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Overcoming software bottlenecks for scalable passive acoustic monitoring: A survey-informed expert consensus

delete2026-08-06
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OA
AI
M
Martino E. Malerba *
K
Kristian Bell
M
Maria M. Palacios
K
Kristen Bellisario
C
Camille Desjonquères
A
Alba Márquez-Rodríguez
I
Irene Mendoza
C
Christoph F. J. Meyer
V
Vijay Ramesh
X
Xavier Raick
T
Tessa A. Rhinehart
C
Connor M. Wood
M
Morgan A. Ziegenhorn
G
Giuseppa Buscaino
M
Marconi Campos‐Cerqueira
M
Marina H. L. Duarte
A
Amandine Gasc
T
Tara Hanf‐Dressler
F
Francis Juanes
L
Leandro Aparecido do Nascimento
DOI：10.1016/j.ecoinf.2026.103971delete
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Abstract

Abstract

En 中文
• PAM generates vast data, shifting bottlenecks from collection to analysis. • Expert solicitation identified AI-based species ID as the top PAM challenge. • Fragmented workflow and tools hinder PAM implementation. • Manual validation, data sharing, and standardisation remain critical barriers. • Practical guides help address key bottlenecks in PAM analytical workflows.
Keywords:
Passive acoustic monitoring
Bioacoustics
Workflow optimisation
Software bottlenecks
Artificial intelligence
Scalable ecological monitoring
Data management

Journal

Ecological Informatics cover
Ecological Informatics
IF:
7.3
Papers:
3.7K
Citations:
1.3W

Organization

No organization information available
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