A wearable sensor node for measuring air quality through citizen science approach: insights from the SOCIO-BEE project

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dc.contributor.authorMorresi, Nicole
dc.contributor.authorPuerta Beldarrain, Maite
dc.contributor.authorLópez de Ipiña González de Artaza, Diego
dc.contributor.authorBarco, Alex
dc.contributor.authorGómez Carmona, Oihane
dc.contributor.authorLópez Gomollón, Carlos
dc.contributor.authorCasado Mansilla, Diego
dc.contributor.authorKotzagianni, Maria
dc.contributor.authorCasaccia, Sara
dc.contributor.authorUdina Oliva, Sergi
dc.contributor.authorRevel, Gian Marco
dc.date.accessioned2025-12-02T15:57:53Z
dc.date.available2025-12-02T15:57:53Z
dc.date.issued2025-06-15
dc.date.updated2025-12-02T15:57:53Z
dc.description.abstractAir pollution is a major environmental and public health challenge, especially in urban areas where fine-grained air quality data are essential to effective interventions. Traditional monitoring networks, while accurate, often lack spatial resolution and public engagement. This study presents a novel wearable wireless sensor node (WSN) that was developed within the Horizon Europe SOCIO-BEE project to support air quality monitoring through citizen science (CS). The low-cost, body-mounted WSN measures NO2, O3, and PM2.5. Three pilot campaigns were conducted in Ancona (Italy), Maroussi (Greece), and Zaragoza (Spain), and involved diverse user groups—seniors, commuters, and students, respectively. PM2.5 sensor data were validated through two approaches: direct comparison with reference stations and spatial clustering analysis using K-means. The results show strong correlation with official PM2.5 data (R2 = 0.75), with an average absolute error of 0.54 µg/m3 and a statistical confidence interval of ±3.3 µg/m3. In Maroussi and Zaragoza, where no reference stations were available, the clustering approach yielded low intra-cluster coefficients of variation (CV = 0.50 ± 0.40 in Maroussi, CV = 0.28 ± 0.30 in Zaragoza), indicating that the measurements had high internal consistency and spatial homogeneity. Beyond technical validation, user engagement and perceptions were evaluated through pre-/post-campaign surveys. Across all pilots, over 70% of participants reported satisfaction with the system’s usability and inclusiveness. The findings demonstrate that wearable low-cost sensors, when supported by a structured engagement and data validation framework, can provide reliable, actionable air quality data, empowering citizens and informing evidence-based environmental policy.en
dc.description.sponsorshipThis work has been sponsored by SOCIO-BEE Horizon Europe project with Grant ID 101037648 and DEUSTEK5 (IT1582-22) Basque University system’s A grade research team granten
dc.identifier.citationMorresi, N., Puerta-Beldarrain, M., López-de-Ipiña, D., Barco, A., Gómez-Carmona, O., López-Gomollon, C., Casado-Mansilla, D., Kotzagianni, M., Casaccia, S., Udina, S., & Revel, G. M. (2025). A wearable sensor node for measuring air quality through citizen science approach: insights from the SOCIO-BEE project. Sensors, 25(12). https://doi.org/10.3390/S25123739
dc.identifier.doi10.3390/S25123739
dc.identifier.eissn1424-8220
dc.identifier.urihttps://hdl.handle.net/20.500.14454/4518
dc.language.isoeng
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)
dc.rights© 2025 by the authors
dc.subject.otherAir quality
dc.subject.otherCitizen science
dc.subject.otherWearable devices
dc.titleA wearable sensor node for measuring air quality through citizen science approach: insights from the SOCIO-BEE projecten
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.issue12
oaire.citation.titleSensors
oaire.citation.volume25
oaire.licenseConditionhttps://creativecommons.org/licenses/by/4.0/
oaire.versionVoR
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