As part of the work, SAKURA-IIoT cloud platform (PaaS) and SAKURA-T cloud software (SaaS) based on it were developed and deployed.

Visualization and analysis of the operation of the elevator equipment made it possible to reduce the energy consumption of the elevator equipment by 8..10% due to the application of administrative and technical measures (optimization of SCADA settings of production management). Of course, the lack of automatic intelligent control and analysis of elevator operation did not ensure the achievement of the maximum effect from the use of IoT technologies.

The team received 100 GB of data on the operation of 65 units of equipment and 2,795 variants of technological routes of the grain elevator for almost three years of operation. These data included every second values of the electrical and technological parameters of the equipment.

The data needed to be organized, as certain data packages may have been missing before the SCADA modernization. Therefore, the team identified two main directions of work – the selection of data on the operation of technological routes, which contain the maximum complete set of parameters, and the selection of algorithms, according to which the neural network could give the best forecasting result.

It was decided to concentrate efforts in two directions:

1. Analysis of the operation of technological routes and forecasting the choice of the most
   optimal technological route.
2. Analysis of the operation of elevator equipment and prediction of equipment failure