## 4 Discussion
### Future Trends  
Digitalization is a fundamental requirement for the mining industry's continued growth. Any mining company seeking to integrate into the current dynamic economic system and remain competitive must apply digital thinking to all of its processes, including mine tailings management [122]. To achieve this digital transformation, mining operations must know where they are and where they want to be; this will allow them to align their strategies with overall market trends and the mining sector. The incorporation of digital technologies is a priority to improve mining productivity and sustainability [123]. We also understand that this transformation process, which entails immersion in an environment of constant change and high uncertainty, is complex both culturally and technologically. This uncertainty can be managed through collaborative processes that allow the industry to address common problems and indicate how to foster the innovation ecosystem [124]. Mine tailings storage facilities are vulnerable to extreme hydrometeorological events resulting from global climate change, such as intense precipitation, frost, heat waves, snowfalls, and other events. This demonstrates how the implementation of sensor systems in TSF infrastructure allows for the real-time and online monitoring of various key operating parameters, granting operators greater safety control. Climate uncertainty and its effects on mine tailings storage facilities require these infrastructures to be resilient and have redundant monitoring systems to avoid failures, collapses, or spills of mine tailings. Adaptive measures to respond to climate change must be implemented, and solutions that incorporate digitalization technologies can help reduce the associated risks [22]. Sensors take two main types of measurements in mine TSFs, point measurements and spatial measurements, and there are currently uses for both types in the mining industry. Therefore, it is essential to define each of these types of measurements and the associated sensors that make them. For example, specific measurements that correspond to the local or specific study of the temporal variation in a particular parameter to be studied in a TSF are point measurements; these include (i) the water table (Casagrande and vibrating wire piezometers), (ii) the magnitude of precipitation (rain gauge), (iii) the flow rate of leaks from the TSF (dam drainage system gauge), and (iv) topographic surveying to enable the georeferencing of characteristic points of the terrain (drone with LiDAR system), among others. Spatial measurements are taken in an area of two or three dimensional space and consider the temporal variation in a specific parameter in a TSF, such as (i) the generation of a 3D model of the TSF with photogrammetry (drone with multispectral camera system), (ii) the estimation of 2D moisture content maps of TSF tailings (satellite image indices and processing), and (iii) 2D estimation of deformation and subsidence maps of the TSF dam (satellite images processed with InSAR), among others. Currently, the mining industry uses both types of measurements, mainly to achieve different purposes depending on the instrument's degree of precision, reliability, and cost-efficiency. Technological solutions that provide confidence are prioritized due to years of experience, and low-cost measures are preferred. Although important developments and advances have been made in sensors that take spatial measurements to monitor TSFs, there are still knowledge gaps and a lack of large-scale experiences that would increase these tools' precision, security, and reliability. In the coming decades, digital twins, augmented reality, computer vision, and AI technologies linked to the Industry 4.0 paradigm are expected to drive disruptive changes that will encourage the use of new spatial monitoring sensors that will replace existing point-measurement sensors.