A Multi-Modal Approach for Gender-Based Violence Detection
The impact of living in an unhealthy and unsafe environment leads to perpetuated aggressive and violent behavior. Many organizations have conducted research to identify that violence against women is a deep-rooted issue and has existed for many years. Institutions and women-led groups have gathered to provide assistance and governments have done a lot to least to support the cause. But the severity of this social pandemic is still unresolved across the globe. Research shows that contact with nature reduces the incidence of aggression and violence within family members in a household. Research also shows that air pollution and aggressive behavior are correlated. This paper provides a multi-modal approach to measure Gender-Based Violence Index (GBVI) by detecting the coverage of green canopies using satellite imagery in addition to sensing the level of atmospheric pollution to calculate violence occurrences before they even happen in a given neighborhood. To support the identification process, computer vision technique will be applied to satellite imagery to measure and map out the Vegetation Index (VI) on a scale of 0-100 in a neighborhood along with using air pollution sensors and Internet of Things (IoT) to detect the level of intoxicants that aggravate the cause of violence against women. The result of this approach is promising for organizations like the United Nations, World Health Organization, and government bodies to create rapid response efforts in the interest of women rights, humanitarians, and security communities.
Khatri, H., & Abdellatif, I. (2020). A Multi-Modal Approach for Gender-Based Violence Detection. IEEE Cloud Summit 2020, 1-6. Retrieved from https://digitalcommons.harrisburgu.edu/isem_student-coursework/2
IEEE Cloud Summit 2020
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