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CCRI: Planning: Collaborative Research: Low-Latency for Augmented Reality Interactive Systems (LLARIS)

CCRI：规划：协作研究：低延迟增强现实交互系统（LLARIS）

基本信息

批准号：
2016714
负责人：
Francisco Ortega
金额：
$ 10万
依托单位：
Colorado State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2023-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2016714&HistoricalAwards=false
关键词：
CCRI Planning Collaborative Research Low

项目摘要

Augmented Reality and Virtual Reality (AR/VR) technologies can massively reshape human interactions, industrial applications, urban planning, education, and many other fields. An AR application typically captures data from a physical device, sends them to a remote server (increasingly hosted through cloud platforms) for processing, and the server then returns the results to the application. These interactions need to happen quickly. The threshold network delay that an AR application can tolerate is typically between 10 to 50 milliseconds. However, when cloud-hosted servers are involved, the actual latency can be much more than 50 milliseconds. Since the speed of light limits network latency, merely creating faster networks with more bandwidth will not solve this problem. Instead, we must move the computation closer to the network's edge while exploiting the computational capacity of the existing cloud platforms. This planning proposal advances state of the art by (1) leveraging collaborative planning (more ideas, perspectives) to develop higher quality, widely usable infrastructure for human-computer interaction researchers; (2) engaging a large group of human-computer interaction and networking researchers in the planning phase, which encourages and increases infrastructure adoption; (3) providing valuable, comprehensive findings applicable to multiple research areas, like machine learning, that will offer researchers novel information to advance their work; and (4) producing a proof-of-concept prototype for future AR infrastructure.The demand is rapidly growing for AR in domains such as manufacturing industry, aviation, education, entertainment, and defense. This project explores how to build the next-generation infrastructure for next-generation AR systems that will become pervasive in people's everyday life. This project not only contributes to the human-computer interaction and networking community but also contributes to the Future of the Work at the Human-Technology Frontier (one of National Science Foundation's 10 big ideas), launches collaborative explorations between computer scientists and cognitive/learning scientists on how to make learning AR applications easier, and produces new interdisciplinary courses. The groundwork laid by this work paves the path for the next-generation research infrastructure and transformative computing and communication systems.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.

增强现实和虚拟现实（AR/VR）技术可以大规模地重塑人类互动、工业应用、城市规划、教育和许多其他领域。AR应用程序通常从物理设备捕获数据，将它们发送到远程服务器（越来越多地通过云平台托管）进行处理，然后服务器将结果返回给应用程序。这些互动需要迅速发生。AR应用程序可以容忍的阈值网络延迟通常在10到50毫秒之间。但是，当涉及云托管服务器时，实际延迟可能远远超过50毫秒。由于光速限制了网络延迟，仅仅创建具有更多带宽的更快网络并不能解决这个问题。相反，我们必须将计算移动到网络边缘，同时利用现有云平台的计算能力。该规划提案通过以下方式推进了最先进的技术：(1)利用协作规划（更多的想法和观点）为人机交互研究人员开发更高质量、广泛可用的基础设施；(2)在规划阶段吸引大批人机交互和网络研究人员，鼓励并增加基础设施的采用；(3)提供适用于多个研究领域的有价值的、全面的发现，如机器学习，这将为研究人员提供新的信息来推进他们的工作；(4)为未来的AR基础设施制作概念验证原型。制造业、航空、教育、娱乐、国防等领域对AR的需求正在迅速增长。该项目探索如何为下一代AR系统构建下一代基础设施，这些系统将在人们的日常生活中无处不在。该项目不仅有助于人机交互和网络社区，而且有助于人类技术前沿工作的未来（美国国家科学基金会十大理念之一），启动计算机科学家和认知/学习科学家之间关于如何使学习AR应用更容易的合作探索，并产生新的跨学科课程。这项工作奠定的基础为下一代研究基础设施和变革性计算和通信系统铺平了道路。该奖项反映了美国国家科学基金会的法定使命，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。

项目成果

期刊论文数量（18）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

NUI-SpatialMarkers: AR Spatial Markers For the Rest of Us

NUI-SpatialMarkers：适合我们其他人的 AR 空间标记

DOI：
10.1109/vrw55335.2022.00022
发表时间：
2022
期刊：
2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops
影响因子：
0
作者：
Karduna, Alex;Williams, Adam S.;Ortega, Francisco R.
通讯作者：
Ortega, Francisco R.

Trustworthy and Reliable Deep-Learning-Based Cyberattack Detection in Industrial IoT

DOI：
10.1109/tii.2022.3190352
发表时间：
2023-01
期刊：
IEEE Transactions on Industrial Informatics
影响因子：
12.3
作者：
Fazlullah Khan;Ryan Alturki;Md. Arafatur Rahman;Spyridon Mastorakis;Imran Razzak;Syed Tauhidullah Shah
通讯作者：
Fazlullah Khan;Ryan Alturki;Md. Arafatur Rahman;Spyridon Mastorakis;Imran Razzak;Syed Tauhidullah Shah

ARtisan Bistro: A Cooking Task Environment to Conduct Studies in Augmented Reality

ARtisan Bistro：用于在增强现实中进行研究的烹饪任务环境

DOI：
发表时间：
2022
期刊：
2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct
影响因子：
0
作者：
AdityaRaikwar, Lucas Plabst
通讯作者：
AdityaRaikwar, Lucas Plabst

Harpocrates: Anonymous Data Publication in Named Data Networking

DOI：
10.1145/3532105.3535025
发表时间：
2022-01
期刊：
Proceedings of the 27th ACM on Symposium on Access Control Models and Technologies
影响因子：
0
作者：
Md Washik Al Azad;R. Tourani;Abderrahmen Mtibaa;Spyridon Mastorakis
通讯作者：
Md Washik Al Azad;R. Tourani;Abderrahmen Mtibaa;Spyridon Mastorakis

An NDN-Enabled Fog Radio Access Network Architecture with Distributed In-Network Caching