engineering and Technology, 2020

Now a day’s IoT brings gadgets together and assumes a fundamental part in different methodologies like smart home automation, brilliant industries, smart environment, agricultural fields and patient health monitoring system and so on. One of the approaches is to monitor the health state of the patient and screen it to doctors or paramedical staff through the IoT, as it is hard to screen the patient for 24 hours. So here the patient health condition or status i.e. Pulse rate, Body Temperature, ECG and so on can be measured by utilizing the protruding sensors. These sensors are associated with the node mcu and mcp 3008, it gathers the information i.e. biomedical data from the sensors and the detected biomedical information can be transmitted to the server. The "Thingspeak" named cloud is utilized here to place the detected information into the server. From this server, the information can be envisioned to the specialists and other paramedical staff either by Thingspeak website or Thingview android application. This system also notifies if there is any change in patient parameters. In this way, this Health monitoring system diminishes the toil of specialists and paramedical staff to screen the patient for 24 hours and further reduces time and cost for support.

Patient Monitoring and Disease Analysis Based on IoT Wearable Sensors and Cloud Computing

2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), 2022

The number of patients to be treated in healthcare facilities is increasing over time due to the growing awareness and importance of formal healthcare. Most healthcare centers lacked modern automation systems, such as continuous patient monitoring, which of schedule the doctor or nurse's visits with the patient. This research is designed to implement a new method of patient monitoring system in a treatment room, using wearable sensors enabled by the Internet of Things (IoT) technology and patient data analysis in cloud computing. The proposed system consists of several sensors to retrieve patient information, such as body temperature, heart rate, blood pressure, electrocardiogram (ECG), and motion sensor. Those parameters are used to analyze patient disease and healthcare during treatment with real-time monitoring to ensure medical professionals obtain the latest update on patient health. The system is designed in an embedded module that is applicable for mobile phones and connected through a Wireless Fidelity (Wi-Fi) system in healthcare facilities. All the patient data retrieved by IoT sensors is delivered to cloud computing to store the data and then analyzed using Long Short-Term Memory (LSTM) Algorithm to examine data related to the patient health and illness. Results show the performance of the IoT sensing system working well and are able to detect and send the data in real-time to healthcare centers globally through a mobile device. Based on real case scenario testing performance, the system accuracy ability to send data is more than 95% while any abnormality is readily detected. Overall, the system has enormous potential for further development and widespread use in the healthcare industry for efficient operations.