Proactive Service in the Housing and Utilities Sector as a Trend of Technological Development (In Russ.)

This research is dedicated to exploring the prospects of implementing proactive maintenance methods in the housing and communal services sector, relying on modern machine learning algorithms. Based on a review of contemporary scientific research on the topic, an analysis of existing solutions to prevent emergencies and reduce costs in the opera-tion of residential properties, as well as successful examples of implementing machine learning technologies in practice, opportunities for applying these technologies in predicting and preventing malfunctions have been identified. The main risks associated with the introduction of artificial intelligence in housing and communal services were also examined. This article delves into the role of machine learning algorithms in optimizing service processes and resource manage-ment, through the adoption of innovative approaches to create a more efficient and sustainable housing and communal infrastructure. It represents a significant contribution to understanding the development prospects of the housing and communal services sector, highlighting how machine learning technologies can enhance the efficiency of housing management, contribute to timely accident prevention, and improve citizens' quality of life. This material will be relevant for executives of managing companies and researchers interested in the implementation of innovative approach-es in managing housing and communal infrastructure.