Sensor-based Search

Sensor-Based Search is a search methodology that systematically locates, identifies, or tracks targets by processing and interpreting data acquired from physical or virtual sensors, distinguishing it from other search approaches through its reliance on real-time or recorded sensory observations to guide and inform the search process.

27

Publications

797

Citations

70

Authors

49

Institutions

Publications per year

2017–2026

4

Authors

70

  1. KJ
    Kenneth J. Hintz

    George Mason University, United States

    3 publications · 63 citations

    3

    h-index

  2. GA
    Gregory A. McIntyre

    U.S. Air Force Institute of Technology, United States

    3 publications · 63 citations

    3

    h-index

  3. KR
    Kay Römer

    Graz University of Technology, Austria

    3 publications · 137 citations

    3

    h-index

  4. TM
    Tana Maurer

    US Night Vision (United States), United States

    2 publications · 28 citations

    2

    h-index

  5. LM
    Leslie M. Collins

    Duke University, United States

    2 publications · 45 citations

    2

    h-index

1–5 of 70

Venues

  1. 5

    h-index

  2. University of Twente Research Information

    Repository · 1 publications · 11 citations

    1

    h-index

  3. Information Processing in Sensor Networks

    Conference · 1 publications · 71 citations

    1

    h-index

  4. IEEE Internet of Things Journal

    1 publications · 15 citations

    1

    h-index

  5. Sensors

    1 publications · 25 citations

    1

    h-index

1–5