هوش مصنوعی برای خودمختاری شهری؛ به سمت شهر خودمختار اراک

ABSTRACT
Today, the use of data and data-driven solutions in urban planning and policy-making has been greatly welcomed by citizens and urban management. In this regard, industry and technology have taken steps to produce products under artificial intelligence at a remarkable speed to ensure the well-being of human life. As a result, the performance of cities may change if these tools are used in the fields of economy, society, environment, and governance. For this purpose, the current research was developed with the aim of artificial intelligence for urban autonomy. In terms of purpose, this research is applied, and in terms of nature and method, it is considered descriptive-analytical research. Documentary and field methods have been used to collect data. Then, based on the theoretical foundations and the Delphi method, the indicators, and variables affecting the autonomous city were extracted in the eight dimensions of governance, security, institutional, economic, decision support, environmental, technology, and supervision. In the second stage, it was analyzed using the mutual effects technique (structural analysis method), scoring, and in the MICMAC software environment, and the driving and key factors of the autonomous city were selected according to the score of influence and direct and indirect influence. The results indicate that the autonomous city system is a stable system, and the driving factors with impact, such as artificial intelligent delivery services, the creation of digital platforms, digital services, connected public transportation, and the creation of a large integrated national data center, have the most impact. Direct factors such as updating old systems, automating financial processes and detecting fraud, creating large integrated national data centers, installing sensors, and creating automation have the most indirect effect and are some of the main factors in the development of the autonomous city. The innovation of the present research lies in providing solutions that incorporate the use of artificial intelligence in managing cities, aiming to move them toward autonomy.
Extended Abstract
Introduction
Today, with the development of human societies and living standards, the need for efficient tools in social interactions and industry has been felt more than ever. In the last decade, citizens and urban management have greatly welcomed the use of data and data-driven solutions in urban planning and policy-making. In this regard, industry and technology have taken steps to produce products under artificial intelligence at a remarkable speed to ensure the well-being of human life. As a result, the performance of cities may change if these tools are used in the fields of economy, society, environment, and governance. For this purpose, the current research with the aim of artificial intelligence for urban autonomy has been developed for the autonomous city of Arak. In terms of purpose, this research is applied, and in terms of nature and method, it is considered descriptive-analytical research.
 
Methodology
The current research is applied in terms of purpose and descriptive-analytical based on its nature and method and relies on future research methods using quantitative and qualitative models. In this research, firstly, with a systematic and structural view, the review of the theoretical literature using the method of collecting documentary and library information in the field of using artificial intelligence in governance and urban management was discussed, then based on the theoretical foundations obtained and the indicators and the influential variables related to artificial intelligence in urban governance, eight dimensions (governance, security, institutional, economic, decision support, environmental, technology, supervision) were extracted. In the second stage, it was scored using the technique of mutual effects (structural analysis method) and analyzed in the environment of MICMAC software, and finally, the driving and key factors of the autonomous city were selected according to direct influence and effectiveness.
 
Results and discussion
According to the preliminary analysis in the field of MDI matrix features, it was found that the number of repetitions with the software proposal is considered 3 times, and the filling degree of the MDI matrix is 68.98%, which shows a high coefficient of influence of the variables on each other. It can be seen that the distribution and dispersion of variables affecting the use of artificial intelligence in the Arak metropolis is L-shaped and indicates the stability of the system, and four categories of variables are influencing factors, two-dimensional factors, dependent factors, and independent factors. They can be identified and separated.
 
Conclusion
Using the experts' Delphi questionnaire, 38 variables were extracted and analyzed using the interaction effects analysis model in Mic Mac software. The results show that key factors play a role in the future state of the realization of urban artificial intelligence in Arak metropolis. These important factors include artificial intelligent delivery services, the creation of digital platforms, digital services, connected public transportation, the creation of a large integrated national data center with the most significant direct impact, and factors such as updating old systems, automating financial processes, and detecting fraud. The large integrated national data center, the installation of sensors, and the creation of automation have the most significant indirect impact and are one of the main factors in the development of the autonomous city.
 
Funding
There is no funding support.
 
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved the content of the manuscript and agreed on all aspects of the work declaration of competing interest none.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
 We are grateful to all the scientific consultants of this paper.