scholarly journals EdgeCare: Leveraging Edge Computing for Collaborative Data Management in Mobile Healthcare Systems

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 22011-22025 ◽  
Author(s):  
Xiaohuan Li ◽  
Xumin Huang ◽  
Chunhai Li ◽  
Rong Yu ◽  
Lei Shu
2021 ◽  
Author(s):  
Michael Enbibel

This research is done for optimizing telemedicine framework by using fogging or fog computing for smart healthcare systems. Fog computing is used to solve the issues that arise on telemedicine framework of smart healthcare system like Infrastructural, Implementation, Acceptance, Data Management, Security, Bottleneck system organization, and Network latency Issues. we mainly used Distributed Data Flow (DDF) method using fog computing in order to fully solve the listed issues.


Author(s):  
Pantea Keikhosrokiani ◽  
Norlia Mustaffa ◽  
Nasriah Zakaria ◽  
Ahmad Suhaimi Baharudin

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.


2016 ◽  
Vol 2016 (0) ◽  
pp. S1440103
Author(s):  
Hikaru ISHIGURI ◽  
Chinghui WU ◽  
Kouhei OGAWA ◽  
Nagomu MORITA ◽  
Yasuyuki NISHIOKA

2021 ◽  
Author(s):  
Mohammad (Behdad) Jamshidi ◽  
Tarek Frikha ◽  
Asal Sabet ◽  
Omar Cheikhrouhou ◽  
Habib Hamam

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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