Enabling Health Monitoring as a Service in the Cloud

Yang, Li; Guo, Li; Guo, Yike

doi:10.1109/ucc.2014.21

Cited by 24 publications

(20 citation statements)

References 25 publications

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“…4, this system consists of three main layers: IoT eHealth Device Layer, IoT eHealth Fog Layer and IoT eHealth Cloud Layer. Note that IoT architecture for eHealth applications is already discussed in [40], [41], [42], [43], [44], [45], [46], [47], [48]. However, the following provides a complete solution from data acquisition and processing, to cloud platform and big data analytics.…”

Section: Iot Ehealth Ecosystemmentioning

confidence: 99%

Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare

Farahani

Firouzi

Chang

et al. 2018

Future Generation Computer Systems

795

371

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Internet of Things (IoT) offers a seamless platform to connect people and objects to one another for enriching and making our lives easier. This vision carries us from compute-based centralized schemes to a more distributed environment offering a vast amount of applications such as smart wearables, smart home, smart mobility, and smart cities. In this paper we discuss applicability of IoT in healthcare and medicine by presenting a holistic architecture of IoT eHealth ecosystem. Healthcare is becoming increasingly difficult to manage due to insufficient and less effective healthcare services to meet the increasing demands of rising aging population with chronic diseases. We propose that this requires a transition from the clinic-centric treatment to patient-centric healthcare where each agent such as hospital, patient, and services are seamlessly connected to each other. This patient-centric IoT eHealth ecosystem needs a multi-layer architecture: 1) device, 2) fog computing and 3) cloud to empower handling of complex data in terms of its variety, speed, and latency. This fog-driven IoT architecture is followed by various case examples of services and applications that are implemented on those layers. Those examples range from mobile health, assisted living, e-medicine, implants, early warning systems, to population monitoring in smart cities. We then finally address the challenges of IoT eHealth such as data management, scalability, regulations, interoperability, device-network-human interfaces, security, and privacy.

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Section: Iot Ehealth Ecosystemmentioning

confidence: 99%

Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare

Farahani

Firouzi

Chang

et al. 2018

Future Generation Computer Systems

795

371

View full text Add to dashboard Cite

show abstract

“…In terms of the rest of the actors involved in value co-creation within the ecosystems, results are shown in Figure 8. We distinguish between: health care related actors, 32 papers (86%) (e.g., [6,7]); patients and/or relatives, 22 papers (60%) (e.g., [8,10]); funders, 12 papers (32%) (e.g., [54,58]); regulatory parties, 10 papers (27%) (e.g., [58,60]); software or technology providers, 22 papers (60%) (e.g., [62,63]); goods providers, nine papers (24%) (e.g., [43,64]); and educational or research institutions, four papers (11%) (e.g., [61,67]).…”

Section: Resultsmentioning

confidence: 99%

Technological Ecosystems in Care and Assistance: A Systematic Literature Review

Marcos-Pablos

García-Peñalvo

2019

Sensors

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Applying the concepts of technological ecosystems to the care and assistance domain is an emerging field that has gained interest during the last years, as they allow to describe the complex relationships between actors in a technologically boosted care domain. In that context, this paper presents a systematic review and mapping of the literature to identify, analyse and classify the published research carried out to provide care and assistance services under a technological ecosystems’ perspective. Thirty-seven papers were identified in the literature as relevant and analysed in detail (between 2003–2018). The main findings show that it is indeed an emerging field, as few of the found ecosystem proposals have been developed in the real world nor have they been tested with real users. In addition, a lot of research to date reports the proposal of platform-centric architectures developed over existing platforms not specifically developed for care and services provision. Employed sensor technologies for providing services have very diverse natures depending on the intended services to be provided. However, many of these technologies do not take into account medical standards. The degree of the ecosystems’ openness to adding new devices greatly depends on the approach followed, such as the type of middleware considered. Thus, there is still much work to be done in order to equate other more established ecosystems such as business or software ecosystems.

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“…The authors in [22] regard the main aspect of IoT as connecting heterogeneous entities and assembling large amounts of data, thus said, in context to the e-health environment, IoT is regarded as the process of connecting data about the patient to facilitate treatment effectively and efficiently, as well as to receive more comprehensive knowledge. The authors illuminate that inevitably healthcare personnel will have mutual knowledge and accessibility to/for a patient's data.…”

Section: Related Workmentioning

confidence: 99%

An innovative IoT service for medical diagnosis

Abbas

2020

IJECE

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Due to the misdiagnose of diseases that increased recently in a scarily manner, many researchers devoted their efforts and deployed technologies to improve the medical diagnosis process and reducing the resulted risk. Accordingly, this paper proposed architecture of a cyber-medicine service for medical diagnosis, based internet of things (IoT) and cloud infrastructure (IaaS). This service offers a shared environment for medical data, and extracted knowledge and findings between patients and doctors in an interactive, secured, elastic and reliable way. It predicts the medical diagnosis and provides an appropriate treatment for the given symptoms and medical conditions based on multiple classifiers to assure high accuracy. Moreover, it entails different functionalities such as on-demand searching for scientific papers and diseases description for unrecognized combination of symptoms using web crawler to enrich the results. Where such searching results from crawler, are processed, analyzed and added to the resident knowledge base (KB) to achieve adaptability and subsidize the service predictive ability.

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Enabling Health Monitoring as a Service in the Cloud

Cited by 24 publications

References 25 publications

Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare

Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare

Technological Ecosystems in Care and Assistance: A Systematic Literature Review

An innovative IoT service for medical diagnosis

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