Development of the real estate data processing model based on modern GeoAI approaches - Kobzan, Sergiy; Pomortseva, Olena; Pankiv, Volodymyr (Technology audit and production reserves, 2026)
The object of the research is geographic information systems (GIS) used in the real estate market. Currently, a significant problem in analyzing market information is the absence of a geographic component when evaluating property costs. This deficiency leads to a simplified understanding of market processes, reduces assessment accuracy, and complicates forecasting methods. During the research, system analysis and geostatistics methods were used to transform data from a discrete to a continuous form. Adding a spatial component to property information and updating data online allows for identifying pattern chains and creating forecast scenarios in the shortest possible time. A generalized scheme for processing large data sets was developed in combination with the GeoAI algorithm flowchart. This allows for developing a full-fledged model of a geographic information system with an adaptive artificial intelligence function, enabling users to rapidly process information for making investment decisions. The article analyzes modern GIS with artificial intelligence functions used to solve various global real estate problems. The proposed a scheme for processing large data sets with GeoAI, reflecting the general structure of interaction between GIS, input/output data arrays, and a neural network used for analyzing and predicting spatial processes. Practical calculations have shown that by using GeoAI, the time for processing large data sets is reduced by more than 10 times.