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Award Abstract # 1646576
CPS: Synergy: Collaborative Research: Enabling Smart Underground Mining with an Integrated Context-Aware Wireless Cyber-Physical Framework

NSF Org: ECCS
Division of Electrical, Communications and Cyber Systems
Recipient: TRUSTEES OF THE COLORADO SCHOOL OF MINES
Initial Amendment Date: August 10, 2016
Latest Amendment Date: June 16, 2021
Award Number: 1646576
Award Instrument: Standard Grant
Program Manager: Lawrence Goldberg
ECCS
 Division of Electrical, Communications and Cyber Systems
ENG
 Directorate for Engineering
Start Date: October 1, 2016
End Date: September 30, 2022 (Estimated)
Total Intended Award Amount: $337,500.00
Total Awarded Amount to Date: $337,500.00
Funds Obligated to Date: FY 2016 = $337,500.00
History of Investigator:
  • Qi Han (Principal Investigator)
    qhan@mines.edu
Recipient Sponsored Research Office: Colorado School of Mines
1500 ILLINOIS ST
GOLDEN
CO  US  80401-1887
(303)273-3000
Sponsor Congressional District: 07
Primary Place of Performance: Colorado School of Mines
1500 Illinois Street
Golden
CO  US  80401-1887
Primary Place of Performance
Congressional District:
07
Unique Entity Identifier (UEI): JW2NGMP4NMA3
Parent UEI: JW2NGMP4NMA3
NSF Program(s): CPS-Cyber-Physical Systems
Primary Program Source: 01001617DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 153E, 7918
Program Element Code(s): 791800
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 12)
Adkins, M. and Han, Q. and Pasricha, S. "Quality-Aware Voice Convergecast in Mobile Low Power Wireless Networks" International Conference on Mobile Computing, Applications, and Services (MobiCASE) , 2019 https://doi.org/10.1007/978-3-030-28468-8_16 Citation Details
Bellini, Pierfrancesco and Bologna, Daniele and Han, Qi and Nesi, Paolo and Pantaleo, Gianni and Paolucci, Michela "Data Ingestion and Inspection for Smart City Applications" IEEE International Conference on SMART Computing , 2020 https://doi.org/10.1109/SMARTCOMP50058.2020.00052 Citation Details
Diller, Jonathan and Hall, Peter and Schanker, Corey and Ung, Kristen and Belous, Philip and Russell, Peter and Han, Qi "ICCSwarm: A Framework for Integrated Communication and Control in UAV Swarms" the Eighth Workshop on Micro Aerial Vehicle Networks, Systems, and Applications , 2022 https://doi.org/10.1145/3539493.3539579 Citation Details
Friedman, Samuel and Han, Qi "Request and Share then Assign (RASTA): Task Assignment for Networked Multi-Robot Teams" IEEE International Conference on Mobile Ad-hoc Sensor Systems (MASS) , 2020 https://doi.org/10.1109/MASS50613.2020.00058 Citation Details
Han, Qi and Nesi, Paolo and Pantaleo, Gianni and Paoli, Irene "Smart City Dashboards: Design, Development, and Evaluation" 2020 IEEE International Conference on Human-Machine Systems (ICHMS) , 2020 https://doi.org/10.1109/ICHMS49158.2020.9209493 Citation Details
Henderson, G and Han, Q. "Distributed Learning Automata based Data Dissemination in Networked Robotic Systems" Mobile Computing, Applications, and Services. MobiCASE 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 290. Springer, , v.290 , 2019 https://doi.org/10.1007/978-3-030-28468-8_10 Citation Details
Perry, Ethan and Han, Qi "Assemble, Control, and Test (ACT): A Management Framework for Indoor IoT Systems" 2021 IEEE International Conference on Smart Computing (SMARTCOMP) , 2021 https://doi.org/10.1109/SMARTCOMP52413.2021.00073 Citation Details
Rands, J. and Han, Q. "Regression-based network monitoring in swarm robotic systems" International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous), November 2019 , 2019 https://doi.org/10.1145/3360774.3360795 Citation Details
Schack, Matthew and Rogers III, John G. and Han, Qi and Dantam, Neil "Optimizing Non-Markovian Information Gain under Physics-based Communication Constraints" IEEE Robotics and Automation Letters , 2021 https://doi.org/10.1109/LRA.2021.3068935 Citation Details
Swamy, Shneka Muthu and Han, Qi "Quality Preserving Voice Stream Multicast over Mobile Low Power Wireless Networks" 2021 IEEE 46th Conference on Local Computer Networks (LCN) , 2021 https://doi.org/10.1109/LCN52139.2021.9524944 Citation Details
Zhao, Yongjian and New, Stephen and Thilakarathna, Kanchana and Zhang, Xiaodong and Han, Qi "Fine Grained Group Gesture Detection Using Smartwatches" International Workshop on Mobile Ubiquitous Systems and Technologies (MUST), in conjunction with IEEE International Conference on Mobile Data Management (MDM), Hong Kong, China, June 10-13, 2019 , 2019 10.1109/MDM.2019.00113 Citation Details
(Showing: 1 - 10 of 12)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

Motivation

Miners work in dangerous environments where they risk mine explosions, fires, poisonous gases, and flooding in tunnels. Mine accidents have killed 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 with uneven walls and obstacles, where the environment continually changes as mining progresses and machinery is repositioned, complicating search and rescue efforts. Unfortunately, the high cost of deploying a safety infrastructure encourages companies to meet only the minimum required safeguards. Mine safety demands a scalable, low-cost solution to enable sensing, communication, and tracking in underground mines to detect precursors to mishaps and also aid rescue efforts in the aftermath of an accident (e.g., a tunnel cave in or an explosion).

Intellectual Merit

The project has devised, designed, prototyped, and tested 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. Specifically, this project has designed quality-aware voice stream multicast and convergecast techniques in low-power wireless mesh networks of sensor nodes operating in noisy underground environments, wireless relay node deployment algorithms to enable more efficient wireless mesh networks, developed techniques for better quality evaluation of mobile augmented reality to be used in improving underground safety, developed a series of algorithms for path planning of drone swarms being used for search and rescue in underground environments. 

 

Broader Impacts

Our techniques are foundational and can be applied 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 results were presented at different academic conferences and published in conference proceedings or journals.  The project has research experience for two graduate students and several undergraduates.

 

The figure below shows a typical network setup in underground environments and also the hardware used for our prototype.

 

   

 

 


Last Modified: 11/28/2022
Modified by: Qi Han

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