WEPOP project scientific production

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Main Authors: Cosoli, Gloria, Casaccia, Sara, PISELLO, ANNA LAURA, Scardulla, Francesco, Dianel Ago, Mansi, Silvia Angela, SARTINI, GIANLUCA, Martins Gnecco, Veronica, Tomar, Puneet, ARNESANO, MARCO
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Published: Zenodo 2026
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_version_ 1866902057849454592
author Cosoli, Gloria
Casaccia, Sara
PISELLO, ANNA LAURA
Scardulla, Francesco
Dianel Ago
Mansi, Silvia Angela
SARTINI, GIANLUCA
Martins Gnecco, Veronica
Tomar, Puneet
ARNESANO, MARCO
author_facet Cosoli, Gloria
Casaccia, Sara
PISELLO, ANNA LAURA
Scardulla, Francesco
Dianel Ago
Mansi, Silvia Angela
SARTINI, GIANLUCA
Martins Gnecco, Veronica
Tomar, Puneet
ARNESANO, MARCO
contents <p>This repository contains the scientific production of the WEPOP project (entirely as open access versions), namely:</p> <ul> <li>n. 6 papers in scientific journals</li> <li>n. 7 conference proceedings</li> <li>n. 1 data descriptor</li> </ul> <p>The DOIs of all the publicazions are reported in the Related work section.</p> <p>Acknowledgements</p> <p>This research was co-funded by the Italian Ministry of Research through the WEPOP (Prot.2022RKLB3J) ‘’WEarable Platform for OptImised Personal comfort’’ project, within the PRIN 2022 program.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_19388267
institution Zenodo
language
publishDate 2026
publisher Zenodo
record_format zenodo
spellingShingle WEPOP project scientific production
Cosoli, Gloria
Casaccia, Sara
PISELLO, ANNA LAURA
Scardulla, Francesco
Dianel Ago
Mansi, Silvia Angela
SARTINI, GIANLUCA
Martins Gnecco, Veronica
Tomar, Puneet
ARNESANO, MARCO
personalized comfort
well-being
built environment
PCM
physiological signals
Machine Learning
signal processing
<p>This repository contains the scientific production of the WEPOP project (entirely as open access versions), namely:</p> <ul> <li>n. 6 papers in scientific journals</li> <li>n. 7 conference proceedings</li> <li>n. 1 data descriptor</li> </ul> <p>The DOIs of all the publicazions are reported in the Related work section.</p> <p>Acknowledgements</p> <p>This research was co-funded by the Italian Ministry of Research through the WEPOP (Prot.2022RKLB3J) ‘’WEarable Platform for OptImised Personal comfort’’ project, within the PRIN 2022 program.</p>
title WEPOP project scientific production
topic personalized comfort
well-being
built environment
PCM
physiological signals
Machine Learning
signal processing
url https://doi.org/10.5281/zenodo.19388267