Cloud-assisted IoT-based health status monitoring framework

Ghanavati, Sara; Abawajy, Jemal; Izadi, Davood; Alelaiwi, Abdulhameed

doi:10.1007/s10586-017-0847-y

Cited by 50 publications

(26 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, an IoT-based heart failure prediction and analysis model through machine learning methods was proposed in [26], and also, recently, in [27], a deep learning framework for prediction of heart disease was proposed for IoT context. & Cloud-based IoT platforms: a variety of studies benefit the advantages of both technologies of cloud and IoT such as [9] that proposed a service-oriented IoT-based framework for unceasing patient condition tracking that used WBAN over smartphones to transfer medical data to the clouds. Experimental assessment regarding the lifetime of sensors, cost, and energy feeding revealed that the suggested framework considerably improves the standard WBANs.…”

Section: Remote Health Monitoring Framework and Architectures In Iotmentioning

confidence: 99%

A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment

Akhbarifar

Javadi

Rahmani

et al. 2020

Pers Ubiquit Comput

View full text Add to dashboard Cite

Internet of Things (IoT) and smart medical devices have improved the healthcare systems by enabling remote monitoring and screening of the patients’ health conditions anywhere and anytime. Due to an unexpected and huge increasing in number of patients during coronavirus (novel COVID-19) pandemic, it is considerably indispensable to monitor patients’ health condition continuously before any serious disorder or infection occur. According to transferring the huge volume of produced sensitive health data of patients who do not want their private medical information to be revealed, dealing with security issues of IoT data as a major concern and a challenging problem has remained yet. Encountering this challenge, in this paper, a remote health monitoring model that applies a lightweight block encryption method for provisioning security for health and medical data in cloud-based IoT environment is presented. In this model, the patients’ health statuses are determined via predicting critical situations through data mining methods for analyzing their biological data sensed by smart medical IoT devices in which a lightweight secure block encryption technique is used to ensure the patients’ sensitive data become protected. Lightweight block encryption methods have a crucial effective influence on this sort of systems due to the restricted resources in IoT platforms. Experimental outcomes show that K-star classification method achieves the best results among RF, MLP, SVM, and J48 classifiers, with accuracy of 95%, precision of 94.5%, recall of 93.5%, and f-score of 93.99%. Therefore, regarding the attained outcomes, the suggested model is successful in achieving an effective remote health monitoring model assisted by secure IoT data in cloud-based IoT platforms.

show abstract

Section: Remote Health Monitoring Framework and Architectures In Iotmentioning

confidence: 99%

A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment

Akhbarifar

Javadi

Rahmani

et al. 2020

Pers Ubiquit Comput

View full text Add to dashboard Cite

show abstract

“…Thus, there is a wide interest for developing efficient and effective approaches to help monitor and look after patients in their home, that is, outside the health facilities. It has been demonstrated that the steady observing of patient's well-being can lead to 50% reduction in hospitalizations, 73% drop in emergency department visits, and 51% decline in patient cost (Ghanavati et al, 2017).…”

Section: Healthcare In Cloudiotmentioning

confidence: 99%

“…Despite that, the proper resource management of large chunks of collected data remains a critical issue in developing remote real-time healthcare systems. In fact, there are several constraints related to the IoT core devices such as limited memory, power supply, and processing capabilities that negatively influence the performance of the networks (Ghanavati et al, 2017). This is particularly true in a CloudIoT environment, in which features like latency, scalability, and data offloading must also be taken into consideration.…”

Section: Healthcare In Cloudiotmentioning

confidence: 99%

Toward an efficient healthcare CloudIoT architecture by using a game theory approach

Macedo

Araújo

Dutra

et al. 2019

Concurrent Engineering

View full text Add to dashboard Cite

The increasing adoption of the Internet of things and cloud computing in recent years provided the increasing development and improvement of various well-known approaches, such as the ambient assisted living approach. The merging of Internet of things and cloud brought about the so-called CloudIoT paradigm. CloudIoT intends to extend both technologies to make possible developing the next generation of smart environments, such as healthcare applications. New healthcare applications demand an increasing capacity of resources for storing, processing, and transmitting data. Looking at this scenario, along with the growing number of devices connected to the Internet of things, we must consider providing mechanisms to mitigate the excessive data offloading on the network, the latency between nodes, and even the unnecessary waste of computing power. In this article, we present an efficient and effective CloudIoT-based healthcare architecture for ambient assisted living environments. The innovation of our approach lies on the use of a game theory approach (by means of a stochastic search algorithm) to improve efficiency and latency of the CloudIoT network. This proposal aims to provide better availability levels to the whole environment. Experiments performed through simulation have shown us a remarkable improvement of network parameters, by applying a stochastic search algorithm called Gur game, when compared to a baseline application.

show abstract

“…The increasing number of the elderly population and people suffering from chronic diseases motivated Ghanavati et al [11] to advocate for the indispensability of the IoT in the healthcare context. To realise the remote monitoring of patients' health status in real time, the authors suggested an independent location framework that is based on the IoT, interconnected sensors and wireless body area network (WBAN).…”

Section: Literature Reviewmentioning

confidence: 99%

Smart Health and Safety Equipment Monitoring System for Distributed Workplaces

2019

View full text Add to dashboard Cite

This paper presents a design and prototype of an IoT-based health and safety monitoring system using MATLAB GUI. This system, which is called the Smart Health and Safety Monitoring System, is aimed at reducing the time, cost and manpower requirements of distributed workplaces. The proposed system is a real-time control and monitoring system that can access on-line the status of consumable devices in the workplace via the internet and prioritise the critically high location that need replenishing. The system dynamically updates the status of all location, such as first aid boxes, earplug dispensers and fire extinguishers. Simulation results of the proposed system gives shorter path, time and cost in comparison to manual maintenance systems.

show abstract

Cloud-assisted IoT-based health status monitoring framework

Cited by 50 publications

References 25 publications

A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment

A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment

Toward an efficient healthcare CloudIoT architecture by using a game theory approach

Smart Health and Safety Equipment Monitoring System for Distributed Workplaces

Contact Info

Product

Resources

About