Artificial intelligence possibilities for the Arcona ecosystem development

The Arcona Ecosystem is a revolutionary product created at the edge of the most advanced and fast-developing technologies of augmented reality and blockchain. However, describing the whole project, it would be wrong not to mention other technologies — and better say branches of science — leveraged.

We are talking about artificial intelligence due to which the very idea of the Digital Land layer becomes implementable.

Artificial intelligence used to be associated with the robots inevitably conquering the world and destroying the humanity. In fact, that is not what this branch of computer science deals with. Well, at least not only.

Basically, it aims to create devices and software enabling to reproduce or simulate the thought and creative processes which the human intelligence is capable of. The core problems of artificial intelligence include programming for certain traits, like self-learning, knowledge engineering, etc. Keeping in “mind” an enormous volume of data and being able to close the knowledge gap with the help of human-like capacities like common sense, analysis, imagination, reasoning, and problem-solving power that is what artificial intelligence more about. It has become an essential part of the technology industry. Research associated with artificial intelligence is highly technical and specialized.

What all this has to do with Arcona?

Arcona is a global ecosystem that will provide millions of end-users with simple and affordable tools for launching authorial AR projects around the world. The ecosystem will be built around a unique technological platform that automatically generates a layer of augmented reality — the Digital Land — anywhere in the world. The most important part of this layer is a set of navigation markers linked to the corresponding locations in the physical world. These markers provide precise remote placement of interactive content and proper displaying of it on the user devices. So, in general, we don’t deal with global replication of the whole Earth surface. To implement our Digital Land layer, we need only to collect and store a number — and a really huge number — of those spatial markers for navigation and remote positioning. This task is less comprehensive and resource intensive.

At the same time, currently existing software solutions can’t provide the required degree of robustness, stability and precision for processing of supposed input data that is represented mostly (but not only) by various images.

So, several core parts of the Digital Land platform are based on our own original know-how algorithmic solutions, in the fields of AI, computational geometry and surface reconstruction, using, as a particular multi-layer convolutional neural networks.This has been possible because of significant investments made by the technology company behind the Arcona project Piligrim XXI in the research of computer vision and artificial intelligence too — besides GIS distribution, AR techs, and 3D simulation.

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