Quality and the efficiency of data in “Smart-Cities”
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IoT streaming data may be impacted by inherent quality problems such as stream inconsistency (redundancy or outlier) and missing (or incomplete) data.
“It is evident that IoT streaming data may be impacted by inherent quality problems such as stream inconsistency (redundancy or outlier) and missing (or incomplete) data [2], which impact the effectiveness and trustworthiness of smart city systems.”
From Semantic-Driven Approach for Validation of IoT Streaming Data in Trustable Smart City Decision-Making and Monitoring Systems (2025) · cites this paper as [2]
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Towards a secure service provisioning framework in a Smart city environment
Khan, Z., Pervez, Z., & Abbasi, A. G. (2017) · Future Generation Computer Systems · doi:10.1016/j.future.2017.06.031 · Cited by 87 · see citing works
Bamgboye, O., Liu, X., Cruickshank, P., & Liu, Q. (2025) · Big Data and Cognitive Computing · doi:10.3390/bdcc9040108 · Cited by 4 · see citing works
“It is evident that IoT streaming data may be impacted by inherent quality problems such as stream inconsistency (redundancy or outlier) and missing (or incomplete) data [2], which impact the effectiveness and trustworthiness of smart city systems.”
- Authors
- Sta, H. B.
- Affiliations
- Tunis University (TN)
- Corresponding author
- Sta, Hatem Ben
- Venue
- Future Generation Computer Systems
- Publisher
- Elsevier BV
- Published
- 2017-09
- Volume
- 74
- Pages
- 409-416
- ISSN
- 0167-739X (ISSN-L)
- OpenAlex
- W2564138207
- Cited by
- 108
- References
- 70
- Citations by year
- 2026: 5 · 2025: 13 · 2024: 11 · 2023: 5 · 2022: 10 · 2021: 14 · 2020: 12 · 2019: 15 · 2018: 13 · 2017: 10
- FWCI
- 13.88
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Future Generation Computer Systems (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Multi-Criteria Decision Making
- Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Data Quality and Management
- Keywords
- smart cities, belief functions, Dempster-Shafer theory, imperfect data, data quality, data integration, information retrieval, uncertainty, imprecision, heterogeneous data sources, health data, Internet of Things
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