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

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) 无线技术（5G 及超越标准的核心技术）来解决地下采矿环境中传感和网络的独特挑战。该技术特别适合地下矿井的恶劣条件，例如灰尘和弱光或黑暗条件。然而，由于在复杂结构中重建高质量 3D 地图、融合静态和移动地下实时地图以及部署毫米波通信基础设施，在采矿中采用毫米波技术具有挑战性。通过克服这些挑战，该项目旨在提高采矿作业的安全性，通过更好的资源管理、导航和机械定位来提高运营效率，并通过推进自主采矿系统的未来为国家利益做出贡献。与以采矿专业知识而闻名的印度机构的合作，由印度科学技术部 (DST) 资助，旨在推进现代采矿技术的发展。该项目通过为学生提供实践经验、将研究成果融入研究生课程以及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方面。 Thrust 1 强调使用毫米波设备实现稳健的 3D 映射，通过动态速度估计和深度学习解决运动误差和信号稀疏等挑战，同时集成移动和静态地图以形成全面的环境结构。 Thrust 2 旨在与毫米波传感一起建立弹性网络，以实现快速连接和精确映射，解决通信系统信号和延迟挑战，并利用深度学习在矿山中实现毫米波的高效部署。 Thrust 3 提出了一个全面的评估计划，用于通过实验室规模的原型测试和采矿模拟器中的试验来验证早期的推力。此外，该项目还在现实采矿环境中的毫米波测试台上设计并凭经验验证了所提出的系统。该项目符合全球可持续发展目标，并解决了现代采矿业中的一些紧迫挑战。该项目由网络技术和系统 (NeTS) 计划以及刺激竞争性研究既定计划 (EPSCoR) 共同资助。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。