Abstract

Mining industry is rapidly transforming into an AI-driven cyber-physical ecosystem where safety and operational reliability depend on robust perception, resilient communication, trustworthy distributed intelligence and continuous monitoring of miners and equipment. Real-world mining environments impose severe constraints like poor illumination, dust, occlusion, GPS-denied conditions, irregular underground topologies, and intermittent connectivity. These factors degrade perception quality, disrupt situational awareness, impair trajectory prediction and weaken the reliability of distributed learning systems. Emerging cyber-physical threats, including backdoor triggers, sensor spoofing, label-flip attacks and poisoned model updates, further jeopardize operational safety, particularly as mines increasingly adopt autonomous vehicles, humanoid assistance, and federated learning for collaborative intelligence. Moreover, energy-constrained sensors experience uneven and unpredictable battery depletion, creating blind spots in safety coverage and disrupting hazard detection pipelines. This paper presents a vision for a Unified Smart Safety and Security Architecture that integrates multimodal perception, spatial-temporal modeling, secure federated learning, reinforcement learning, DTN-enabled communication and energy-aware sensing into a cohesive safety fabric. We detail five core modules: Miner-finder, Multimodal Situational Awareness, Backdoor Attack Monitor, TrustFED-LFD and IoT-driven Equipment Health Monitoring, addressing critical gaps in miner localization, hazard understanding, model integrity, federated robustness and predictive maintenance. Together, these modules form an end-to-end framework capable of detecting hazards, responding to disasters, guiding miners through obstructed pathways, identifying compromised models or sensors and ensuring the health of mission-critical equipment. By unifying these components, this work outlines a comprehensive research vision for building a futuristic, resilient, proactive and trustworthy intelligent mining system capable of safeguarding miners and maintaining operational continuity under extreme and adversarial conditions.

Department(s)

Computer Science

Comments

Centers for Disease Control and Prevention, Grant None

Keywords and Phrases

Distributed system; DTN communication; energy-aware sensing; machine unlearning; multimodal perception; post-disaster navigation; smart mining

International Standard Serial Number (ISSN)

2155-2509; 2155-2487

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2026 Institute of Electrical and Electronics Engineers, All rights reserved.

Publication Date

01 Jan 2026

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