Emotion-Enhanced Content Recommendation in IoT-Connected Entertainment Environments for Personalized Streaming Experiences
S. Mohan Kumar, J. Selvi, Balaji Madhavan, S. Rajarajan, C. Nelson Kennedy Babu · 2023
The Internet of Things (IoT) and content recommendation systems are converging, which provides a new paradigm for improving the personalization of streaming experiences. This convergence occurs within the context of the shifting landscape of entertainment consumption. This study investigates the topic of "Emotion-Enhanced Content Recommendation in IoT-Connected Entertainment Environments." A ground-breaking framework for identifying the emotional states of viewers while streaming content has been established by integrating Internet of Things devices with technology for emotion identification. This system uses real-time data from the Internet of Things devices, such as wearables and ambient sensors, to pick up on subtle emotional indicators such as facial expressions and physiological reactions. These insights into users' feelings are then used to dynamically alter content suggestions so that the people align with the predominant emotional contexts of individual users. The use of contextual emotional intelligence not only boosts user engagement and happiness but also plots a road toward a streaming ecology that is more empathic and immersive. This research investigates ethical problems, highlights technical hurdles, and highlights the possibility of individualized emotional resonance in entertainment powered by the IoT.