Bindi: Affective internet of things to combat gender-based violence

dc.affiliation.dptoUC3M. Departamento de Tecnología Electrónicaes
dc.affiliation.dptoUC3M. Departamento de Teoría de la Señal y Comunicacioneses
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Diseño Microelectrónico y Aplicaciones (DMA)es
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Procesado Multimediaes
dc.affiliation.institutoUC3M. Instituto Universitario de Estudios de Géneroes
dc.contributor.authorMiranda Calero, José Ángel
dc.contributor.authorRituerto González, Esther
dc.contributor.authorLuis Mingueza, Clara
dc.contributor.authorCanabal Benito, Manuel Felipe
dc.contributor.authorRamírez Bárcenas, Alberto
dc.contributor.authorLanza Gutiérrez, José Manuel
dc.contributor.authorPeláez Moreno, Carmen
dc.contributor.authorLópez Ongil, Celia
dc.contributor.funderComunidad de Madrides
dc.contributor.funderMinisterio de Ciencia e Innovación (España)es
dc.contributor.funderUniversidad Carlos III de Madrides
dc.description.abstractThe main research motivation of this article is the fight against gender-based violence and achieving gender equality from a technological perspective. The solution proposed in this work goes beyond currently existing panic buttons, needing to be manually operated by the victims under difficult circumstances. Instead, Bindi, our end-to-end autonomous multimodal system, relies on artificial intelligence methods to automatically identify violent situations, based on detecting fear-related emotions, and trigger a protection protocol, if necessary. To this end, Bindi integrates modern state-of-the-art technologies, such as the Internet of Bodies, affective computing, and cyber-physical systems, leveraging: 1) affective Internet of Things (IoT) with auditory and physiological commercial off-the-shelf smart sensors embedded in wearable devices; 2) hierarchical multisensorial information fusion; and 3) the edge-fog-cloud IoT architecture. This solution is evaluated using our own data set named WEMAC, a very recently collected and freely available collection of data comprising the auditory and physiological responses of 47 women to several emotions elicited by using a virtual reality environment. On this basis, this work provides an analysis of multimodal late fusion strategies to combine the physiological and speech data processing pipelines to identify the best intelligence engine strategy for Bindi. In particular, the best data fusion strategy reports an overall fear classification accuracy of 63.61% for a subject-independent approach. Both a power consumption study and an audio data processing pipeline to detect violent acoustic events complement this analysis. This research is intended as an initial multimodal baseline that facilitates further work with real-life elicited fear in women.en
dc.description.sponsorshipThis work was supported in part by the Department of Research and Innovation of Madrid Regional Authority, in the EMPATIA-CM Research Project (Reference Y2018/TCS-5046) funded by MCIN/AEI/10.13039/501100011033 under Grant PDC2021-121071-I00; in part by the European Union NextGenerationEU/PRTR in part by the Spanish Ministry of Universities with the FPU under Grant FPU19/00448; and in part by the Madrid Government (Comunidad de Madrid-Spain) through the Multiannual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M26), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).en
dc.identifier.bibliographicCitationMiranda Calero, J. A., Rituerto-Gonzalez, E., Luis-Mingueza, C., Canabal, M. F., Barcenas, A. R., Lanza-Gutierrez, J. M., Pelaez-Moreno, C., & Lopez-Ongil, C. (2022). Bindi: Affective Internet of Things to Combat Gender-Based Violence. IEEE Internet of Things Journal, 9(21), 21174-21193.en
dc.identifier.publicationtitleIEEE Internet of Things Journalen
dc.relation.projectIDComunidad de Madrid. Y2018/TCS-5046es
dc.relation.projectIDGobierno de España. PDC2021-121071-I00es
dc.relation.projectIDComunidad de Madrid. EPUC3M26es
dc.rights© The authors.en
dc.rightsAtribución 3.0 España*
dc.rights.accessRightsopen accessen
dc.subject.otherArtificial intelligence of thingsen
dc.subject.otherEdge computingen
dc.subject.otherFear recognitionen
dc.subject.otherMicroelectromechanical systemsen
dc.subject.otherMultimodal data fusionen
dc.subject.otherSmart sensorsen
dc.titleBindi: Affective internet of things to combat gender-based violenceen
dc.typeresearch article*
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
2.16 MB
Adobe Portable Document Format