Data-driven Surveillance
Data-Driven Surveillance is a methodological framework within production surveillance that systematically employs empirical data and analytical algorithms to monitor, detect, and evaluate deviations in production processes, distinguishing itself by its reliance on quantitative evidence and automated inference rather than predefined rules or subjective oversight.
39
Publications
1.6K
Citations
124
Authors
68
Institutions
Publications per year
2017–2026
27
Parents
39
Big Data Surveillance: Introduction
Mark Andrejevic, Kelly Gates · Surveillance & Society · 2014 · 225 citations · Full text
Mark Andrejevic · Surveillance & Society · 2019 · 132 citations · Full text
Alexandra Brintrup, Edward Elson Kosasih, Philipp Schaffer et al. · International Journal of Production Research · 2023 · 79 citations · Full text
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68
Memorial University of Newfoundland
St. John's, Canada
3 h-index
3 publications
239 citations

University of Colorado Denver
Denver, United States
2 h-index
4 publications
94 citations
University of California, Berkeley
Berkeley, United States
2 h-index
11 publications
213 citations

The University of Queensland
Brisbane, Australia
2 h-index
4 publications
285 citations
University of California, Irvine
Irvine, United States
1 h-index
1 publications
13 citations
American College of Surgeons
Chicago, United States
1 h-index
1 publications
37 citations

University of Amsterdam
Amsterdam, The Netherlands
1 h-index
1 publications
38 citations
Texas Tech University
Lubbock, United States
1 h-index
6 publications
138 citations
1–8 of 68
5 publications · 526 citations
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2 publications · 57 citations
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PACMHCI · 1 publications · 13 citations
1
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1 publications · 11 citations
1
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1 publications · 20 citations
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