Edge computing in multi-scope service-oriented mobile healthcare systems

This chapter introduces Mobile Healthcare Systems (MHS) and employs some theories to explore the behavioral intention of Smartphone users in Penang, Malaysia to use MHS. A survey was conducted in the form of questionnaire to Smartphone users in Penang, Malaysia for the duration of three weeks starting in September 2013. A total number of 123 valid surveys out of 150 were returned, which is equivalent to a response rate of 82%. The authors use Partial Least Squares (PLS) for analyzing the proposed measurement model. The factors that are tested are self-efficacy, anxiety, effort expectancy, performance expectancy, attitude, and behavioral intention to use. The results indicate which factors have a significant effect on Smartphone users' behavioral intention and which factors are not significant. The results assist in assessing whether MHS is highly demanded by users or not, and will assist in development of the system in the future.

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An Intelligent Edge Computing Based Semantic Gateway for Healthcare Systems Interoperability and Collaboration

2018 IEEE 6th International Conference on Future Internet of Things and Cloud (FiCloud) ◽

10.1109/ficloud.2018.00060 ◽

2018 ◽

Cited By ~ 3

Author(s):

Tshiamo Sigwele ◽

Yim Fun Hu ◽

Muhammad Ali ◽

Jiacheng Hou ◽

Misfa Susanto ◽

...

Keyword(s):

Healthcare Systems ◽

Edge Computing

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Protection of Service-Oriented Environments Serving Critical Infrastructures

Inventions ◽

10.3390/inventions3030062 ◽

2018 ◽

Vol 3 (3) ◽

pp. 62

Author(s):

Dimosthenis Kyriazis

Keyword(s):

Decision Making ◽

High Performance ◽

Performance Monitoring ◽

Critical Infrastructure ◽

Failure Detection ◽

False Positives ◽

Edge Computing ◽

Monitoring Data ◽

Critical Infrastructures ◽

Service Oriented

The emergence of service-oriented architectures has driven the shift towards a service-oriented paradigm, which has been adopted in several application domains. The advent of cloud computing facilities and recently of edge computing environments has increased the aforementioned paradigm shift towards service provisioning. In this context, various “traditional” critical infrastructure components have turned to services, being deployed and managed on top of cloud and edge computing infrastructures. However, the latter poses a specific challenge: the services of the critical infrastructures within and across application verticals/domains (e.g., transportation, health, industrial venues, etc.) need to be continuously available with near-zero downtime. In this context, this paper presents an approach for high-performance monitoring and failure detection of critical infrastructure services that are deployed in virtualized environments. The failure detection framework consists of distributed agents (i.e., monitoring services) to ensure timely collection of monitoring data, while it is enhanced with a voting algorithm to minimize the case of false positives. The goal of the proposed approach is to detect failures in datacenters that support critical infrastructures by targeting both the acquisition of monitoring data in a performant way and the minimization of false positives in terms of potential failure detection. The specific approach is the baseline towards decision making and triggering of actions in runtime to ensure service high availability, given that it provides the required data for decision making on time with high accuracy.

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Mobile Healthcare Systems: Generating Dynamic Smartphone Apps to Serve Multiple Medical Specializations - Assisting Monitoring Patient@Home and Health Record Follow-up

Proceedings of the International Conference on Health Informatics ◽

10.5220/0004237302150220 ◽

2013 ◽

Keyword(s):

Healthcare Systems ◽

Health Record ◽

Smartphone Apps ◽

Mobile Healthcare

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IoMT, Edge Computing, Blockchain, and Deep Learning for Next Generation Healthcare Systems (Preprint)

10.2196/preprints.29215 ◽

2021 ◽

Author(s):

Mohammad (Behdad) Jamshidi ◽

Tarek Frikha ◽

Asal Sabet ◽

Omar Cheikhrouhou ◽

Habib Hamam

Keyword(s):

Intelligent Systems ◽

Personal Information ◽

Healthcare Systems ◽

Cyber Attacks ◽

Edge Computing ◽

Medical Documentation ◽

Next Generation ◽

Healthcare Data ◽

Smart Healthcare ◽

Flexible Infrastructure

UNSTRUCTURED Processing medical data, diagnosing diseases, determining the best possible medical centers or physicians, and recommending the more effective remedies or drugs in the earliest time are the most important challenges to deploy intelligent systems for healthcare purposes. Hence, utilization of the Internet of Medical Things (IoMT) with Edge Computing (EC) technology will result in a strong network to aggregate the healthcare data more reliably and solve the aforementioned challenges. However, the administration of the millions of individuals with a wide variety of physical or mental disorders is another challenge associated with the use of such Artificial Intelligence-based platforms, especially when it comes to a large number of insurance conditions and companies. Furthermore, although the EC-based platforms can increase the security of the data, there are still vulnerable to face some cyber-attacks. Thus, the privacy of sensitive personal information of patients should be considered. Blockchain is a suitable option to overcome the problems associated with medical documentation and administration of patient’s affairs using smart contracts. An EC-based platform based on blockchain to improve the weaknesses of conventional smart healthcare systems is rendered in this research. The proposed platform takes the advantage of both EC and blockchain in the terms of speed, security, accuracy, and bandwidth. It should be noted that this method could be utilized as a flexible infrastructure for the next generation healthcare systems using any kind of crypto network like Bitcoin, Ethereum, Cardano, etc.

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