Evidence map›Paper›PMID 38163154›Full record

ReviewHeliyon2024

Ecology & computer audition: Applications of audio technology to monitor organisms and environment.

Björn W Schuller, Alican Akman, Yi Chang, Harry Coppock, Alexander Gebhard, Alexander Kathan, Esther Rituerto-González, Andreas Triantafyllopoulos, Florian B Pokorny

Abstract readReview
In one paragraph

Review in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Björn W SchullerGLAM - Group on Language, Audio, & Music, Imperial College London, UK.
Alican AkmanGLAM - Group on Language, Audio, & Music, Imperial College London, UK.
Yi ChangGLAM - Group on Language, Audio, & Music, Imperial College London, UK.
Harry CoppockGLAM - Group on Language, Audio, & Music, Imperial College London, UK.
Alexander GebhardEIHW - Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Germany.
Alexander KathanEIHW - Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Germany.
Esther Rituerto-GonzálezEIHW - Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Germany.
Andreas TriantafyllopoulosEIHW - Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Germany.
Florian B PokornyEIHW - Chair of Embedded Intelligence for Health Care and Wellbeing, University of Augsburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among the 17 Sustainable Development Goals (SDGs) proposed within the 2030 Agenda and adopted by all the United Nations member states, the 13th SDG is a call for action to combat climate change. Moreover, SDGs 14 and 15 claim the protection and conservation of life below water and life on land, respectively. In this work, we provide a literature-founded overview of application areas, in which computer audition - a powerful but in this context so far hardly considered technology, combining audio signal processing and machine intelligence - is employed to monitor our ecosystem with the potential to identify ecologically critical processes or states. We distinguish between applications related to organisms, such as species richness analysis and plant health monitoring, and applications related to the environment, such as melting ice monitoring or wildfire detection. This work positions computer audition in relation to alternative approaches by discussing methodological strengths and limitations, as well as ethical aspects. We conclude with an urgent call to action to the research community for a greater involvement of audio intelligence methodology in future ecosystem monitoring approaches.

Indexed as

Audio technologyCall to actionComputer auditionEcologyEnvironmentOrganism

Identifiers

PMID38163154
PMCPMC10755287

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.