THEORETICAL FOUNDATIONS OF ARTIFICIAL INTELLIGENCE APPLICATION IN THE "SAFE CITY" SYSTEM

This article explores the theoretical foundations of integrating artificial intelligence (AI) into the Safe City system. Key approaches to using AI to improve urban safety are examined, including monitoring, threat prediction, emergency management, and optimization of response resources. International experience in integrating AI into urban security systems is analyzed, identifying the advantages and limitations of such solutions. The role of theoretical models, machine learning algorithms, and big data analytics as the foundation for the functioning of smart city systems is emphasized.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-27
DOI
https://doi.org/10.5281/zenodo.18802843
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

THEORETICAL FOUNDATIONS OF ARTIFICIAL INTELLIGENCE APPLICATION IN THE "SAFE CITY" SYSTEM

Iminov Akbarjon Odiljonovich
Zenodo (CERN European Organization for Nuclear Research)
Smart Cities and Technologies
article

THEORETICAL FOUNDATIONS OF ARTIFICIAL INTELLIGENCE APPLICATION IN THE "SAFE CITY" SYSTEM

Iminov Akbarjon Odiljonovich
article en

Abstract

This article explores the theoretical foundations of integrating artificial intelligence (AI) into the Safe City system. Key approaches to using AI to improve urban safety are examined, including monitoring, threat prediction, emergency management, and optimization of response resources. International experience in integrating AI into urban security systems is analyzed, identifying the advantages and limitations of such solutions. The role of theoretical models, machine learning algorithms, and big data analytics as the foundation for the functioning of smart city systems is emphasized.

Zenodo (CERN European Organization for Nuclear Research)
Tashkent State University of Economics (UZ)
Sustainable cities and communities
Openalex Percentile: Top 49%
Smart Cities and Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.