1931 Figure 7 – Web application developed for flyrock prediction and projectile database 3.2 Monitoring Component The capability to monitor and quantify actual flyrock events is a fundamental element of the framework. Van der Walt and Spiteri (2020) highlighted key limitations in existing measurement approaches used to validate prediction models, concluding that more accurate, reliable, and unbiased methods are required to precisely determine flyrock travel distances. McKenzie et al. (2015) further noted that continuous improvement of blasting practices represents a key preventative measure against flyrock, relying heavily on systematic video capture, secure storage, and structured analysis and classification of blast footage. The routine collection of data from flyrock events, even where no incident occurs, has been shown to significantly enhance the accuracy and robustness of existing predictive models (Zhou et al., 2024). The monitoring component ensures that each blast’s flyrock performance is observed and recorded in a consistent, reliable manner. Continuous monitoring is essential to detect flyrock occurrences that would otherwise go unnoticed and furthermore it also facilitates gathering data for analysis. The framework mandates systematic blast video capture for all blasts. In practice, this involves setting up high-speed or highresolution video cameras at strategic vantage points around the blast, at a safe distance. This includes the use of drones. Clear guidelines were developed for camera placement, field of view, and capturing criteria to maximize the chances of recording potential flyrock events. By codifying video monitoring for every blast, the framework moves away from an ad-hoc approach and also reduces reliance on subjective eyewitness accounts. It is a vital requirement for the measuring component of the framework. 3.3 Measuring Component The measuring component quantifies flyrock events by extracting data from the monitoring records. Essentially, it converts what is seen (or not seen) in the videos and field observations into actionable numerical information, such as how far fragments travelled and how that compares to predictions. Although traditional visual methods to analyze blast videos for flyrock are currently the most reliable method, it can be time consuming (Papillon, et al., 2018; Van Der Walt, 2019). As part of embedding the framework, blast performance analytics tools and services are also being evaluated and utilized by some of the mine sites to reduce post blast analysis time. Figure 8 are snapshots out of at least two trials done by the company to evaluate potential video analysis and monitoring services. Snapshot A is using BlastVision® (GroundProbe - Orica Digital Solutions, 2024), while snapshot B is using DetoVision® FlyRock (Eneax Core, 2026). Figure 8 - Blast performance analytics for flyrock projectile tracking
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