Autonomous Drone Technology in Underground Mining: A Review of Current Trends and Future Directions

December 2024
Vol-11, Issue-1
Paper ID: 25584
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Science and Tech
Keywords
Autonomous Drones Underground Mining Real-time Mapping Environmental Monitoring Hazard Detection Maintenance and Inspection Sensor Technology Navigation Systems and Artificial Intelligence (AI).
Abstract
Autonomous drone technology has emerged as a transformative solution in the mining industry, particularly in addressing the complex challenges of underground mining. This review examines the integration of autonomous drones, highlighting current trends, diverse applications, and future directions. Key areas of focus include real-time mapping and surveying, ventilation and air quality monitoring, rockfall and hazard detection, and maintenance and inspection. Additionally, the review delves into the sophisticated sensors, advanced navigation systems, and robust communication technologies that underpin drone operations in subterranean environments. The discussion encompasses critical challenges related to safety, reliability, regulatory frameworks, and technological limitations. Looking ahead, the review identifies future directions emphasizing the integration of cutting-edge technologies such as artificial intelligence (AI) and enhanced sensor systems. By synthesizing insights from over 80 academic sources, this comprehensive review aims to guide researchers and practitioners towards innovative applications and effective solutions in the field of autonomous drones for underground mining.

Author Information

# Name Institute / Affiliation
1 Abubakar Hussaini Department of Computing Technology, SRM Institute of Science and Technology, India

How to Cite

Use the following formats to cite this article in your research.

APA Style
Hussaini, Abubakar (2024). Autonomous Drone Technology in Underground Mining: A Review of Current Trends and Future Directions. International Journal of Advance Research and Innovative Ideas In Education, 11(1), 899-913.
MLA Style
Hussaini, Abubakar. "Autonomous Drone Technology in Underground Mining: A Review of Current Trends and Future Directions." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 1, 2024, pp. 899-913.
IEEE Style
Abubakar Hussaini, "Autonomous Drone Technology in Underground Mining: A Review of Current Trends and Future Directions," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 1, pp. 899-913, 2024.
Vancouver Style
Hussaini Abubakar. Autonomous Drone Technology in Underground Mining: A Review of Current Trends and Future Directions. International Journal of Advance Research and Innovative Ideas In Education. 2024;11(1):899-913.
Harvard Style
Hussaini, Abubakar (2024) 'Autonomous Drone Technology in Underground Mining: A Review of Current Trends and Future Directions', International Journal of Advance Research and Innovative Ideas In Education, 11(1), pp. 899-913.
Chicago Style
Hussaini, Abubakar. "Autonomous Drone Technology in Underground Mining: A Review of Current Trends and Future Directions." International Journal of Advance Research and Innovative Ideas In Education 11, no. 1 (2024): 899-913.
Turabian Style
Hussaini, Abubakar. "Autonomous Drone Technology in Underground Mining: A Review of Current Trends and Future Directions." International Journal of Advance Research and Innovative Ideas In Education 11, no. 1 (2024): 899-913.

Export Citation

Related Research

A Deep Learning-Based Framework for Mood-Oriented Music Recommendation Using Facial Expression Analysis
Vaibhav Ashok Bhangare et al. 2026 Computer Engineering
PDF Unavailable
Survey On : Intelligent Payroll and Human Resource Management Systems: A Systematic Review of Automation, Security, and Analytics
Vishakha Jadhav et al. 2026 Human Resource Management, Artificial Intelligence, Machine Learning, Payroll Systems, Cybersecurity, Business Intelligence, Robotic Process Automation, Employee Analytics, Digital Transforma
PDF Unavailable
Civic Engagement & Empowerment Platform
Supriya Dadaso Bankar et al. 2026 Computer engineering
PDF Unavailable
RAG System Development with Pydantic AI ChromaDB & Groq
Prof. Priyanka P. Kakade et al. 2026 Computer Engineering
PDF Unavailable
Machine Learning Based Early Stage Diabetes Detection System
Rohan Mulik et al. 2026 Computer Engineering
PDF Unavailable
A Survey on Skillsense:AI Career Analyzer App
Kirti Datir et al. 2026 Computer Engineering
PDF Unavailable
Employee Performance Portal
P.Harika et al. 2026 Computer science and engineering
PDF Unavailable