Application of IoT and Automation in Mining Operations: Enhancing Safety, Productivity, And Environmental Sustainability in Smart Mining

Mining industries across the world are increasingly adopting digital technologies to address challenges associated with worker safety, operational inefficiency, and environmental degradation. Underground mining environments are particularly hazardous due to the presence of toxic gases, high temperatures, dust generation, poor illumination, and the possibility of roof falls and explosions. The integration of the Internet of Things (IoT), automation, wireless sensor networks, and cloud computing has emerged as a transformative solution for developing intelligent and sustainable mining systems. This research presents an IoT-based smart mining framework designed for real-time environmental monitoring, automated hazard detection, and operational control in underground mines. The proposed system utilises a Raspberry Pi 3 Model B+ integrated with MQ2 gas sensors, DHT11 temperature-humidity sensors, Light Dependent Resistors (LDR), ultrasonic sensors, and cloud-based monitoring platforms such as ThingSpeak. The system continuously measures methane concentration, temperature, humidity, and illumination levels while transmitting data to remote supervisors for continuous monitoring and analysis. Automated warning mechanisms including buzzers and LED indicators, are activated when hazardous conditions exceed permissible limits. The study demonstrates that IoT-enabled mining significantly improves worker safety, reduces response time during emergencies, enhances productivity, and minimizes environmental impacts through optimized energy consumption and predictive maintenance. Furthermore, the research highlights the environmental benefits of smart mining technologies, including reduced fuel consumption, lower greenhouse gas emissions, and improved resource utilization. The findings indicate that the integration of IoT and automation can support the transition toward sustainable and intelligent mining operations aligned with Industry 4.0 principles.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-17
DOI
https://doi.org/10.5281/zenodo.20258121
Primary Topic
Mining Techniques and Economics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Application of IoT and Automation in Mining Operations: Enhancing Safety, Productivity, And Environmental Sustainability in Smart Mining

Dipankar Mandal, Shyam Bihari Rathor, Dr. Ved Prakash Singh, Biswajit Mukherjee et al.
Zenodo (CERN European Organization for Nuclear Research)
Mining Techniques and Economics
article

Application of IoT and Automation in Mining Operations: Enhancing Safety, Productivity, And Environmental Sustainability in Smart Mining

Dipankar Mandal, Shyam Bihari Rathor, Dr. Ved Prakash Singh, Biswajit Mukherjee, Abhrajit Laha
article en

Abstract

Mining industries across the world are increasingly adopting digital technologies to address challenges associated with worker safety, operational inefficiency, and environmental degradation. Underground mining environments are particularly hazardous due to the presence of toxic gases, high temperatures, dust generation, poor illumination, and the possibility of roof falls and explosions. The integration of the Internet of Things (IoT), automation, wireless sensor networks, and cloud computing has emerged as a transformative solution for developing intelligent and sustainable mining systems. This research presents an IoT-based smart mining framework designed for real-time environmental monitoring, automated hazard detection, and operational control in underground mines. The proposed system utilises a Raspberry Pi 3 Model B+ integrated with MQ2 gas sensors, DHT11 temperature-humidity sensors, Light Dependent Resistors (LDR), ultrasonic sensors, and cloud-based monitoring platforms such as ThingSpeak. The system continuously measures methane concentration, temperature, humidity, and illumination levels while transmitting data to remote supervisors for continuous monitoring and analysis. Automated warning mechanisms including buzzers and LED indicators, are activated when hazardous conditions exceed permissible limits. The study demonstrates that IoT-enabled mining significantly improves worker safety, reduces response time during emergencies, enhances productivity, and minimizes environmental impacts through optimized energy consumption and predictive maintenance. Furthermore, the research highlights the environmental benefits of smart mining technologies, including reduced fuel consumption, lower greenhouse gas emissions, and improved resource utilization. The findings indicate that the integration of IoT and automation can support the transition toward sustainable and intelligent mining operations aligned with Industry 4.0 principles.

Zenodo (CERN European Organization for Nuclear Research)
Responsible consumption and production
Openalex Percentile: Top 7%
Mining Techniques and Economics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.