A study to classify wild bees' signal using time series analysis

Mohapatra, AR; Nerse, C; Oberst, S; Navarro-Payá, D; Etxeberria, J; Matus, JT; Bianco, L; Tucci, MR; Casacci, LP; Barbero, F

A study to classify wild bees' signal using time series analysis

Mohapatra, AR Nerse, C

Oberst, S

Navarro-Payá, D Etxeberria, J Matus, JT Bianco, L Tucci, MR Casacci, LP Barbero, F

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Publisher:: Society of Acoustics
Publication Type:: Conference Proceeding
Citation:: Proceedings of the International Congress on Sound and Vibration, 2024
Issue Date:: 2024-01-01

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Field	Value	Language
dc.contributor.author	Mohapatra, AR
dc.contributor.author	Nerse, C https://orcid.org/0000-0003-4003-6262
dc.contributor.author	Oberst, S https://orcid.org/0000-0002-1388-2749
dc.contributor.author	Navarro-Payá, D
dc.contributor.author	Etxeberria, J
dc.contributor.author	Matus, JT
dc.contributor.author	Bianco, L
dc.contributor.author	Tucci, MR
dc.contributor.author	Casacci, LP
dc.contributor.author	Barbero, F
dc.date	2024-07-08
dc.date.accessioned	2025-02-20T20:52:42Z
dc.date.available	2025-02-20T20:52:42Z
dc.date.issued	2024-01-01
dc.identifier.citation	Proceedings of the International Congress on Sound and Vibration, 2024
dc.identifier.issn	2329-3675
dc.identifier.issn	2329-3675
dc.identifier.uri	http://hdl.handle.net/10453/185233
dc.description.abstract	Bees (Anthophila) are among the most effective pollinators in nature being responsible for approximately one-third of the total crop pollination for human dietary supply. The interaction between plants and bees plays here an essential role and may also include vibro-acoustic signals as an important medium of information transmission. Plants have been shown to respond to airborne acoustic signals of flying pollinators by increasing the sugar concentration in the nectar. Yet very little is known about the pollinators vibro-acoustic signatures and plant-relevant effective traits of the signal. Here we present an analysis framework of acoustic signals for three different bee species, namely Rhodanthidium sticticum, Amegilla quadrifasciata, and Apis mellifera, recorded in the rural areas (Chera, Chulilla, and Macastre) of the Province of Valencia, Spain, visiting Antirrhinum (snapdragon) plants. First, from audio-visual recordings, audio signals for different bee behaviours during visits were identified. We showed that periodogram and recurrence-based spectrograms could be used to classify real-life bio-acoustic data recorded outdoors. This approach can also be used to predict future data sets for which a traditional approach like spectral analysis is unsuitable, especially for noisy, more nonlinear, and complex data.
dc.language	en
dc.publisher	Society of Acoustics
dc.relation.ispartof	Proceedings of the International Congress on Sound and Vibration
dc.relation.ispartof	International Congress on Sound and Vibration
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.title	A study to classify wild bees' signal using time series analysis
dc.type	Conference Proceeding
utslib.location.activity	Amsterdam, Netherlands
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	University of Technology Sydney/UTS Groups
pubs.organisational-group	University of Technology Sydney/UTS Groups/Transport Research Centre (TRC)
pubs.organisational-group	University of Technology Sydney/UTS Groups/Centre for Audio, Acoustics and Vibration (CAAV)
pubs.organisational-group	University of Technology Sydney/UTS Groups/Transport Research Centre (TRC)/Transport Research Centre (TRC) Associate Members
pubs.organisational-group	University of Technology Sydney/UTS Groups/Centre for Audio, Acoustics and Vibration (CAAV)/Centre for Audio, Acoustics and Vibration (CAAV) Associate Members
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
dc.date.updated	2025-02-20T20:52:40Z
pubs.finish-date	2024-07-11
pubs.publication-status	Published
pubs.start-date	2024-07-08

Abstract:

Bees (Anthophila) are among the most effective pollinators in nature being responsible for approximately one-third of the total crop pollination for human dietary supply. The interaction between plants and bees plays here an essential role and may also include vibro-acoustic signals as an important medium of information transmission. Plants have been shown to respond to airborne acoustic signals of flying pollinators by increasing the sugar concentration in the nectar. Yet very little is known about the pollinators vibro-acoustic signatures and plant-relevant effective traits of the signal. Here we present an analysis framework of acoustic signals for three different bee species, namely Rhodanthidium sticticum, Amegilla quadrifasciata, and Apis mellifera, recorded in the rural areas (Chera, Chulilla, and Macastre) of the Province of Valencia, Spain, visiting Antirrhinum (snapdragon) plants. First, from audio-visual recordings, audio signals for different bee behaviours during visits were identified. We showed that periodogram and recurrence-based spectrograms could be used to classify real-life bio-acoustic data recorded outdoors. This approach can also be used to predict future data sets for which a traditional approach like spectral analysis is unsuitable, especially for noisy, more nonlinear, and complex data.

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http://hdl.handle.net/10453/185233