AI smart glasses evolve into wearable personal assistants
AI Smart Glasses for Wearable Intelligence: From Egocentric Sensing to Agentic Personalization
Computer Vision and Pattern Recognition
Summary
Smart glasses are becoming more than just devices to display information or record what you see. The authors explain how recent advances in artificial intelligence are making smart glasses into intelligent systems worn on the face that can understand their environment and help people in real time. These glasses combine sensing from a first-person perspective, efficient computing, smart reasoning, and interactive design to offer personalized assistance in daily tasks. The survey outlines the hardware, AI capabilities, interaction methods, and real-world uses, while highlighting future research challenges.
What this means in practice
- •For healthcare providers: Use AI smart glasses to provide real-time personalized assistance and monitoring to patients in clinical and everyday settings.
- •For cultural tourism guides: Enhance tourist experiences by offering contextual and personalized information through AI smart glasses adapted to cultural sites.
A survey. It maps existing work.
Authors
Xu Yuan, Yi Wang, Zhuohang Jiang, Haohao Qu, Yujuan Ding, Shanru Lin, Guoliang Xing, Hongxia Yang, Jiannong Cao, Qing Li, Wenqi Fan
Abstract
Recent advances in artificial intelligence (AI) are reshaping smart glasses from egocentric capture and display devices into platforms for wearable intelligence. Smart glasses increasingly serve as wearable AI systems that connect first-person observation with real-time assistance under strict form-factor constraints. We frame this transition through the lens of \emph{AI smart glasses} and define them as a system-level concept in which egocentric sensing, resource-aware computing, intelligent reasoning, multimodal interaction, and real-world application constraints are co-designed for personalized assistance in the physical world. To systematically study this perspective, we organize the survey around four connected dimensions. First, we examine the hardware foundation that bounds sensing, computation, feedback delivery, and sustained deployment. Second, we study wearable intelligence, where egocentric signals are transformed into perceptual, contextual, and agentic capabilities. Third, we discuss interaction design, through which users request, receive, correct, and regulate assistance during ongoing activity. Fourth, we analyze application scenarios across healthcare, accessibility, situated learning, daily life assistance, cultural tourism, and industrial support, showing how domain requirements reshape system design and evaluation. We further identify five cross-cutting research challenges for future AI smart glasses: next-generation hardware, trustworthy egocentric intelligence, lifelong personalized memory, proactive intelligence, and embodied foundation models. By centering smart glasses as wearable-intelligence platforms, this survey provides a unified framework for organizing technologies, applications, and open challenges in this emerging area.