Collaborative Research: CCRI: New: Distributed Sensing & Computing Over Sparse Environments (DISCOVER) Platform

合作研究：CCRI：新：分布式传感

• 批准号: 2120485
• 负责人: Paul Heinrich
• 金额: $ 136.65万
• 依托单位: Northern Arizona University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2120485&HistoricalAwards=false
• 关键词: Collaborative; Research; CCRI; New; Distributed

DISCOVER (Distributed Sensing and Computing Over Sparse Environments) is a cyberinfrastructure testbed for remote, rural, and sparsely populated areas, consisting of a fabric of highly configurable and fixed and mobile Internet-of-Things (IoT) nodes and a heterogeneous wireless network. The project is a collaborative effort among two minority and undergraduate serving institutions: Northern Arizona University (NAU) and Navajo Technical University (NTU), the largest tribal college in the country located in Navajo land in New Mexico. DISCOVER sites will be located at the NAU and NTU campuses as well as several remote sites.DISCOVER will enable focused research on new breeds of algorithms that address a range of challenges around prioritization and optimization of computation and communication in remote, less populous and rural areas. The proposed infrastructure will advance the frontier of science in different fields of the CISE community by enabling remote experimentation for innovative research including the development and evaluation of: (1) methodologies for collecting and analyzing regional-scale, sparse, temporal-spatial data, (2) heterogeneous networked services, (3) distributed computing and AI, control, decision making, in-network computation and information extraction algorithms for complex CPS, (4) communication-aware software for remote sensing and actuation in heterogeneous and resource-limited networks.The primary goal of DISCOVER is to provide a research platform for investigation of distributed computing, networking, security, control and coordination solutions in a heterogeneous configurable cyber-physical system infrastructure that will provide critical services for areas and populations at increasing risk of being underserved. The education and outreach impacts of this project include training and research opportunities for undergraduate students, engaging underrepresented minority students from American Indian and Alaska Native populations---in particular the Navajo and Tohono O'odham nations---at NAU, NTU and other local tribal colleges and undergraduate universities, and developing hands-on research experiments for K-12 students.A project website will be created to post the material, updates, collected data, and sample scripts. The website will be maintained by the PI and will be accessible via https://www.cefns.nau.edu/~fa334/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.

DISCOVER(稀疏环境下的分布式传感和计算)是面向偏远、农村和人口稀少地区的网络基础设施试验台，由高度可配置且固定和移动的物联网(IoT)节点和异类无线网络组成。该项目是两个少数民族和本科生服务机构的合作努力：北亚利桑那大学(NAU)和纳瓦霍技术大学(NTU)，这是美国最大的部落学院，位于新墨西哥州的纳瓦霍区。DISCOVER将在NAU和NTU校区以及几个偏远地点进行。DISCOVER将使人们能够集中研究新型算法，以解决偏远、人口较少和农村地区计算和通信的优先顺序和优化方面的一系列挑战。拟议的基础设施将推动CEISE社区不同领域的科学前沿，为创新研究提供远程实验，包括开发和评估：(1)收集和分析区域尺度的稀疏时空数据的方法，(2)异质联网服务，(3)分布式计算和人工智能，控制，决策，网络内计算和复杂CP的信息提取算法，(4)用于异质和资源有限的网络中的遥感和驱动的通信感知软件。Discovery的主要目标是为研究分布式计算，网络，安全，各种可配置的网络物理系统基础设施中的控制和协调解决方案，将为面临服务不足风险增加的地区和人口提供关键服务。该项目的教育和外展影响包括为本科生提供培训和研究机会，吸引来自美国印第安人和阿拉斯加原住民-特别是纳瓦霍族和托霍诺奥奥德姆族--的少数族裔学生在NAU、NTU和其他当地部落学院和本科大学学习，并为K-12学生开发动手研究实验。将创建一个项目网站，以发布材料、更新、收集的数据和脚本样本。该网站将由PI维护，并可通过https://www.cefns.nau.edu/~fa334/This访问，该奖项反映了国家科学基金会的法定使命，并已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。

项目成果

Wildland Fire Detection and Monitoring Using a Drone-Collected RGB/IR Image Dataset

• DOI: 10.1109/access.2022.3222805
• 发表时间: 2022
• 期刊: IEEE Access
• 影响因子: 3.9
• 作者: Xiwen Chen;Bryce Hopkins;Hao Wang;Leo O’Neill;Fatemeh Afghah;A. Razi;Peter Fulé;Janice Coen;Eric Rowell;Adam Watts

Attention-Guided Synthetic Data Augmentation for Drone-based Wildfire Detection

用于基于无人机的野火检测的注意力引导综合数据增强

• DOI: 10.1109/infocomwkshps57453.2023.10226139
• 发表时间: 2023
• 期刊: IEEE
• 作者: Boone, Julia;Hopkins, Bryce;Afghah, Fatemeh
• 通讯作者: Afghah, Fatemeh

5G Wings: Investigating 5G-Connected Drones Performance in Non-Urban Areas

5G Wings：研究非城市地区 5G 连接无人机的性能

• 发表时间: 2023
• 期刊: and Computing for UAV Swarms
• 作者: Gharib, Mohammed;Hopkins, Bryce;Murrin, Jackson;Koka, Andre;Afghah, Fatemeh
• 通讯作者: Afghah, Fatemeh

SCC5G: A PQC-based Architecture for Highly Secure Critical Communication over Cellular Network in Zero-Trust Environment

SCC5G：基于 PQC 的架构，用于在零信任环境中通过蜂窝网络进行高度安全的关键通信

• 发表时间: 2023
• 期刊: and Computers
• 作者: Gharib, Mohammed;Afghah, Fatemeh
• 通讯作者: Afghah, Fatemeh