The technology combines micro-vibration monitoring, risk assessment and digital-twin modelling to help identify potential rock-collapse hazards and improve mine safety management.
Developed and manufactured in South Korea, Do-it has developed a micro-vibration-based predictive safety management system designed to detect signals associated with rock deformation and stress changes that may precede large-scale collapse incidents in open-pit and underground mines.
The system uses proprietary micro-vibration sensors based on atomic clock technology, combining high-precision time-synchronization data, source-localization algorithms and artificial intelligence (AI)-based pattern analysis to identify vibration origins and quantitatively assess risk levels.
According to the company’s product information, micro-vibrations can arise not only from blasting activities but also from the accumulation of small-scale rock deformation and changes in underground stress. Monitoring these signals can help assess potential instability in mining environments.
The system integrates collected data into a digital-twin environment that provides a three-dimensional visualization of the mine structure, known as a 3D Digital Mine.
Its functions include predicting potential risk-propagation scenarios and automatically generating evacuation routes. The platform also supports analysis of work routes and operational efficiency, location-based safety management, worker and vehicle tracking, production and operations management, and environmental monitoring.
By bringing these capabilities together in a digital environment, the system is designed to support mine operators in monitoring rock stability, assessing potential hazards and coordinating safety and operational activities.
Windshear International Phil. Inc. is identified as Do-it’s Philippine local partner. The company lists Kurt P. Frankenberger as its contact for inquiries about the mining solution.
The system is presented as a technology option for both open-pit and underground mining operations, combining sensor-based monitoring and digital modelling in a single safety management framework.
