NeTS: Small: NSF-DST: Modernizing Underground Mining Operations with Millimeter-Wave Imaging and Networking

NeTS：小型：NSF-DST：利用毫米波成像和网络实现地下采矿作业现代化

• 批准号: 2342833
• 负责人: Sanjib Sur
• 金额: $ 59.96万
• 依托单位: University of South Carolina at Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-05-01 至 2027-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2342833&HistoricalAwards=false
• 关键词: NeTS; Small; NSF; DST; Modernizing; NeTS; Small; NSF; DST; Modernizing

The project aims to address the unique challenges of sensing and networking in underground mining environments by employing millimeter-wave (mmWave) wireless, a core technology for 5G and beyond standards. This technology is particularly suited for the harsh conditions of underground mines, such as dust and low light or dark conditions. However, the adoption of mmWave technology in mining is challenging due to reconstructing high-quality 3D maps in complex structures, fusing static and mobile underground real-time maps, and deploying mmWave communication infrastructures. By overcoming these challenges, this project seeks to enhance safety in mining operations, improve operational efficiency through better resource management, navigation, and machinery positioning, and contribute to the national interest by advancing the future of autonomous mining systems. The collaboration with Indian institutions, known for their mining expertise, funded by the Department of Science and Technology (DST), India, aims to advance the state of the art in modern mining technology. This project supports education and diversity by providing hands-on experiences to students, integrating research results into graduate-level courses, and demonstrating prototypes. The technical contributions of this project involve three main thrusts. Thrust 1 emphasizes robust 3D mapping with mmWave devices, addressing challenges like motion error and signal sparsity through dynamic velocity estimation and deep learning while integrating mobile and static maps for a comprehensive environment structure. Thrust 2 aims to establish resilient networking alongside mmWave sensing for rapid connectivity and precise mapping, addressing communication systems signaling and latency challenges and leveraging deep learning for efficient mmWave deployment in mines. Thrust 3 presents a comprehensive evaluation plan for validating earlier thrusts through tests with lab-scale prototypes and trials in a mining simulator. Furthermore, the project designs and empirically validates the proposed systems in a mmWave testbed inside a real-world mining environment. This project aligns with global sustainability goals and addresses some of the pressing challenges in the modern mining industry.This project is jointly funded by the Networking Technology and Systems (NeTS) program, and the Established Program to Stimulate Competitive Research (EPSCoR).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.

该项目旨在通过采用毫米波（MMWave）无线（一种5G和超出标准的核心技术）来应对地下采矿环境中传感和网络的独特挑战。这项技术特别适合地下矿山的恶劣条件，例如灰尘和低光或黑暗条件。但是，由于在复杂的结构中重建高质量的3D地图，融合静态和移动地下实时地下图以及部署MMWave通信基础架构，因此采用MMWave技术在采矿中的采用是具有挑战性的。通过克服这些挑战，该项目旨在通过更好的资源管理，导航和机械定位来提高采矿业务的安全性，提高运营效率，并通过促进自主采矿系统的未来来促进国家利益。与印度科学技术系（DST）资助的印度机构合作，旨在推进现代采矿技术的最新技术。该项目通过为学生提供动手体验，将研究结果纳入研究生级课程并展示原型来支持教育和多样性。该项目的技术贡献涉及三个主要推力。推力1强调与MMWave设备的强大3D映射，通过动态速度估计和深度学习来应对运动误差和信号稀疏等挑战，同时将移动和静态图整合为全面的环境结构。 Thrust 2旨在建立弹性网络以及MMWave感知的迅速连通性和精确映射，解决通信系统信号传导和延迟挑战，并利用深度学习以进行矿山中的有效MMWave部署。推力3提出了一项全面的评估计划，用于通过实验室规模的原型和采矿模拟器中的试验来验证早期推力。此外，该项目在现实世界采矿环境中的MMWave测试中验证了拟议的系统。 This project aligns with global sustainability goals and addresses some of the pressing challenges in the modern mining industry.This project is jointly funded by the Networking Technology and Systems (NeTS) program, and the Established Program to Stimulate Competitive Research (EPSCoR).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.