Emotionally Intelligent AI: A Multimodal Human Computer Interface
Abstract: Facial emotion detection in humans is a major focus in today's technological advancements. Robotic applications are being applied in almost all domains. This field holds immense potential to benefit humanity through improved self-awareness, empathy, and social interaction. The human face is an integral component of an individual's physical form and plays a critical role in the detection and identification of emotions, serving as the principal medium through which fundamental affective states are manifested. Leveraging advancements in machine learning and sensor technologies, the proposed interface captures and analyzes diverse data streams, including facial expressions, speech patterns, and physiological responses, to infer user emotional states. By integrating data from multiple modalities, such as facial expressions, vocal cues, and physiological signals, the AI aims to recognize and interpret human emotions accurately. This emotional awareness allows the AI to adapt its behavior, providing more intuitive and engaging interactions. Integrating IoT into an emotion recognition model can significantly enhance its capabilities by providing real-time, contextual data and expanding the range of detectable emotional cues.[1] IoT is a notable innovation, which fundamentally is an associated system of physical articles or gadgets that can be gotten to through the internet. IoT systems leverage sensors to capture information and exchange it across the system. This project aims to develop and implement a novel, automatic emotion detection system and facial recognition system based on AI (Artificial Intelligence) and IoT (Internet of Things).
Authors
- Ashwini Battawar
- Pranav Deulkar
- Vedant Gawande
- Navoday Kopawar
- Yogesh Gohane
- Swapnil Chavhan
- Darshan Dudhe
- Amit Durge
Institutions
- Universitas Darma Persada (ID)
Publication Details
- Journal
- International Journal for Research in Applied Science and Engineering Technology
- Published
- 2025-03-24
- DOI
- https://doi.org/10.22214/ijraset.2025.67761
- Primary Topic
- Speech and dialogue systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00