Understanding Ioht and Edge/Fog Computing Solutions for Smart In-Home Remote Healthcare

13 Pages Posted: 5 Mar 2022


Healthcare information systems have been dominated by cloud technology and the Internet of Things (IoT) for decades today. In some urgent scenarios, for the latency and energy efficiency prerequisites to be satisfied for a instant gathering and analysis of care data, fog and edge computing architectures are solutions, integrated with 5G mobile networks and AI. To settle these challenges, we reveal a prevailing architectural framework that is based on fog/edge optimal computing approaches smart In-home Remote Healthcare solutions and architectures, and recognize the challenges and requirements of IoHT devices for diverse utilization instances. In addition, we also indicate challenges and possible solutions in integrating fog/edge computing into remote IoHT solutions. Even with these upsides, conventional centralized access constraint confronts privacy problems and patient health data security. This study likewise constructs a “ blockchain-enabled edge that computes” mechanism, through which smart contracts with the consensus protocol produced by Edge Intelligent Server are deployed to security privacy topics and balance scalability in trustless surroundings. The analysis consequences displayed that there is a vast benefit for remote IoHT solutions that are dependent on fog and edge techniques. We expect this paper will be a significant guideline for the succeeding elaboration of fog/edge-based that computes solutions for smart in-home remote healthcare IoT applications. There will be a change of paradigm from “ hospital-based ” to “ distributed patient in-home healthcare ”.

Keywords: Fog/Edge Computing, Internet of Health Things (IoHT), Smart In-Home Remote Healthcare, Blockchain-Enabled Edge Computing, Security and Privacy

Suggested Citation

Chu, Kuo Ming, Understanding Ioht and Edge/Fog Computing Solutions for Smart In-Home Remote Healthcare. Available at SSRN: https://ssrn.com/abstract=4050300 or http://dx.doi.org/10.2139/ssrn.4050300

Kuo Ming Chu (Contact Author)

Cheng Shiu University ( email )

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