CAREER: Toward a Specialized Edge for Augmented Reality

增强现实（AR）应用是一种流行的媒体，使数百万用户受益。领域专家和公众使用AR应用程序进行日常任务，包括安全培训，旅游和在线购物。然而，现有的边缘辅助AR系统在处理噪声传感器数据、在动态工作负载下管理边缘资源以及减轻视觉隐私风险方面往往存在不足。拟议的工作将通过设计一个通用的设备到边缘管道，为专业化的边缘奠定科学基础，AR开发人员可以使用该管道来实现和部署高效和隐私保护的AR任务。所提出的技术将补充和扩展用于移动的AR框架和边缘资源管理的现有方法。建议的研究重点包括：（1）高质量数据捕获，自适应和可扩展的数据共享以及资源高效执行的技术;（2）AR研究人员获得新见解的方法和数据集，以及开发人员提高AR应用程序性能的资源管理技术;以及（3）隐私保护方法，帮助AR开发人员减轻与AR开发和部署相关的隐私风险。所提出的技术将跨越开发到部署，并提高AR应用程序的端到端性能。PI定期开放源代码系统和数据集，促进采用并使研究界受益。该研究计划将通过为具有不同技术背景的学生提供参与移动的和边缘计算研究的机会，支持本科研究人员的参与。PI将在PI的现有课程中创建和试点移动的AR交互式课程材料，并将其公开。与AR技术领导者和领域专家的合作将简化技术转移，并让学生接触真实世界的AR产品。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Augmented Reality (AR) applications are a popular media that benefits millions of users. Domain experts and the public use AR applications for daily tasks, including safety training, tourism, and online shopping. However, existing edge-assisted AR systems often fall short in handling noisy sensor data, managing edge resources under dynamic workloads, and mitigating visual privacy risks. The proposed work will lay the scientific foundations for a specialized edge by designing a generic device-to-edge pipeline that AR developers can use to implement and deploy efficient and privacy-preserving AR tasks. The proposed techniques will complement and extend existing approaches for mobile AR frameworks and edge resource management. The proposed research thrusts include: (1) techniques for high-quality data capture, adaptive and scalable data sharing, and resource-efficient execution; (2) methods and datasets for AR researchers to gain new insights, and resource management techniques for developers to improve the performance of their AR applications; and (3) privacy-preserving approaches that help AR developers mitigate privacy risks associated with AR development and deployment. The proposed techniques will span development through deployment and improve AR applications' end-to-end performance. The PI regularly open-sources systems and datasets, promoting adoption and benefiting the research community. The research program will support the inclusion of undergraduate researchers by providing opportunities to students with diverse technical backgrounds to engage in mobile and edge computing research. The PI will create and pilot interactive course materials on mobile AR in the PI's existing courses and make them publicly available. Collaboration with AR technology leaders and domain experts will ease technology transfer and expose students to real-world AR products.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.