Iot Data Cleaning
IoT Data Cleaning is a data preprocessing methodology that specifically addresses the identification, correction, and removal of errors, inconsistencies, and noise in raw data generated by Internet of Things devices to ensure data accuracy, completeness, and reliability for downstream analytics and decision-making.
30
Publications
872
Citations
113
Authors
60
Institutions
Publications per year
2017–2026
26
Parents
30
An IoT Based Smart Farming System Using Machine Learning
Amine Dahane, Rabaie Benameur, Bouabdellah Kechar et al. · 2020 · 79 citations
Shivanjali Khare, Michael W. Totaro · 2019 · 51 citations
1–5 of 30
113
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h-index
1 publications · 21 citations
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1–5 of 113
60

Gachon University
Seongnam-si, South Korea
2 h-index
3 publications
67 citations
Case Western Reserve University
Cleveland, United States
1 h-index
4 publications
52 citations

University of Modena and Reggio Emilia
Modena, Italy
1 h-index
3 publications
39 citations

University of Oulu
Oulu, Finland
1 h-index
6 publications
84 citations
Ho Chi Minh City University of Technology
Ho Chi Minh City, Vietnam
1 h-index
1 publications
35 citations

Shanghai Jiao Tong University
Shanghai, China
1 h-index
2 publications
98 citations

King Saud University
Riyadh, Saudi Arabia
1 h-index
3 publications
78 citations

Hubei University
Wuhan, China
1 h-index
3 publications
39 citations
1–8 of 60
3 publications · 148 citations
3
h-index
2 publications · 121 citations
2
h-index
1 publications · 35 citations
1
h-index
1 publications · 30 citations
1
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1 publications · 33 citations
1
h-index
1–5