# 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
### Digital Twins in Mining 4.0  
Digital twins, as well as artificial intelligence, are an immanent part of mine's digital ecosystem [56], changing the role of humans in processes management, from the driver of automated machines (Operator 3.0 of remote control of partially robotic equipment) and further to Operator 5.0 (\"miner of the future\") [57], which uses biomechanical support, interact with collaborative robots, relies on augmented reality for the assistance of machinery engineers [58]. In general, the digital ecosystem of Operator 4.0 activity corresponds to the maturity of Digital 3.0 and, in perspective, 4.0 [59]. We highlight the difficulties in the unification and system integration of software made by many companies around the world as the limitation of digital twinning processes of mining. These difficulties are connected with the incomplete compatibility of software products developed by different vendors and composing the digital ecosystem of the modern mining enterprise. For example, widespread software--production solutions made by ABB, OSIsoft data integrators, asset management by IBM Maximo, cloud data management by Microsoft Azure, customer management by Microsoft Dynamics 365, and business analytics by Microsoft Power BI--communicate with each other using Microsoft Excel sheets only. It reduces the overall efficiency of the digital ecosystem of the enterprise [60]. In turn, we see overcoming the difficulties of integrating software into a single ecosystem in the formation of a unified approach to software compatibility by the majority of developers. In addition to cyber-physical systems, Mining 4.0 includes computer-integrated mining and smart mining, which quintessence is the use of integrated systems for design, management, equipment capacity, mining safety, and product quality monitoring [61]. The most important elements of digital ecosystems are smart sensors and digital twins. The latter is designed to balance the performance, synchronize data processing, and improve interface compatibility of various digital systems of mines--mobile devices, personal computers, and controllers [62]. Using digital twins of mining equipment and processes, different users (smart machines and humans) can stay connected and respond to unpredictable situations to avoid accidents (Figure 8) [63]. The digital twin also makes it possible to solve the problem of incompatibility of digital avatars of processes, requiring large and fast calculations [64], to reduce the number of physical prototypes [65]. Due to this, digital twins are used in mining and geological engineering process design by connecting all users to the enterprise information system [66]. Expanding the participation of digital twins in displaying results of big data analysis is possible using the BERT-BiLSTM CRF (conditional random field) neural network, which accelerates the recognition of problems with mining equipment more accurately and faster than autonomous smart sensors [67]. In general, the use of neural networks together with digital twins makes it possible to create digital clones of mining processes as close to reality as possible, during continuous self-learning of networks, for example, for optimizing resource and energy consumption [68]. Figure 8: The use of a digital twin in Mining 4.0 (Reprinted from Ref. [63]). In parallel with digital twins, the valuable part of Mining 4.0--a blockchain--is transforming into a cross-chain ecosystem that integrates information from different participants of subsoils mining and processing (extractive companies, electricity and heat producing firms [69], government regulatory authorities, insurance companies, and investors [70]). Distributed computing technologies (the basis of the blockchain) are used in forecasting methane appearance in coal mines.