Bindi: Affective Internet of Things to Combat Gender-Based Violence

Loading...
Thumbnail Image
Authors
López-Ongil, Celia
Peláez-Moreno, Carmen
Lanza-Gutiérrez, Jose M.
Bárcenas, Alberto Ramírez
Canabal, Manuel F.
Luis-Mingueza, Clara
Rituerto-González, Esther
Calero, Jose A. Miranda
Issue Date
2022-05-23
Type
Article
Language
en_US
Keywords
Affective , Internet of Things , Combat , Gender-Based Violence
Research Projects
Organizational Units
Journal Issue
Alternative Title
Abstract
The 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.
Description
Citation
J. A. Miranda Calero et al., "Bindi: Affective Internet of Things to Combat Gender-Based Violence," in IEEE Internet of Things Journal, vol. 9, no. 21, pp. 21174-21193, 1 Nov.1, 2022, doi: 10.1109/JIOT.2022.3177256.
Publisher
IEEE Internet of Things Journal
Journal
Volume
Issue
PubMed ID
DOI
ISSN
EISSN