Recent Advancements in Digital Management and Monitoring of Mine Waste: Sensors, Characterization, and Predictive Modeling-A Review.

Mining activities generate substantial volumes of solid waste materials during exploration and processing. These residuals pose environmental and geotechnical concerns due to their large spatial footprints and associated risks but may also contain potentially valuable resources. These characteristics highlight the necessity and opportunity of effective management and monitoring strategies. In recent years, a diverse range of technologies and methods have been applied to characterize mine waste compositions and analyze their spatial-temporal variability. These include remote sensing systems, ground-based sensors, and advanced data-driven methods. Despite the rapid advancement, the existing literature provides limited insight into the critical evaluation of how these techniques are applied in practice. This review systematically examines peer-reviewed journal articles published between 2021 and 2024 to highlight the state of the art in characterization, modeling, and monitoring techniques for mine waste. The review identifies recent trends, key gaps, advantages, and limitations of these techniques. The summary suggests that mining companies and research communities are increasingly adopting innovative technologies, transitioning from conventional methods to more sustainable practices. However, it also reveals ongoing challenges and persistent limitations. Further efforts, such as real-time monitoring capabilities, are required to achieve full implementation and integration across the industry and academia.