Requirements, Limitations and Recommendations for Enabling End-to-End Quality of Context-Awareness in IoT Middleware
Open accessAbstract
Satisfying a context consumer’s quality of context (QoC) requirements is important to context management platforms (CMPs) in order to have credibility. QoC indicates the contextual information’s quality metrics (e.g., accuracy, timeliness, completeness). The outcomes of these metrics depend on the functional and quality characteristics associated with all actors (context consumers (or) context-aware applications, CMPs, and context providers (or) IoT-data providers) in context-aware IoT environments. This survey identifies and studies such characteristics and highlights the limitations in actors’ current functionalities and QoC modelling approaches to obtain adequate QoC and improve context consumers’ quality of experience (QoE). We propose a novel concept system based on our critical analysis; this system addresses the functional limitations in existing QoC modelling approaches. Moreover, we highlight those QoC metrics affected by quality of service (QoS) metrics in CMPs. These recommendations provide CMP developers with a reference system they could incorporate, functionalities and QoS metrics to maintain in order to deliver an adequate QoC.
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It is still challenging to encode the intricacies of context in AI algorithms.
“It is still challenging to encode the intricacies of context in AI algorithms [96].”
From Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond (2024) · cites this paper as [96]
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Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond
Nasir, S., Khan, R. A., & Bai, S. (2024) · IEEE Access · doi:10.1109/access.2024.3369912 · Cited by 152 · see citing works
- Authors
- Jagarlamudi, K. S., Zaslavsky, A., Loke, S. W., Hassani, A., & Medvedev, A.
- Affiliations
- Deakin University (AU)
- Corresponding author
- Jagarlamudi, Kanaka Sai
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2022-02-19
- Volume
- 22
- Issue
- 4
- Pages
- 1632
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC8880260
- OpenAlex
- W4212882910
- Cited by
- 15
- References
- 56
- Citations by year
- 2026: 4 · 2024: 5 · 2023: 5 · 2022: 1
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Deakin Research Online (Deakin University) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Service-Oriented Architecture and Web Services
- Keywords
- quality of context, context awareness, IoT middleware, quality of experience, quality of service, context-aware systems, reference systems
- MeSH terms
- Internet of Things, Surveys and Questionnaires
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