CAREER: Toward a Specialized Edge for Augmented Reality

增强现实(AR)应用是一种使数百万用户受益的流行媒体。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，现有的边缘辅助增强现实系统在处理噪声传感器数据、管理动态工作负载下的边缘资源以及缓解视觉隐私风险方面往往存在不足。这项拟议的工作将通过设计一种通用的设备到边缘管道，为专业优势奠定科学基础，AR开发者可以使用该管道来实施和部署高效且保护隐私的AR任务。建议的技术将补充和扩展移动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、自适应和可扩展数据共享以及资源高效执行的技术；(2)增强现实研究人员获得新见解的方法和数据集；以及(3)帮助增强现实开发者缓解与增强现实相关的隐私风险的隐私保护方法。建议的技术将跨越开发到部署，并提高AR应用的端到端性能。国际和平研究所定期开放源码系统和数据集，促进采用并使研究界受益。该研究计划将通过向具有不同技术背景的学生提供从事移动和边缘计算研究的机会，支持纳入本科生研究人员。PI将在其现有课程中创建和试点关于移动AR的互动课程材料，并将其公之于众。与AR技术领导者和领域专家的合作将简化技术转让，并使学生接触到现实世界的AR产品。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.