Intelligent technologies in the evolution of electronic geodetic instruments: conceptual basis for the integration of artificial intelligence into spatial management systems and geoinformation environments

The article explores the issue of intellectualisation of electronic geodetic instruments in the context of spatial management systems, emphasising the transformation from automated procedures to adaptive self-learning technological solutions with the integration of digital ethics principles. An algorithmic analysis is implemented using the extended Kalman filter (EKF) and recurrent Long Short-Term Memory (LSTM) neural network architectures for adaptive filtering of information flows, as well as geospatial statistics and GIS visualisation methods for verifying coordinate consistency. The obtained scientific results indicate that intellectualisation determines the transformation to cognitive systems with sensor integration (GNSS, IMU, EDM), achieving millimetre accuracy using artificial intelligence algorithms – particularly EKF and LSTM – for predictive modelling of errors and auto-correction. It was established that cloud infrastructure and interoperability with GIS platforms (ArcGIS, QGIS) form a unified digital environment with data validation mechanisms, which increases metrological stability and ethical accountability of systems. The practical significance of the study is determined by the improvement of public administration systems, in particular urban planning, land cadastral accounting and infrastructure monitoring, where intelligent devices provide real-time data updates and preventive risk management. The study contributes to increasing the transparency of state registers through digital measurement passports, reducing errors and legal conflicts in the geoinformation environment. Prospects for further scientific exploration include the development of ethical standards for artificial intelligence in geodesy and integration with Internet of Things (IoT) technologies to establish global monitoring networks.