# Review of Transition from Mining 4.0 to Mining 5.0 Innovative Technologies
## 3 Review of the Transition from Mining 3.0 to 4.0
### Big Data in Smart Mining (Mining 4.0)  
The transition to Mining 5.0 will mean the displacement of a person by smart machines from intellectual work to engineering creativity, for which the concept of smart mining is already being implemented in Mining 4.0 today. It combines artificial intelligence capable of solving complex operational problems, modern telecommunication systems (means of storage and transmission of big data), and means of their ultrafast processing [84].  
In turn, the digital basis of smart mining is an analysis of big data, which allows for creating new knowledge without human intervention [85], integrating engineering, logistic, and economic information for managing the business cycle of minerals mining and processing [86], and adapting production volumes to changes in the world market of raw materials [87]. With regard to the operation of mining machines, cloud computing in the field of big data processing allows for optimizing their work with an increase in productivity of up to 30% [88].  
Analysis of big data helps to move to subsoils intelligent geological exploration. It significantly reduces the loss of minerals due to improved accuracy of geological mapping [89], which is critically important for the development of deep deposits, especially with occurrence anomalies [90]. For modeling future underground mine workings on other planets in the course of space exploration, big data analytics can help with the integration of knowledge and data obtained on Earth [91]. It can also be translated to the modeling of mining workings under the seabed, penetrated with autonomous underwater robots (for that purpose, the computational fluid dynamics method is recommended, along with using Tracsim and OrcaFlex digital instruments [92]. Relying on computational fluid dynamics model cells gave positive results in the analysis of methane inflow from coal array pores to workings to radically improve the effectiveness of mine ventilation [93].  
Big data in 3D modeling implementation in underground mine working design is based on point clouds obtained from various sources (ground penetrating radars, LiDAR scanners, etc.) and is of high relevance today (for example, digital speckle correlation is effective for predicting the strength characteristics of rocks in the composite roof in deep mines [94]). Virtual simulation with the construction of a fully functional interactive 3D model is successfully used in the analysis of the reliability of mineshaft structures [95].  
The combination of laser scanning technologies, big data analysis, and 3D modeling allows controlling unmanned vehicles in underground mine workings, avoiding accidents and collisions [96]. This, using machine vision, allows for creating adaptive 3D models of mine workings [97], including using simultaneous location and mapping (the precision of displaying details reaches 0.01 m) [98]. In turn, the Hermite radial basis function with  
Figure 9: Visualization of open pit mining using a 3D model built using smart sensors in real-time (Reprinted from Ref. [83]).  
spatial interpolation used for 3D modeling of ore deposits can significantly improve the accuracy of the calculation of mineral reserves [99] due to integrating geological maps, multispectral images, and magnetic surveys from drones [100].