MODEL FOR EXTRACTING GEOLOCATION FEATURES AND INTEGRATING THEM WITH CITIZEN APPEAL PROBLEMS

Mallayev, Oybek, Gazatov , Jamoliddin, Aliyev, Jaloliddin

Al-Farg'oniy avlodlari · 2026-yil

Annotatsiya

This article proposes a model for identifying urban infrastructure problems in citizen appeals based on geolocation data. In the study, features are extracted from geolocation points, timestamps, and movement parameters submitted by citizens. Based on these extracted features, methods for automatically detecting issues such as traffic congestion, road damage, waste accumulation, and traffic light malfunctions have been developed. The proposed model classifies citizen appeals using geospatial clustering and machine learning algorithms. The research results demonstrate that the use of geolocation data enables the rapid identification of urban infrastructure problems and improves the efficiency of decision-making processes in urban management systems.

Maqola ma’lumotlari
MualliflarMallayev, Oybek, Gazatov , Jamoliddin, Aliyev, Jaloliddin
JurnalAl-Farg'oniy avlodlari
Nashr sanasi2026-03-18
Son1
Betlar235-240
TilRus

Kalit so‘zlar

geolocation, machine learning, geo-map, urban computing, GPS, DBSCAN, геолокация, машинное обучение, геокарта, GPS, urban computing, DBSCAN, geoxarita, geolokatsiya, mashinali o‘qitish, GPS, urban computing, DBSCAN

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