The number of Russian companies that develop hybrid solutions for AI and IoT is approaching zero in spite of their pretty simple technical implementation. Such a point of view expressed CEO at PTC Russia Andrey Sholokhov who will take part in the AI Conference panel discussion. In our flash interview, Andrey shared his opinion on the difference between Russian and Western IoT solutions as well as difficulties of the development of hybrid products in AI+IoT sphere.

Let’s compare the quality of hybrid solutions in AI and IoT sphere in Russia and Western countries, which are better?

It would be a subjective comparison. Notwithstanding, we can single out the key differences in IoT analytics solutions provided by the U.S., Western Europe, partly Asian countries and Russia.

  • Higher popularity of industrial tools (used by dozens or even hundreds of clients across the globe) compared to DIY solutions.
  • More widespread use of publicly available cloud technologies for data storage and processing.
  • More experience (both successful and negative) in conducting such projects.

Who are the first to benefit from such solutions?

Projects related to IoT analytics are first of all useful to enterprises that deal with projects in the sphere of lean production and practice Six Sigma using IoT tools. Recently, such a direction has been titled ‘Digital Lean’.

Could you provide an approximate percentage of AI+IoT solutions implementation into Russian companies?

The number of such companies is approaching zero. We would probably find some amateurish or Russian system of equipment monitoring, but tasks related to machine learning or statistical analysis are performed in a hurry and in fact appear to be individual projects.

Is it more difficult to develop hybrid AI+IoT solutions in comparison to ones based on a single technology?

From a technical point of view, projects based on both the Internet of Things and machine learning are not that complex. The point is that the interface between these technologies is normalized data collected by IoT tools and then analyzed by AI.

The only possible technical problem may arouse when you have to build an analytic model using current, not recorded data. Notwithstanding, such cases are rare. We currently have industrial tools capable of providing such functionality.

I would rather describe the complexity of the two technologies as ideological. Creators of systems for equipment monitoring strive to develop ultimate solutions. Such solutions can show business owners essential aspects that are to be eliminated. The ways of its implementation may include process suspension and changeover.

Does the state assist in the development of these technologies? If it doesn’t, what help would you appreciate?

It doesn’t. It would be much helpful if state officials understand not only the advantages of emerging technologies but also considerable limits of their application. I would also appreciate if they elaborate realistic expectations from innovation application.