A blockchain-based fog computing framework for activity recognition as an application to e-healthcare services
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Islam et al. admit Internet bandwidth is a constraint.
“Similarly, Islam et al. (2019) also admit that Internet bandwidth is a constraint.”
From Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda (2020) · cites this paper as Islam et al., 2019
Time-related issues discussed as constraints include time searching for global smart contracts, increased time consumption, transmission timing, time to seek data in shared storage, and higher total execution time.
“Time-related issues have also been discussed as a constraint, including the time spent searching for the global smart contracts (Dagher et al., 2018), increased time consumption (Islam et al., 2019), transmission timing (Griggs et al., 2018), time required for seeking the required data in shared storage by the data recipient (Rahmadika & Rhee, 2019), and higher total execution time (Kuo et al., 20”
From Blockchain in healthcare: A systematic literature review, synthesizing framework and future research agenda (2020) · cites this paper as Islam et al., 2019
Fog computing has many benefits and is suited for applications that require fast response time, low latency, and real-time processing, especially healthcare.
“Fog computing has many benefits and is suited for applications that require fast response time, low latency, and real-time processing, for specially healthcare [47,208].”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [208]
Islam et al.'s human activity recognition platform including blockchain based Fog-Cloud computing did not describe how blockchain has been utilized and no performance analysis has been conducted regarding blockchain, Fog and Cloud platform.
“The authors did not describe how blockchain has been utilized in the proposed framework and no performance analysis has been conducted regarding blockchain, Fog and Cloud platform.”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [208]
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References 40 · Cited by 154
- Authors
- Islam, N., Faheem, Y., Din, I. U., Talha, M., Guizani, M., & Khalil, M.
- Affiliations
- Islamia College University (PK)
- COMSATS University Islamabad (PK)
- University of Haripur (PK)
- King Saud University (SA)
- Qatar University (QA)
- Corresponding author
- Din, Ikram Ud
- Venue
- Future Generation Computer Systems
- Publisher
- Elsevier BV
- Published
- 2019-11
- Volume
- 100
- Pages
- 569-578
- ISSN
- 0167-739X (ISSN-L)
- OpenAlex
- W2946466583
- Cited by
- 154
- References
- 40
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 29 · 2023: 33 · 2022: 22 · 2021: 29 · 2020: 22 · 2019: 4
- FWCI
- 8.62
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Future Generation Computer Systems (publishedVersion)
- Qatar University QSpace (Qatar University) (submittedVersion)
- Funders
- King Saud University
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Keywords
- human activity recognition, blockchain, fog computing, e-health, Internet of Things security, video action recognition, salient feature extraction, support vector machine, remote patient monitoring, mental illness
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