Paper Contents
Abstract
This paper offers an extensive discussion of multimodal systems in computing, highlighting the fusion of different types of datatext, image, audio, and videoto make user interaction, decision-making, and personalization more effective across domains. Other than AI-centric terminologies and AI-based personalization models, this research looks into system architecture, data fusion techniques, and unimodal versus multimodal model comparison. It also addresses methodology, data issues, scalability, and ethical issues pertinent to multimodal data fusion. Educational, health, and e-commerce applications are provided with support from simulation instances and structured component analysis.
Copyright
Copyright © 2025 SATBIR. This is an open access article distributed under the Creative Commons Attribution License.
