# Research and Technological Innovations in Automation, Robotics, and Intelligent Mining Systems for Transformative Improvements in Workplace Safety, Health, and Efficiencies

> **NIH ALLCDC U60** · MISSOURI UNIVERSITY OF SCIENCE & TECHNOLOGY · 2024 · $2,000,000

## Abstract

RESEARCH PLAN – ABSTRACT
The U.S. mining industry has advanced technological innovations to improve safety, and health.
These technologies have reduced accidents and fatalities over the years. However, the industry has
one of the most dangerous environments for workers. The 2021 fatality rate of 16.15 was four
times the average rate for all US industries. Autonomous, robotic, and intelligent (ARI) systems
are the next frontiers for achieving zero fatality. This proposal will therefore advance research
initiatives, technological innovations, and interventions in ARI systems to eliminate mine fatalities
within the next two decades. The program will be carried out under the MERIT (Mine Escape,
Research, Innovations and Technology) Center at Missouri University of Science and Technology
(S&T) in collaborations with New Mexico Institute of Mining and Technology (NMT), the mining
industry and NIOSH.
The proposal will (1) develop intelligent data analytics using artificial intelligence (AI) and
machine learning (ML) algorithms for analysis, predictions, and process management to assure
ARI systems; (2) develop cyber and systems network security to secure, protect, and prevent
adversarial attacks against ARI systems; (3) develop an integrated human-centered design and
change management system within human-centered operations for the new intelligent paradigm to
ensure smooth operations; (4) develop an intelligent communication system for bulk data transfer
with embedded systems for data warehousing, processing, and usage to provide 360O vision and
prevent collisions; (5) develop intelligent robot assistance in mining for safe operations in high-
temperature areas, areas with toxic and explosive gasses, or tight spaces for equipment
maintenance; and (6) create intelligent mine rescue and post-disaster surveillance for the emerging
ARI systems.
The PD and another Co-PI hold full-time academic positions in mining and explosives engineering
at S&T and NMT. S&T offers an ABET-accredited mining engineering program. It also offers
Master of Engineering (M.E.), Master of Science (M.S.), Doctor of Philosophy (Ph.D.) and Doctor
of Engineering (D.E.) in mining engineering. S&T also offers M.S. and Ph.D. degrees in
explosives engineering (https://mee.mst.edu/degrees/). One PI, from NMT, also holds a full-time
academic position in mineral engineering. NMT also offers an ABET-accredited undergraduate
and M.S. and Ph.D. degrees in mining engineering with research in explosives engineering
(https://www.nmt.edu/academics/index.php). S&T’s Experimental Mine and Explosives Research
Facilities, NMT’s Mining Research Facilities, and other research labs provide unparalleled
environments, and resources to undertake this initiative.
This initiative is a collaborative, multi-university, and multi-disciplinary effort that brings together
researchers from mining and explosives, electrical and computer, and mechanical and aerospace
engineering, engineering management and systems eng...

## Key facts

- **NIH application ID:** 10909777
- **Project number:** 5U60OH012685-02
- **Recipient organization:** MISSOURI UNIVERSITY OF SCIENCE & TECHNOLOGY
- **Principal Investigator:** Venkata Allada
- **Activity code:** U60 (R01, R21, SBIR, etc.)
- **Funding institute:** ALLCDC
- **Fiscal year:** 2024
- **Award amount:** $2,000,000
- **Award type:** 5
- **Project period:** 2023-09-01 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10909777

## Citation

> US National Institutes of Health, RePORTER application 10909777, Research and Technological Innovations in Automation, Robotics, and Intelligent Mining Systems for Transformative Improvements in Workplace Safety, Health, and Efficiencies (5U60OH012685-02). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10909777. Licensed CC0.

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