Eco-Cognitive Mining Systems (ECMS): A Foundational Framework for Self-Aware, Adaptive, and Sustainable Mining Operations
Maaz A. Ali *
Geological Research Authority of Sudan, Ministry of Minerals, Khartoum, Sudan and Saudi Mining Polytechnic, Arar, Saudi Arabia.
*Author to whom correspondence should be addressed.
Abstract
The mining industry faces growing pressure to meet global resource demands while adhering to strict environmental, social, and governance (ESG) standards. Existing frameworks in Mining 4.0 largely focus on digital transformation but lack environmental self-awareness and adaptive sustainability control. This study introduces the Eco-Cognitive Mining System (ECMS), a novel paradigm that integrates Cognitive Equilibrium and Smart Environmental Calibration (SEC) within a unified cognitive control architecture. ECMS allows mines to perceive environmental changes, reinterpret operational objectives, and autonomously adapt across the production lifecycle.
A quantitative simulation comparing ECMS against a baseline fixed-control system demonstrates substantial improvements: an 85% reduction in emission violations, improved safety stability, and lower operational costs. The results validate ECMS as a foundational framework for Mining 5.0, where intelligent autonomy and sustainability coalesce to form self-aware, adaptive, and ecologically balanced mining ecosystems.
Keywords: Eco-cognitive Mining System (ECMS), cognitive sustainability, mining 5.0, adaptive environmental control, digital twin, artificial intelligence, sustainable mining, Smart Environmental Calibration (SEC), Cognitive Equilibrium Engine (CEE), self-aware industrial systems