AI technologies for generating digital models of territorial development

Introduction. Despite the unstable economic situation, the Russian housing construction market is showing record growth. Therefore, the accuracy and validity of the taken decisions become as relevant as the rate of territorial project development. Active development and implementation of artificial intelligence technologies in construction open up opportunities for an effective response to current challenges by automating digital models for the development of territories, taking into account many factors, as well as regulatory and economic parameters.

Materials and methods. The article examines the developed multi-stage method for generating digital models of territories for housing development. The method uses a chain of AI algorithms, including for generating linear and area objects, as well as optimal functional zoning of the territory. This solves problems related to the design of street and road networks and determination of the functional purpose for the formed quarters including capital construction facilities and related infrastructure.

Results. Experimental studies on the application of the developed generation method have demonstrated a 200-fold reduction in the labor intensity of conceptual design compared to the classical approach. This ensures the ultra-fast and accurate development of concepts and greatly accelerates the work on complex projects. The method has been successfully tested and implemented in the rTIM digital AI platform for territorial information modeling.

Conclusions. Further research in the field of algorithm optimization has the potential to expand the scope of application for AI technologies to solve development problems in both multi-apartment residential projects and other areas of the construction industry.

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