# Applications of Machine Learning and Computer Vision in Industry 4.0
## 2 Industry 4.0
### Roles of Intelligent Diagnostics in Industry 4.0  
The basis of the Industry 4.0 concept is the full use of interconnected cyber-physical systems equipped with artificial intelligence elements, which will be able to autonomously provide selected activities in production processes that were previously provided by humans. The principles of this concept can be applied to both industrial production and service provision [7].  
The development and implementation of automation and process control conceived in this way requires the development of new methods of automatic control. However, new tasks will also bring new challenges that can only be addressed by applying and developing the latest knowledge from a number of engineering disciplines: machine perception systems, intelligent sensing, intelligent human-machine and machine-to-machine communication, computer vision, machine learning, etc. New insights from these fields will enable modelling and subsequent replacement of human decision-making activities by machine activities [7].  
Artificial intelligence will play a key role in the new tasks and challenges. This discipline offers solutions that will be as efficient as possible, provide flexibility, be able to fully exploit shared data storage (cloud solutions) and fully exploit the concept of the Internet of Things.  
Artificial intelligence will play a key role in new tasks and challenges. This discipline offers solutions that are as efficient as possible, provide flexibility, are able to take full advantage of shared data storage (cloud solutions) and fully exploit the concept of the Internet of Things [8].  
The basic characteristics of control and decision-making systems in Industry 4.0 are their automated behavior with elements of artificial intelligence, openness, the ability to integrate into large-scale units, the ability to communicate intelligently with people and with each other, high security (protection of data and communications from cyber-attacks), and also the fact that they will be able to be remotely monitored, diagnosed and their activities managed [7].  
The goals of Industry 4.0 require the involvement and development of cyber practices and methods that will be applied in a wide range of industrial and societal practices. New practices in the automation of both industrial and societal processes, namely monitoring, control, decision-making, diagnostics, planning, etc., require research and development in the following areas, for example [7]:  
* Research and development of intelligent sensors providing information on the progress of production processes and monitoring essential parameters of the production process and products
* Development of methods and means of intelligent perception of the environment and tools for intelligent man-machine communication (computer vision, speech and language processing) and industrial machine-to-machine communication (e.g., wireless communication for mechatronic applications);* Research and development of methods for analysis of collected data to enable efficient management of production as part of the entire value chain (from input components/raw materials to maximum satisfaction of customer needs)--on-line and off-line processing of large-scale data (\"big data,\" e.g., for the purpose of fast information retrieval and knowledge extraction, for the field of technical diagnostics--identification of atypical behavior, fault prediction, etc.)
* Research and development of artificial intelligence methods and their application in the development of advanced methods for automated decision-making, control, diagnosis and monitoring in areas of technical and social practice  
Applied research in AI is therefore crucial to the application of Industry 4.0 ideas--the results from these areas are literally the foundation of all Industry 4.0 solutions. Therefore, this part of research can be considered a priority, indispensable and indisputable [7].