Process Safety and Intelligent Monitoring for Mining Engineering

Dear Colleagues,

Mining engineering is inherently linked to exploitation of resources, ecological protection, and the safety of human lives and property. As shallow mine resources are progressively depleted, mining operations are extending to deeper strata, where extreme environments—characterized by high stress, elevated ground temperature, and high gas content—are increasingly prevalent. These conditions, compounded by the demands of intelligent transformation, pose significant challenges to traditional process safety management and monitoring methods: inefficient multi-source data integration, delayed disaster warning accuracy, and insufficient spatiotemporal resolution of sensing systems. Particularly in complex geological settings, hazards such as strata instability, surface subsidence, ground fissures, and landslides frequently result from mining activities. They result in a substantial increase in environmental remediation expenditure for mining areas. This not only restricts the sustainable development of the mining industry but also exacerbates ecological and social risks. Against this backdrop, the integration of process safety theory with intelligent monitoring technologies (such as big data, remote sensing, and artificial intelligence) has emerged as a critical strategy for achieving full-process dynamic perception, accurate assessment, and proactive prevention in mining operations. This shift towards a “prevention-first” safety management mode is essential for addressing the limitations of conventional approaches and ensuring the industry’s long-term sustainability. Relevant research in this area holds immense practical value for enhancing safe mining practices and mitigating the environmental and social impacts of resource extraction.

This Special Issue on “Process Safety and Intelligent Monitoring for Mining Engineering” aims to collect high-quality works focusing on the review, theoretical innovation, technological breakthroughs, and practical applications of process safety assurance and intelligent monitoring in mining engineering. Topics include, but are not limited to, the following:

• High-precision intelligent monitoring technology;
• Multi-source heterogeneous data fusion;
• Disaster mechanisms and prediction;
• Rock strata movement and control;
• Big data analysis for mine safety;
• Safety process control methods and optimization strategies;
• Intelligent equipment applications in mine safety.

Dr. Yanjun Zhang
Dr. Yueguan Yan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.