Innovation science and technologiy 2-том 3-нөмір (2026)
A MODEL FOR DETECTING URBAN INFRASTRUCTURE PROBLEMS IN CITIZENS’ APPEALS BASED ON GEOLOCATION FEATURES
Mallayev, Oybek, Gazatov, Jamoliddin, Aliyev, Jaloliddin
Аңдатпа
This article proposes a model for identifying and classifying urban infrastructure problems based on geolocationdata derived from citizens’ appeals. The study extracts features from geolocation points submitted by citizens, includingtimestamps and movement parameters.Based on these features, methods have been developed for the automatic detection of issues such as traffic congestion,road damage, waste accumulation, and traffic signal malfunctions. The proposed model enables the classification ofurban problems using machine learning algorithms.The research results demonstrate that the use of geolocation-based citizen appeal data significantly enhances theefficiency of identifying urban issues and supports faster and more informed decision-making processes in urbanmanagement systems.
geo-map, machine learning, interactive services, GPS, NLP.
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