This review demonstrates advancements in interface optimization and human-computer interaction, suggesting AI-driven methods may enhance user experience.
In today’s digital world, where users expect fast, seamless, and personalized interactions, interface optimization has become a crucial area of focus. The evolution of technology over the past decades has dramatically reshaped how people engage with digital systems. Early user interfaces, often characterized by static pages and limited interactivity, reflected the constraints of hardware performance and network capabilities at the time. As processing power increased and internet access expanded, user expectations also rose, driving the need for more dynamic and responsive designs. The emergence of frontend frameworks like React and Vue, alongside the growth of cloud-based backend infrastructures, has enabled developers to create interfaces that are not only visually flexible but also functionally adaptive. Meanwhile, artificial intelligence and machine learning have introduced new possibilities for real-time personalization, predictive interaction, and natural user engagement. This paper reviews key theoretical concepts in interface design, examines the application of new technologies in both 2D and 3D environments, and discusses advancements in human-computer interaction methods, including voice recognition, gesture control, and haptic feedback. It also addresses challenges such as the high computational cost of advanced interfaces, the complexity of catering to diverse user needs, and concerns around data privacy. Looking forward, trends like adaptive AI-driven interfaces, augmented reality (AR), and fully immersive virtual environments are likely to redefine the boundaries of human-machine interaction. By linking current practices with emerging developments, this review aims to offer practical insights for researchers and developers committed to advancing the future of digital interface design.
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Zhiyao Ma (2025) studied this question.