AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Vibration and noise are among the most information-rich by-products of mining. Every blast, haul truck pass, crusher start-up, pump cycle, rockfall impact, and conveyor idler defect leaves a distinctive mechanical and acoustic fingerprint. This chapter develops a practical and scientific framework for monitoring vibrat...
A digital twin in mining is a dynamic, real-time virtual representation of physical assets and operational processes that supports predictive modeling, optimization, and decision-making. This chapter examines the architecture, data integration strategies, modeling approaches, and practical applications of digital twins...
Data analytics and artificial intelligence (AI) are transforming geotechnical monitoring by extracting insights from large sensor datasets. This chapter covers analytics objectives (trend detection, anomaly identification, and prediction) and data types (time-series, spatial, imagery, and point clouds). We discuss prep...
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