sensor network, reliable communication infrastructure, and calibration of site-specific threshold parameters. Variability in geological conditions may require localized adjustments to maintain system accuracy and minimize false alarms. In addition, the integration of the system into existing operational workflows represents a key challenge, particularly in ensuring consistent interpretation and response by underground personnel. While the system simplifies risk communication, its effectiveness ultimately depends on training and adoption at the operational level. From a techno-operational standpoint, further work is required to assess long-term performance, cost-benefit implications, and adaptability to different mining methods and depths. Future developments may include the incorporation of predictive analytics, machine learning techniques, and automated calibration methods to enhance system performance and reliability. These improvements would further support the transition toward fully predictive and adaptive geomechanical risk management systems. The zoning of maximum probable magnitude shown in Figure 4 highlights sectors with elevated seismic potential, supporting the definition of localized risk thresholds and preventive operational controls. Figure 2. Spatial distribution of recorded microseismic events at Level 2670 CR0600 (pilot area) prior to the application of magnitude of completeness (Mc). The dataset includes all detected events, showing dispersion and the presence of low-magnitude records that may affect statistical reliability. 65
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