Collaborative Research:CISE-MSI:DP:CNS:Adaptive Multi-Tiered, Multi-Task Base Station Infrastructure For Communication-Denied Environments

合作研究:CISE-MSI:DP:CNS:用于通信被拒绝环境的自适应多层、多任务基站基础设施

基本信息

  • 批准号:
    2318726
  • 负责人:
  • 金额:
    $ 24.94万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-10-01 至 2026-09-30
  • 项目状态:
    未结题

项目摘要

Nowadays, cellular networks have emerged as the preeminent communication technology, primarily due to their profound impact on modern society. 5G and beyond offer distinctive features, such as high transmission rate, ultra-reliable low-latency communication, massive machine-type communication, and edge and cloud computing. Nevertheless, the performance of these networks can be susceptible to fluctuations in demand or unanticipated physical damage to the underlying infrastructure - i.e., terrestrial base stations (TBSs) - through natural or man-made disasters. Recent advancements in artificial intelligence, control systems, and autonomy within the realm of cyber-physical systems have facilitated the utilization of autonomous unmanned aerial vehicles (UAVs) and autonomous vehicles to establish temporary cellular networks. These networks rely on flying base stations (FBSs) or vehicular base stations (VBS) in large-scale disasters or events where TBSs are either unavailable or unable to provide the required coverage and quality of service (QoS). In addition to their communication services, these autonomous vehicles can offer diverse functionalities, including rapid mapping of expansive areas, operations in hazardous zones, emergency deliveries, and search-and-rescue missions. However, despite the conceptual, scientific, and engineering advancements achieved thus far, the FBS and VBS infrastructures have not yet reached their full maturity.The principal objective of this project is to develop an adaptive, multi-objective, multitier, and multi-task infrastructure consisting of aerial and vehicular base stations (MTBS). The aim is to improve the coverage and QoS of cellular systems while simultaneously facilitating various services, including situational awareness, package delivery, and target tracking, particularly in scenarios where the number of available vehicles is limited. The research and education agenda is framed around three thrusts: (1) performing fundamental research aimed at developing models and algorithmic tools for developing and implementing an adaptive, multi-tiered collection of UAVs and VBSs, to provide communication infrastructure in challenging environments, such as in a disaster zone; (2) developing trajectory-planning models in MTBS systems to deliver a realistic solution for effectively utilizing the base stations in critical missions wherein a small number of vehicles are available; and (3) evaluating the performance of the proposed models using testbed environments. The testbed and open-source code packages developed in this project will allow educators and field professionals to deploy them in both learning and training environments.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.
如今,蜂窝网络已成为卓越的通信技术,主要是因为它们对现代社会产生了深远的影响。 5G及以上技术具有高传输速率、超可靠低时延通信、海量机器类通信、边缘计算和云计算等显着特征。然而,这些网络的性能可能容易受到需求波动或自然或人为灾害对底层基础设施(即地面基站(TBS))的意外物理损坏的影响。人工智能、控制系统和网络物理系统领域的自主性的最新进展促进了利用自主无人机(UAV)和自动驾驶车辆来建立临时蜂窝网络。在大规模灾难或事件中,TBS 不可用或无法提供所需的覆盖范围和服务质量 (QoS),这些网络依赖于飞行基站 (FBS) 或车载基站 (VBS)。除了通信服务之外,这些自动驾驶车辆还可以提供多种功能,包括快速绘制广阔区域的地图、危险区域的操作、紧急交付以及搜救任务。然而,尽管迄今为止在概念、科学和工程方面取得了进步,FBS 和 VBS 基础设施尚未完全成熟。该项目的主要目标是开发一种自适应、多目标、多层和多任务的系统基础设施包括空中和车载基站(MTBS)。其目的是提高蜂窝系统的覆盖范围和服务质量,同时促进各种服务,包括态势感知、包裹递送和目标跟踪,特别是在可用车辆数量有限的情况下。研究和教育议程围绕三个重点:(1)进行基础研究,旨在开发模型和算法工具,以开发和实施自适应、多层无人机和 VBS 集合,以在具有挑战性的环境中提供通信基础设施,例如在灾区; (2) 开发 MTBS 系统中的轨迹规划模型,以提供现实的解决方案,以便在可用车辆数量较少的关键任务中有效利用基站; (3) 使用测试平台环境评估所提出模型的性能。该项目中开发的测试平台和开源代码包将允许教育工作者和现场专业人员将其部署在学习和培训环境中。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评估进行评估,被认为值得支持。影响审查标准。

项目成果

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Fatemeh Afghah其他文献

Efficient Fuzzy-Based 3-D Flying Base Station Positioning and Trajectory for Emergency Management in 5G and Beyond Cellular Networks
用于 5G 及其他蜂窝网络应急管理的高效模糊 3D 飞行基站定位和轨迹
  • DOI:
    10.1109/jsyst.2024.3359776
  • 发表时间:
    2024-06-01
  • 期刊:
  • 影响因子:
    4.4
  • 作者:
    M. J. Sobouti;H. Adarbah;Afshin Alaghehb;Hamid Chitsaz;A. Mohajerzadeh;Mehdi Sookhak;Seyed Amin Hosseeini Seno;Abedin Vahedian;Fatemeh Afghah
  • 通讯作者:
    Fatemeh Afghah
PyroTrack: Belief-Based Deep Reinforcement Learning Path Planning for Aerial Wildfire Monitoring in Partially Observable Environments
PyroTrack:基于信念的深度强化学习路径规划,用于部分可观测环境中的空中野火监测
  • DOI:
    10.48550/arxiv.2403.11095
  • 发表时间:
    2024-03-17
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sahand Khoshdel;Qi Luo;Fatemeh Afghah
  • 通讯作者:
    Fatemeh Afghah
FlameFinder: Illuminating Obscured Fire through Smoke with Attentive Deep Metric Learning
FlameFinder:通过专注的深度度量学习通过烟雾照亮模糊的火焰
  • DOI:
    10.48550/arxiv.2404.06653
  • 发表时间:
    2024-04-09
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Hossein Rajoli;Sah;Khoshdel;Fatemeh Afghah;Xiaolong Ma
  • 通讯作者:
    Xiaolong Ma
Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision
气候智能型林业的人工智能:前瞻性愿景
  • DOI:
    10.1109/cogmi58952.2023.00011
  • 发表时间:
    2023-11-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Feng Luo;Ling Liu;G. G. Wang;Vijay Kumar;Mark S. Ashton;Jacob Abernethy;Fatemeh Afghah;Matthew H. E. M. Browning;David Coyle;Philip Dames;Tom O'Halloran;James Hays;Patrick Heisl;Chenfanfu Jiang;Puskar Khanal;V. Krovi;Sara Kuebbing;Nianyi Li;Jingjing Liang;Ninghao Liu;Steve McNulty;C. Oswalt;Neil Pederson;D. Terzopoulos;Christopher W. Woodall;Yongkai Wu;Jian Yang;Yin Yang;Liang Zhao
  • 通讯作者:
    Liang Zhao
Wildland Fire Detection and Monitoring Using a Drone-Collected RGB/IR Image Dataset
使用无人机收集的 RGB/IR 图像数据集进行荒地火灾探测和监控
  • DOI:
    10.1109/access.2022.3222805
  • 发表时间:
    2024-09-14
  • 期刊:
  • 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
  • 通讯作者:
    Adam Watts

Fatemeh Afghah的其他文献

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{{ truncateString('Fatemeh Afghah', 18)}}的其他基金

CAREER: Toward Autonomous Decision Making and Coordination in Intelligent Unmanned Aerial Vehicles' Operation in Dynamic Uncertain Remote Areas
职业:在动态不确定的偏远地区实现智能无人机操作的自主决策和协调
  • 批准号:
    2232048
  • 财政年份:
    2022
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Continuing Grant
Collaborative Research: SWIFT: LARGE: AI-Enabled Spectrum Coexistence between Active Communications and Passive Radio Services: Fundamentals, Testbed and Data
合作研究:SWIFT:大型:主动通信和无源无线电服务之间人工智能支持的频谱共存:基础知识、测试平台和数据
  • 批准号:
    2202972
  • 财政年份:
    2021
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
Collaborative Research: CPS: Medium: Wildland Fire Observation, Management, and Evacuation using Intelligent Collaborative Flying and Ground Systems
协作研究:CPS:中:使用智能协作飞行和地面系统进行荒地火灾观测、管理和疏散
  • 批准号:
    2204445
  • 财政年份:
    2021
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
Collaborative Research: CPS: Medium: Wildland Fire Observation, Management, and Evacuation using Intelligent Collaborative Flying and Ground Systems
协作研究:CPS:中:使用智能协作飞行和地面系统进行荒地火灾观测、管理和疏散
  • 批准号:
    2039026
  • 财政年份:
    2021
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
Collaborative Research: CPS: Medium: Wildland Fire Observation, Management, and Evacuation using Intelligent Collaborative Flying and Ground Systems
协作研究:CPS:中:使用智能协作飞行和地面系统进行荒地火灾观测、管理和疏散
  • 批准号:
    2204445
  • 财政年份:
    2021
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
Collaborative: Smart Health in the AI and COVID Era
协作:人工智能和新冠时代的智能健康
  • 批准号:
    2120217
  • 财政年份:
    2021
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
PFI-RP: Design and Fabrication of Hardware-based Security Platform using Fabrication Variability of Ultra low Power Memories
PFI-RP:利用超低功耗存储器的制造可变性设计和制造基于硬件的安全平台
  • 批准号:
    2204502
  • 财政年份:
    2021
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
PFI-RP: Design and Fabrication of Hardware-based Security Platform using Fabrication Variability of Ultra low Power Memories
PFI-RP:利用超低功耗存储器的制造可变性设计和制造基于硬件的安全平台
  • 批准号:
    2204502
  • 财政年份:
    2021
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
SCC-PG: Just in Time Intervention for Patients with Chronic Heart Diseases in Arizona tribes
SCC-PG:对亚利桑那州部落慢性心脏病患者进行及时干预
  • 批准号:
    2125643
  • 财政年份:
    2021
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
SCC-PG: Just in Time Intervention for Patients with Chronic Heart Diseases in Arizona tribes
SCC-PG:对亚利桑那州部落慢性心脏病患者进行及时干预
  • 批准号:
    2213915
  • 财政年份:
    2021
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant

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相似海外基金

Collaborative Research: CISE-MSI: RCBP-RF: CNS: ESD4CDaT - Efficient System Design for Cancer Detection and Treatment
合作研究:CISE-MSI:RCBP-RF:CNS:ESD4CDaT - 癌症检测和治疗的高效系统设计
  • 批准号:
    2318573
  • 财政年份:
    2023
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
Collaborative Research: CISE-MSI: DP: HCC: Buenas - Giving All a Seat at the Table Using Mixed Reality
协作研究:CISE-MSI:DP:HCC:布埃纳斯 - 使用混合现实为所有人提供席位
  • 批准号:
    2318657
  • 财政年份:
    2023
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  • 项目类别:
    Standard Grant
Collaborative Research:CISE-MSI:DP:CNS:Enabling On-Demand and Flexible Mobile Edge Computing with Integrated Aerial-Ground Vehicles
合作研究:CISE-MSI:DP:CNS:通过集成空地车辆实现按需且灵活的移动边缘计算
  • 批准号:
    2318662
  • 财政年份:
    2023
  • 资助金额:
    $ 24.94万
  • 项目类别:
    Standard Grant
Collaborative Research:CISE-MSI:DP:CNS:Enabling On-Demand and Flexible Mobile Edge Computing with Integrated Aerial-Ground Vehicles
合作研究:CISE-MSI:DP:CNS:通过集成空地车辆实现按需且灵活的移动边缘计算
  • 批准号:
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Collaborative Research: CISE: Large: Integrated Networking, Edge System and AI Support for Resilient and Safety-Critical Tele-Operations of Autonomous Vehicles
合作研究:CISE:大型:集成网络、边缘系统和人工智能支持自动驾驶汽车的弹性和安全关键远程操作
  • 批准号:
    2321531
  • 财政年份:
    2023
  • 资助金额:
    $ 24.94万
  • 项目类别:
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