IOT-ENABLED SMART MINING: LEVERAGING REAL-TIME DATA ANALYTICS AND INFORMATION SYSTEMS FOR SUSTAINABLE MINERAL PROCESSING

Abstract

The rapid evolution of the Internet of Things (IoT) and data-driven technologies has ushered in a new era of innovation in the mining industry, where sustainability and efficiency are increasingly becoming strategic imperatives. This research explores the integration of IoT-enabled smart systems and real-time data analytics within the domain of mineral processing to address long-standing challenges such as resource inefficiency, high operational costs, and environmental degradation. The study investigates how interconnected sensing devices, automated control systems, and advanced information frameworks can collectively transform traditional mining operations into intelligent, responsive, and sustainable processes. Through the deployment of IoT sensors across mining equipment and processing plants, data related to machinery performance, ore quality, energy consumption, and environmental parameters can be continuously captured and analyzed. These insights enable predictive maintenance, optimized process control, and real-time decision-making, thereby reducing downtime and resource wastage. Furthermore, the research highlights the role of integrated information systems in harmonizing heterogeneous data streams into a unified decision-support platform. By employing advanced analytics, cloud computing, and machine learning algorithms, the proposed model facilitates dynamic monitoring of production efficiency and environmental impact across the mining lifecycle. Emphasis is placed on developing an adaptive framework that balances productivity with ecological responsibility, supporting circular economy principles and regulatory compliance. Case-based analysis demonstrates how smart mining technologies contribute to minimizing tailings, lowering carbon footprints, and enhancing worker safety through automation and remote operations. The findings suggest that IoT-driven smart mining not only promotes operational transparency but also serves as a foundation for sustainable mineral governance. The paper concludes that the integration of real-time analytics and intelligent information systems fosters a paradigm shift toward resilient, data-centric mining ecosystems. Such a transformation is essential for achieving long-term sustainability, economic viability, and technological competitiveness in the global mining sector. Future directions include exploring the interoperability of IoT platforms, enhancing cybersecurity frameworks, and scaling intelligent decision models for diverse geological and operational contexts.