Emotion-Aware AI Model for Early Detection of Gender-Based Violence and Mental Distress

In this paper, we propose an Emotion-Aware AI Model for early detection of gender-based violence and associated mental distress. Our system continuously monitors a person’s emotional state (via smartphone or wearable sensors) and flags patterns indicative of abuse or psychological crisis. The model architecture combines deep networks for visual, vocal, and textual emotion analysis, and fuses them with an attention mechanism to form a holistic affective representation. By leveraging emotional cues as predictive features, the system aims to raise alerts before severe harm occurs. The rest of this draft outlines related work, the proposed methodology and architecture, a hypothetical experimental setup, expected contributions, and future directions