CPS: Synergy: Collaborative Research: Enabling Smart Underground Mining with an Integrated Context-Aware Wireless Cyber-Physical Framework

CPS：协同：协作研究：通过集成的上下文感知无线网络物理框架实现智能地下采矿

• 批准号: 1646576
• 负责人: Qi Han
• 金额: $ 33.75万
• 依托单位: Colorado School of Mines
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1646576&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; Enabling

To reduce reliance on other countries for minerals (e.g., coal, rare-earth metals), the USA has seen an invigoration of mining activity in recent years. Unfortunately, miners often have to work in dangerous environments where there is risk of mine explosions, fires, poisonous gases, and flooding in tunnels. Mine accidents have killed over 500 US and 40,000 mine workers worldwide in the past decade. Most of these accidents occurred in structurally diverse underground mines with extensive labyrinths of interconnected tunnels, where the environment continually changes as mining progresses and machinery is repositioned, complicating search and rescue efforts. In recognition of the severity of the problem, the Mine Improvement and New Emergency Response Act passed in 2006 mandated mines to monitor levels of methane, carbon monoxide, smoke, and oxygen to warn miners of possible danger due to air poisoning, fire, or explosions. The Act also mandated plans to rapidly and safely respond in post-accident scenarios, involving two-way, wired or semi-wired tracking and communication systems that could save lives during entrapment and water inundation emergencies. But the high cost of deploying such a safety infrastructure encourages companies today to meet only the bare minimum required safeguards. This project will involve transformative, foundational, and synergistic research that is necessary to overcome monitoring, communication, and tracking challenges in the underground mining context, to realize a cost-effective safety infrastructure that can be deployed in any type of underground mine. Such a framework will not only minimize the risks facing hundreds of thousands of miners in the USA today, but the foundational research outcomes will also be applicable to a wide range of applications in the realms of Smart and Connected Communities (S&CC) and Internet of Things (IoT), wherever the emphasis is on creating smart workplaces, sustainably operating in harsh environments, and improving human safety.The principal objective of this proposal is to devise, design, prototype, and test a fundamentally novel wireless cyber-physical framework of low-cost, energy-efficient, and reliable sensor nodes and commodity smartphones for monitoring, tracking, and communication, to improve miner safety in underground mines. This synergy project contributes to the science and engineering principles needed to realize Cyber-Physical Systems and seeks to grow at the intersection of three research thrusts: quality-aware voice and data streaming, mobile computing assisted location tracking, and computational electromagnetics driven wireless signal characterization. These three thrusts (1) introduce novel mechanisms to enable the co-existence of high quality voice streams with environmental sensor data streams in low-power wireless mesh networks of sensor nodes operating in noisy underground environments; (2) develop schemes for energy-efficient scheduling of location queries and error-tolerant indoor localization to locate individual miners and groups of miners underground; and (3) characterize wireless signal behavior with electromagnetic modeling in highly complex and uncertain environments, based on measurements from a real underground mine, to guide optimal placement of wireless nodes in mining tunnels. Not only is the convergence of these thrusts novel as a whole, but also the techniques and insights developed for each thrust are transformative and go beyond conventional approaches. Collaboration with a mining company for technology transfer will enable rapid real-world deployment of the proposed research. The broader impacts of the research will tightly integrate research results into all levels of teaching, including graduate, undergraduate, and K-12 education; broaden the participation of women and minority students in Cyber-Physical research; and integrate research into the syllabi of existing and new courses.

减少对其他国家矿物的依赖（例如，煤炭，稀土金属），美国近年来看到了采矿活动的振兴。不幸的是，矿工经常不得不在危险的环境中工作，那里有矿井爆炸，火灾，有毒气体和隧道洪水的风险。在过去十年中，矿难已造成500多名美国和4万名全球矿工死亡。这些事故大多发生在结构多样的地下矿井，其中有大量相互连接的隧道，随着采矿的进展和机械的重新定位，环境不断变化，使搜索和救援工作复杂化。由于认识到问题的严重性，2006年通过的《矿井改进和新应急反应法》要求矿井监测甲烷、一氧化碳、烟雾和氧气的水平，以警告矿工可能因空气中毒、火灾或爆炸而造成的危险。该法案还规定了在事故发生后迅速安全地作出反应的计划，包括双向有线或半有线跟踪和通信系统，这些系统可以在被困和水淹没紧急情况下挽救生命。但是，部署这种安全基础设施的高昂成本促使今天的公司只满足最低限度的安全保障要求。该项目将涉及变革性、基础性和协同性研究，这是克服地下采矿环境中的监测、通信和跟踪挑战所必需的，以实现可在任何类型的地下矿山中部署的具有成本效益的安全基础设施。这样的框架不仅将最大限度地减少当今美国数十万矿工面临的风险，而且基础研究成果也将适用于智能互联社区（S& CC）和物联网（IoT）领域的广泛应用，重点是创建智能工作场所，在恶劣环境中可持续运营，该提案的主要目标是设计，设计，原型设计和测试一种低成本，节能，可靠的传感器节点和商品智能手机的无线网络物理框架，用于监控，跟踪和通信，以提高地下矿井中矿工的安全性。该协同项目有助于实现网络物理系统所需的科学和工程原理，并寻求在三个研究方向的交叉点上发展：质量感知语音和数据流，移动的计算辅助位置跟踪和计算电磁学驱动的无线信号表征。这三个重点（1）引入新的机制，以使高质量的语音流与环境传感器数据流能够在嘈杂的地下环境中操作的传感器节点的低功率无线网状网络中共存;（2）开发用于位置查询的节能调度和容错室内定位的方案，以定位地下的单个矿工和矿工组;以及（3）基于来自真实的地下矿井的测量，利用高度复杂和不确定环境中的电磁建模来表征无线信号行为，以指导采矿隧道中无线节点的最佳布置。不仅这些重点的融合作为一个整体是新颖的，而且为每个重点开发的技术和见解也是变革性的，超越了传统的方法。与一家矿业公司合作进行技术转让，将使拟议研究能够在现实世界中快速部署。研究的更广泛影响将紧密结合研究成果到各级教学，包括研究生，本科和K-12教育;扩大妇女和少数民族学生在网络物理研究的参与;并将研究纳入现有和新课程的教学大纲。

项目成果

Distributed Learning Automata Based Data Dissemination in Networked Robotic Systems

• DOI: 10.1007/978-3-030-28468-8_10
• 发表时间: 2019-06
• 期刊: 2023 31st Mediterranean Conference on Control and Automation (MED)
• 作者: Gerald Henderson;Qi Han

Performance evaluation of wi-fi for underground robots

地下机器人Wi-Fi性能评估

• DOI: 10.1145/3360774.3368198
• 发表时间: 2019
• 期刊: Networking and Services
• 作者: Zhu, L.;Wen, X.;Han, Q.;Fryer, A.;Suttora, N.;Petruska, A.
• 通讯作者: Petruska, A.

Request and Share then Assign (RASTA): Task Assignment for Networked Multi-Robot Teams

请求并共享然后分配（RASTA）：网络多机器人团队的任务分配

• DOI: 10.1109/mass50613.2020.00058
• 发表时间: 2020
• 期刊: IEEE International Conference on Mobile Ad-hoc Sensor Systems (MASS
• 作者: Friedman, Samuel;Han, Qi
• 通讯作者: Han, Qi

Quality-Aware Voice Convergecast in Mobile Low Power Wireless Networks

• DOI: 10.1007/978-3-030-28468-8_16
• 发表时间: 2019-06
• 作者: Mike Adkins;Qi Han;S. Pasricha

ICCSwarm: A Framework for Integrated Communication and Control in UAV Swarms

ICCSwarm：无人机群集成通信和控制框架

• DOI: 10.1145/3539493.3539579
• 发表时间: 2022
• 期刊: and Applications
• 作者: Diller, Jonathan;Hall, Peter;Schanker, Corey;Ung, Kristen;Belous, Philip;Russell, Peter;Han, Qi
• 通讯作者: Han, Qi