Enhancing Human-Computer Interaction Through Artificial Intelligence and Machine Learning: A Comprehensive Review

Enhancing Human-Computer Interaction Through Artificial Intelligence and Machine Learning: A Comprehensive Review

Neha Singh (Invertis University, India), Jitendra Nath Shrivastava (Invertis University, India), Gaurav Agarwal (Invertis University, India), Akash Sanghi (Invertis University, India), Swati Jha (Invertis University, India), Kamal Upreti (Christ University, India), Ramesh Chandra Poonia (Christ University, India), and Amit Kumar Gupta (KIET Group of Institutions, India)
Copyright: © 2025 |Pages: 22
DOI: 10.4018/979-8-3693-5728-6.ch009
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Abstract

The interaction between Human-Cyber-Physical Systems (CPS) has become increasingly critical as CPS technologies permeate various facets of modern life, from smart homes to industrial automation. This highlights the evolving landscape of research aimed at fostering smooth interaction between humans and CPS, stressing the necessity of bridging the gap between users and these intricate systems.Effective interaction with CPS requires a profound understanding of human behaviors, preferences, and cognitive processes. .Furthermore, this emphasizes notable research trends aimed at improving Human-CPS interaction, including the exploration of innovative interaction modalities such as natural language processing, gesture recognition, and brain-computer interfaces.Thanks to Artificial Intelligence (AI) and Machine Learning (ML), computer interactions are changing a lot.
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