Dynamic Sensor Selection
Dynamic Sensor Selection is a context-aware fusion methodology that dynamically identifies and activates the most relevant subset of available sensors in real time based on situational, environmental, or task-specific conditions to optimize performance, resource efficiency, and data quality.
41
Publications
1.5K
Citations
124
Authors
66
Institutions
Publications per year
2017–2026
13
Parents
41
Sensor ontologies: from shallow to deep models
David J. Russomanno, Cartik R. Kothari, O. Thomas · 2005 · 103 citations
IoT-based predictive maintenance for fleet management
Patrick Killeen, Bo Ding, Iluju Kiringa et al. · Procedia Computer Science · 2019 · 99 citations · Full text
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Syracuse University
Syracuse, United States
3 h-index
8 publications
443 citations

University of Ottawa
Ottawa, Canada
3 h-index
8 publications
367 citations
University of Southern California
Los Angeles, United States
2 h-index
4 publications
92 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
6 publications
198 citations
Rensselaer Polytechnic Institute
Troy, United States
2 h-index
3 publications
47 citations

Centre National de la Recherche Scientifique
Paris, France
2 h-index
4 publications
124 citations
University of Michigan
Ann Arbor, United States
2 h-index
4 publications
112 citations
University of Science and Technology of Mazandaran
Behshahr, Iran
1 h-index
1 publications
15 citations
1–8 of 66
2 publications · 38 citations
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1 publications · 43 citations
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1 publications · 23 citations
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1 publications · 15 citations
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TIOT · 1 publications · 14 citations
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