Secure Smart Wearable Computing through Artificial Intelligence-Enabled Internet of Things and Cyber-Physical Systems for Health Monitoring (original) (raw)
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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..
AI-Enabled Wearable Medical Internet of Things in Healthcare System: A Survey
Applied Sciences
Technology has played a vital part in improving quality of life, especially in healthcare. Artificial intelligence (AI) and the Internet of Things (IoT) are extensively employed to link accessible medical resources and deliver dependable and effective intelligent healthcare. Body wearable devices have garnered attention as powerful devices for healthcare applications, leading to various commercially available devices for multiple purposes, including individual healthcare, activity alerts, and fitness. The paper aims to cover all the advancements made in the wearable Medical Internet of Things (IoMT) for healthcare systems, which have been scrutinized from the perceptions of their efficacy in detecting, preventing, and monitoring diseases in healthcare. The latest healthcare issues are also included, such as COVID-19 and monkeypox. This paper thoroughly discusses all the directions proposed by the researchers to improve healthcare through wearable devices and artificial intelligence....
Towards a Smart Healthcare System
International Journal of Healthcare Information Systems and Informatics
With the rapid development in smart medical devices, Internet of things has a large applicability in healthcare sector. The current system is based on a centralized communication with cloud servers. However, this architecture increases security and privacy risks. This paper describes an architecture of a smart healthcare system for remote patient monitoring. To ensure security and privacy, the architecture uses the Blockchain technology. For data analysis, smart contracts and artificial intelligence are used. The architecture is divided into three layers: smart medical devices layer, fog layer and cloud layer. To validate the proposed approach, a scenario based on diabetes management system is described. The architecture is applied to provide remote diabetic patients monitoring. The system could suggest treatments, generate proactive predictions and predict future complications as well as alerting physicians in case of emergency.
System Discovery * IOT Health Monitoring System
In this advanced universe of increasing population, IoT assumes an essential part. Security is the biggest concern in adopting Internet of things technology. It discovered its application in computerized transportation, smart home, smart cities, farming, and medical care. In hospital, IOT is an important aspect in monitoring the patients. Patients' protection and quality of life must be ensured and improved as IoT-based health care systems are developed. These technologies are mostly intended for the elderly. Wearable devices are used to build a body sensor network for people living in rural areas. The information about the patients is recorded via this network. This paper describes real-time patient monitoring in the absence of doctors, without the need for manual data collection as well as, we provide a new classification of cyber-attacks that may affect the healthy functioning of such infrastructures. •
A Secure IoT-Cloud Based Healthcare System for Disease Classification Using Neural Network
Computer Systems Science and Engineering
The integration of the Internet of Things (IoT) and cloud computing is the most popular growing technology in the IT world. IoT integrated cloud computing technology can be used in smart cities, health care, smart homes, environmental monitoring, etc. In recent days, IoT integrated cloud can be used in the health care system for remote patient care, emergency care, disease prediction, pharmacy management, etc. but, still, security of patient data and disease prediction accuracy is a major concern. Numerous machine learning approaches were used for effective early disease prediction. However, machine learning takes more time and less performance while classification. In this research work, the Attribute based Searchable Honey Encryption with Functional Neural Network (ABSHE-FNN) framework is proposed to analyze the disease and provide stronger security in IoT-cloud healthcare data. In this work, the Cardiovascular Disease and Pima Indians diabetes dataset are used for heart and diabetic disease classification. Initially, means-mode normalization removes the noise and normalizes the IoT data, which helps to enhance the quality of data. Rectified Linear Unit (RLU) was applied to adjust the feature weight to reduce the training cost and error classification. This proposed ABSHE-FNN technique provides better security and achieves 92.79% disease classification accuracy compared to existing techniques.
A Decade of Internet of Things: Analysis in the Light of Healthcare Applications
IEEE Access
Impressive growth in the number of wearable health monitoring devices has affected global health industry as they provide rapid and intricate details related to physical examinations, such as discomfort, heart rate, blood glucose level, etc., which enable doctors to efficiently diagnose sensitive heart troubles. Internet of Medical Things (IoMT) is a phenomenon wherein computer networks and medical equipment are connected through the Internet to provide real-time interaction between physicians and patients. In this article, we present a comprehensive view of IoMT and its related Machine Learning (ML)based developed frameworks designed, or being utilized, in the last decade, i.e., 2010 through 2019. The presented techniques are designed for monitoring limbs, controlling rural healthcare, identifying e-health applications, monitoring health through mobile apps, classifying heart sounds, detecting stress in drivers, monitoring cardiac diseases, making decision to predict heart attacks, recognizing human activities, and classifying breast cancer. The aim is to provide a clear picture of the existing IoMT environment so that the analysis may pave the way for the diagnosis of critical disorders such as cancer, heart attack, and blood pressure among others. In the end, we also provide some unresolved challenges that are confronted in the deployment of secure IoMT-based healthcare systems.
SMART HEALTHCARE SYSTEM USING IOT
MANTECH PUBLICATION, 2020
In the most recent decade the social insurance checking frameworks have drawn significant considerations of the scientists. The prime objective was to build up a solid patient checking framework with the goal that the medicinal services experts can screen their patients, who are either hospitalized or executing their typical day by day life exercises. In this work we present a cell phone based remote medicinal services checking framework that can give ongoing on the web data about physiological states of a patient. Our proposed framework is intended to quantify and screen critical physiological information of a patient so as to precisely portray the status of her/his wellbeing and wellness. By utilizing the data contained in the content or email message the human services proficient can give essential medicinal exhorting. The framework chiefly comprises of sensors (for example temperature sensor, gyrator, accelerometer), area storage (for example GPS), microcontroller (for example Raspberry Pi), and programming (for example Raspbian, Disk imager). The patient's temperature, no. of steps he/she strolls, area and ECG information are checked, shown, and put away by our framework. Alongside above notice parameters, android application will show timing and sum for drinking water and caution about same.
Smart Medication for secure health with Internet of Things
Advances in Multidisciplinary and scientific Research Journal Publication, 2021
For over a decade, network and technology has been improved to an equal extent which has led to an easy transmission of data over the entire globe. Besides growth and development of Internet of Things in our daily life such as health care and home automation, secured transmission is significant regarding how confidential and secured the information is, to assure the privacy. The data related to the health are acquired from medical devices and monitoring systems. Some information are acquired from the patient. In this project we will be more particular in gathering the information from the patient. They ultimately end up in Electronic Healthcare Records. These records are sent to labs, doctors, nurses and other parties involved. This enables doctors, caregivers to monitor patient's physiological conditions at any time according to the information obtained. Hence, it is based on this that this research work is carried out to determine the level at which the internet has been able ...
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A significant study has been undertaken in the areas of health care and administration of cutting-edge artificial intelligence (AI) technologies throughout the previous decade. Healthcare professionals studied smart gadgets and other medical technologies, along with the AI-based Internet of Things (IoT) (AIoT). Connecting the two regions makes sense in terms of improving care for rural and isolated resident individuals. The healthcare industry has made tremendous strides in efficiency, affordability, and usefulness as a result of new research options and major cost reductions. This includes instructions (AIoT-based) medical advancements can be both beneficial and detrimental. While the IoT concept undoubtedly offers a number of benefits, it also poses fundamental security and privacy concerns regarding medical data. However, resource-constrained AIoT devices are vulnerable to a number of assaults, which can significantly impair their performance. Cryptographic algorithms used in the...