Embedded Sensing

Embedded Sensing is a method in which sensor functionality is integratively implemented within IoT-enabled actuator systems through computational models or soft sensor techniques, enabling context-aware data acquisition and real-time monitoring without relying on dedicated physical sensors.

160

Publications

9K

Citations

601

Authors

210

Institutions

Publications per year

2017–2026

64

Authors

601

  1. CL
    Christine L. Borgman

    University of California, Los Angeles, United States

    9 publications · 832 citations

    9

    h-index

  2. DE
    Deborah Estrin

    University of California, Los Angeles, United States

    7 publications · 327 citations

    7

    h-index

  3. JC
    Jillian C. Wallis

    University of California, Los Angeles, United States

    7 publications · 728 citations

    7

    h-index

  4. MS
    Matthew S. Mayernik

    NSF National Center for Atmospheric Research, United States

    6 publications · 285 citations

    6

    h-index

  5. AP
    Alberto Pepe

    University of California, Los Angeles, United States

    6 publications · 254 citations

    6

    h-index

1–5 of 601

Venues

  1. Sensors

    8 publications · 236 citations

    8

    h-index

  2. eScholarship (California Digital Library)

    Repository · 5 publications · 149 citations

    5

    h-index

  3. 5

    h-index

  4. IEEE Sensors Journal

    4 publications · 99 citations

    4

    h-index

  5. 2

    h-index

1–5