探索使用移动增强现实来辅助决策

W. K. Soeltz, Jeff Hickey, Zona Kostic, Anna Lin, Kartik Swamy
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引用次数: 1

摘要

扩展现实适应正在广泛的学科中获得牵引力。移动电话和无标记增强现实(AR)是检索信息的迷人方法,因为它们使内容能够在用户移动时在其直接环境中呈现。这种在物理环境中呈现虚拟内容的方法将为大多数无法使用头戴式显示器等高端设备的大量观众所接受。随着大量的观众,移动设备上的增强现实可以实时显示动态内容,甚至在户外环境中,为用户提供有关物理工件的即时和上下文相关的信息。本文的目的是讨论开发一个移动应用程序,该应用程序将帮助用户根据附近显示的在线内容做出现场决策。除了开发一款帮助用户定位附近餐厅的应用程序外,该应用程序还将重点放在架构、用户界面和体验设计上,因为该应用程序将用于焦点有限的环境中(例如,交通噪音或与真实物体遮挡)。最后讨论了应用程序的用户体验以及该领域未来的研究方向。随着移动设备的快速发展,理解为支持移动决策的应用程序开发更好的用户体验所固有的一些挑战和设计约束是至关重要的。
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Exploring the use of mobile AR to aid decision-making on-the-go
Extended reality adaptation is gaining traction across a broad spectrum of disciplines. Mobile phones and markerless augmented reality (AR) are fascinating methods for retrieving information because they enable content to be rendered in the user’s immediate environment while they are on the move. This method of rendering virtual content within a physical environment will be accessible to a large audience that, for the most part, does not have access to high-end equipment such as head-mounted displays. Along with a large audience, augmented reality on mobile devices can display dynamic content in real time, even in outdoor settings, providing users with information about physical artifacts that is both immediate and contextually relevant. The purpose of this paper is to discuss the development of a mobile application that will assist users in making on-the-spot decisions based on online content displayed nearby. Along with developing an application that assists users in locating nearby restaurants, a strong emphasis is placed on architecture, user interface, and experience design, as the application will be used in environments with limited focus (e.g., traffic noise or occlusion with real objects). The study concludes with a discussion of the application’s user experience and future research directions in this field. With the rapid evolution of mobile devices, it is critical to understand some of the challenges and design constraints inherent in developing better user experiences for applications that support on-the-go decision-making.
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