Examination of Healthcare Diagonosis using Iot

In recent years, online applications, spare many services for wellness of health related issues. The application is kept updated so that the health related data are kept modernized for future references. The application collects information from IoT devices and then compares them with other existing data from the prevailing records with the same disease. The collected data is then reserved in a database that hold all records about the healthcare issues. Cloud computing technology is used to guard and reserve the healthcare records. Cloud and IoT technology are connected to provide users with a completely developed healthcare record. The existing system makes use of Fuzzy Rule Based Neural Classifier that helps in assembling and categorizing the diabetes data under the guidance of severity analyzer. This work, present the comparison of some classification algorithms and obtain the accuracy, the dataset collected is a real-time dataset. The output and results are tabulated after the comparison of the algorithms.

Download Full-text

Fuzzy Rule based Enhanced Homomorphic Encryption in Cloud Computing

International Journal of Computer Applications ◽

10.5120/17706-8709 ◽

2014 ◽

Vol 101 (8) ◽

pp. 13-18

Author(s):

Randeep Kaur ◽

Supriya Kinger

Keyword(s):

Cloud Computing ◽

Homomorphic Encryption ◽

Fuzzy Rule ◽

Rule Based

Download Full-text

Cloud Based Wireless Infrastructure for Health Monitoring

Virtual and Mobile Healthcare ◽

10.4018/978-1-5225-9863-3.ch003 ◽

2020 ◽

pp. 34-55 ◽

Cited By ~ 1

Author(s):

Ajay Chaudhary ◽

Sateesh Kumar Peddoju ◽

Suresh Kumar Peddoju

Keyword(s):

Cloud Computing ◽

Health Monitoring ◽

Healthcare Services ◽

Power Source ◽

Vital Role ◽

Healthcare Applications ◽

Related Data ◽

Health Related ◽

Healthcare Monitoring ◽

Wireless Infrastructure

The wireless infrastructure based devices can collect data for long period of time even with a tiny power source as they perform specific function of collection of health related data and sending to gateways. The sensing data of healthcare monitoring consumes low power but they had limited computation power to process this data, where the cloud computing plays a vital role and compliment the loophole of wireless infrastructure based systems. In cloud computing with its immense computation power for easily deployment of healthcare monitoring algorithms and helps to process sensed data. As these two technologies did great jobs in their respective fields a conflate framework of these two technologies may lead to a great architecture for healthcare applications. This chapter reviews complete state-of-the-art and several use cases related to healthcare monitoring using different wireless infrastructure and adapting cloud based technologies in providing the healthcare services.

Download Full-text

A fuzzy rule-based fog–cloud computing for solar panel disturbance investigation

Cogent Engineering ◽

10.1080/23311916.2019.1624287 ◽

2019 ◽

Vol 6 (1) ◽

pp. 1624287 ◽

Cited By ~ 5

Author(s):

Suryono Suryono ◽

Ainie Khuriati ◽

Teddy Mantoro ◽

Murat Kunelbayev

Keyword(s):

Cloud Computing ◽

Fuzzy Rule ◽

Solar Panel ◽

Rule Based

Download Full-text

Security and Privacy in IoT-Cloud-Based e-Health Systems—A Comprehensive Review

Symmetry ◽

10.3390/sym12071191 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1191 ◽

Cited By ~ 3

Author(s):

Chanapha Butpheng ◽

Kuo-Hui Yeh ◽

Hu Xiong

Keyword(s):

Cloud Computing ◽

Health Information ◽

Health Systems ◽

Intelligent Systems ◽

Future Trend ◽

Security And Privacy ◽

The Internet ◽

Research Perspectives ◽

Health Related ◽

Iot Devices

When the Internet and other interconnected networks are used in a health system, it is referred to as “e-Health.” In this paper, we examined research studies from 2017–2020 to explore the utilization of intelligent techniques in health and its evolution over time, particularly the integration of Internet of Things (IoT) devices and cloud computing. E-Health is defined as “the ability to seek, find, understand and appraise health information derived from electronic sources and acquired knowledge to properly solve or treat health problems. As a repository for health information as well as e-Health analysis, the Internet has the potential to protect consumers from harm and empower them to participate fully in informed health-related decision-making. Most importantly, high levels of e-Health integration mitigate the risk of encountering unreliable information on the Internet. Various research perspectives related to security and privacy within IoT-cloud-based e-Health systems are examined, with an emphasis on the opportunities, benefits and challenges of the implementation such systems. The combination of IoT-based e-Health systems integrated with intelligent systems such as cloud computing that provide smart objectives and applications is a promising future trend.

Download Full-text

Enhanced Load Balancing Approach for Cloud Data Center Load Optimization

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2021.9399 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1270-1274

Author(s):

J. Prassanna ◽

V. Neelanarayanan

Keyword(s):

Cloud Computing ◽

Load Balancing ◽

Data Center ◽

Resource Control ◽

Resource Optimization ◽

Computing Technology ◽

Cloud Data Center ◽

Cloud Data ◽

Load Optimization ◽

Related Data

Cloud computing is a most popular technology that has huge response in markets. Cloud computing has the potential to access applications and their related data via the Internet anywhere. Most companies already pay for the use of cloud resources for storage purposes and ultimately reduce the costs of infrastructure spending. They can make use of this technology for accessing to company applications like pay-as-you-go approach. One of the major obstacles associated with cloud computing technology is to better optimization of resource allocation. Assigning of workloads to the servers using load balancing techniques is used to achieve less response time and better resource optimization across the server. Resource control and balance of load are the major conflicts in the cloud environment, which is why there are different load balancing algorithms, each with its own advantages and disadvantage. In order to achieve a better economy and mutual benefit, efficient algorithms can be derived simultaneously by optimizing servers, green computing and better utilization of resources. The objective of this paper is to analyze and enhance existing load balancing algorithms.

Download Full-text

Intelligent Optimization Mechanism Based on an Objective Function for Efficient Home Appliances Control in an Embedded Edge Platform

Electronics ◽

10.3390/electronics10121460 ◽

2021 ◽

Vol 10 (12) ◽

pp. 1460

Author(s):

Rongxu Xu ◽

Wenquan Jin ◽

Yonggeun Hong ◽

Do-Hyeun Kim

Keyword(s):

Machine Learning ◽

Cloud Computing ◽

Energy Consumption ◽

Objective Function ◽

Smart Home ◽

Edge Computing ◽

Rule Based ◽

Home Appliances ◽

Iot Devices ◽

Optimization Mechanism

In recent years the ever-expanding internet of things (IoT) is becoming more empowered to revolutionize our world with the advent of cutting-edge features and intelligence in an IoT ecosystem. Thanks to the development of the IoT, researchers have devoted themselves to technologies that convert a conventional home into an intelligent occupants-aware place to manage electric resources with autonomous devices to deal with excess energy consumption and providing a comfortable living environment. There are studies to supplement the innate shortcomings of the IoT and improve intelligence by using cloud computing and machine learning. However, the machine learning-based autonomous control devices lack flexibility, and cloud computing is challenging with latency and security. In this paper, we propose a rule-based optimization mechanism on an embedded edge platform to provide dynamic home appliance control and advanced intelligence in a smart home. To provide actional control ability, we design and developed a rule-based objective function in the EdgeX edge computing platform to control the temperature states of the smart home. Compared to cloud computing, edge computing can provide faster response and higher quality of services. The edge computing paradigm provides better analysis, processing, and storage abilities to the data generated from the IoT sensors to enhance the capability of IoT devices concerning computing, storage, and network resources. In order to satisfy the paradigm of distributed edge computing, all the services are implemented as microservices. The microservices are connected to each other through REST APIs based on the constrained IoT devices to provide all the functionalities that accomplish a trade-off between energy consumption and occupant-desired environment setting for the smart home appliances. We simulated our proposed system to control the temperature of a smart home; through experimental findings, we investigated the application against the delay time and overall memory consumption by the embedded edge system of EdgeX. The result of this research work suggests that the implemented services operated efficiently in the raspberry pi 3 hardware of IoT devices.

Download Full-text

A Fuzzy Rule-Based Fog Cloud Computing untuk Menganalisis Faktor Penyebab Kematian Ibu Meninggal Masa Postpartum

JATISI (Jurnal Teknik Informatika dan Sistem Informasi) ◽

10.35957/jatisi.v8i4.1262 ◽

2021 ◽

Vol 8 (4) ◽

pp. 1680-1692

Author(s):

Arif Wicaksono Septyanto

Keyword(s):

Blood Pressure ◽

Cloud Computing ◽

Fuzzy Rule ◽

Rule Based

Analisis penyebab kematian ibu pasca postpartum sangatlah penting dalam mengurang kematian ibu. Angka kematian ibu pasca postpartum diindonesia sangatlah tinggi sekitar 359 dalam 100.000 kelahiran. Faktor -faktor kematian ibu pasca postpartum jarang dianalisis lebih dalam sehingga tidak ada penanganan berkelanjuttan. Pada penelitian ini penulis menggunakan system fuzzy rule-based fog cloud computing untuk memonitoring kematian ibu berdasarkan tanda-tanda vital dan tanda-tanda fisik dengan menggunakan 10 parameter penyebab kematian ibu masa postpartum. Fog cloud digunakan untuk pengolahaan data dalam sever local agar mengurangi beban saat menggunakan cloud computing. Analisis awal parameter kematian ibu dirubah kedalam rentang low, medium dan high kemudian dimonitoring pada tujuh hari pasca postpartum dari hasil analisis yang dilakukan didapat faktor dominan kematian ibu pasca postpartum untuk tanda-tanda vital dipengaruhi oleh Blood Pressure dengan nilai MF 0,44 dengan status “High” untuk tanda-tanda fisik dipengaruhi oleh Anogenital Lochea Sanguinolenta dengan nilai MF 0,46 dengan status dalam system “High”. Parameter lain tidak terlalu berpengaruh terhadap kematian ibu cenderung turun dari hari pertama hingga hari ke tujuh pasca postpartum.

Download Full-text

E -Patient Deidentified Record Integration using Cloud Computing

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b3294.079220 ◽

2020 ◽

Vol 9 (2) ◽

pp. 157-160

Keyword(s):

Public Health ◽

Cloud Computing ◽

Data Storage ◽

Modern Architecture ◽

Public Health Care ◽

Health Record ◽

Related Data ◽

Patient Health ◽

Health Related ◽

Care Problems

With the development of science and technology, the design of modern architecture is becoming more and more attractive. Now a days the medical fields become more wide development in machinery the same way the data storage also developed higher . The main reason for proposing the paper is to store the patient data into the cloud. The patient can access the data from anywhere at any time. . The delivering of public health solutions can lead to increased efficiency in health related data. Many nations across the globe have launched aggressive stimulus programs aimed at solving public health care problems in efficient way .This paper proposed for maintain the patient health record in cloud computing.

Download Full-text

Similarity Measure of Breast Cancer Datasets Using Fuzzy Rule-Based Classification by Attribute

International Journal of Extreme Automation and Connectivity in Healthcare ◽

10.4018/ijeach.2019010103 ◽

2019 ◽

Vol 1 (1) ◽

pp. 12-28

Author(s):

Tengyue Li ◽

Simon Fong

Keyword(s):

Breast Cancer ◽

Information Gain ◽

Fuzzy Rule ◽

Ensemble Methods ◽

Classification Algorithms ◽

Rule Generation ◽

Rule Based ◽

Reasoning System ◽

Evaluation Approach ◽

Test Instance

To compare with two datasets based on attributes by using classification algorithms, for the attributes, the authors need to select them by rules and the system is known as rule-based reasoning system which classifies a given test instance into a particular outcome from the learned rules. The test instance carries multiple attributes, which are usually the values of diagnostic tests. In this article, the authors propose a classifier ensemble-based method for comparison of two breast cancer datasets. The ensemble data mining learning methods are applied to rule generation, and a multi-criterion evaluation approach is used for selecting reliable rules over the results of the ensemble methods. The efficacy of the proposed methodology is illustrated via an example of two breast cancer datasets. This article introduces a novel fuzzy rule-based classification method called FURIA, to obtain a relationship between two breast cancer datasets. Hence, it can find the similarity between these two datasets. The new method is compared vis-à-vis with other classical statistical approaches such as correlation and mutual information gain.

Download Full-text