In this paper, we consider the need to create an algorithmized digital platform for the development of electric charging networks of road transport and to optimize the load on the current power grid complex. In modern conditions, this platform can become an example of a mechanism for public-private partnerships and the development of environmentally friendly transport. The purpose of the platform is to provide users with up-to-date information about the state of the electric vehicle battery, reduce the cost of creating a network charging infrastructure for electric vehicle transport, automated resource accounting for power supply companies, and other services. The use of information technologies to combine the processes of economic relations in the field of energy sales services will attract funds for infrastructure development by increasing the load factor of generating capacities and unloading power centers. In the article, the authors propose a digital platform architecture using modern technologies such as IIoT, Vehicle to Grid (V2G), Machine learning, Big Data.

The research considers conducting orthogonal experiment (OT) as one of the stages in developing a new discrete element method (DEM) parameters calibration approach. The measured responses in experiment are the parameters obtained by DEM animation processing using machine vision system (MVS). The variable factors in experiment are DEM parameters. A brief overview of an existing calibration approaches given in the article. The choice of OT as a design of experiment tool among other mathematical tools discussed. Experiments conducted using specially developed rig where bulk material's flow captured as DEM animation. DEM animation converted to video and then processed using MVS that allow register the values of such parameters as angle of repose or expiration time (measured responses). The results of the OT show that it is possible to identify four measured responses with the most valuable correlation coefficient. DEM parameters with the biggest influence on the measured responses identified for each of the obtained regression. Obtained results are useful in learning or iterative algorithms development for DEM parameters calibration.

Today the industry is facing a shortage of skilled workers and an aging workforce, which will eventually lead to a loss of knowledge. But augmented reality technology can connect field workers with experts who are able to provide remote guidance in real time. The subsequent advantage is that the information obtained by AR devices can be used as accumulated successful experience in the future, which facilitates decision-making in specific business processes of the company. With AR, employees gain experience and skills much faster. This paper shows the application of augmented reality technology in the maintenance of electromechanical equipment. The main functions of the augmented reality system for servicing electrical equipment are presented, the solution to the problem of integrating an augmented reality software application with existing automation systems is shown, and the methods of interaction of the developed software module with third-party modules, for example, various analytical modules, etc. are described.