Scalable Sensing Architectures

Scalable Sensing Architectures is a distributed sensing framework designed to systematically expand in sensor node count or spatial coverage while maintaining performance efficiency, resource optimization, and data integrity across varying scales.

28

Publications

3K

Citations

130

Authors

73

Institutions

Publications per year

2017–2026

9

Authors

130

  1. SL
    Simon Laflamme

    Iowa State University, United States

    3 publications · 142 citations

    3

    h-index

  2. RA
    Ronald A. Peterson

    Dartmouth College, United States

    2 publications · 616 citations

    2

    h-index

  3. EM
    Emiliano Miluzzo

    Dartmouth College, United States

    2 publications · 616 citations

    2

    h-index

  4. PL
    Peter L. Voyvodic

    Inserm, France

    2 publications · 95 citations

    2

    h-index

  5. AP
    Amir Pandi

    Microbiologie de l’alimentation au service de la santé, France

    2 publications · 95 citations

    2

    h-index

1–5 of 130

Venues

  1. 2

    h-index

  2. Nature Communications

    1 publications · 83 citations

    1

    h-index

  3. Science

    1 publications · 195 citations

    1

    h-index

  4. Journal of Sensors

    1 publications · 55 citations

    1

    h-index

  5. Smart Materials and Structures

    SMS · 1 publications · 32 citations

    1

    h-index

1–5