نوع مقاله : علمی - پژوهشی
موضوعات
عنوان مقاله English
نویسنده English
Extended Abstract
Introduction
Smart cities are becoming one of the most satisfactory tools for policymakers seeking to achieve sustainable urban and regional development goals and achieve a better quality of urban life. Smart cities offer major solutions to reduce costs and solve urban problems, solve housing issues, traffic problems and prevent crime and crime caused by rapid urbanization. For this reason, smart cities are becoming one of the most satisfactory tools for governments seeking to achieve sustainable development goals, achieve a higher quality of life for citizens, improve government efficiency and create desirable participatory governance.
Methodology
The research has been of a quantitative type, it has been tried to analyze the intelligent transportation equipment in 15 areas of Isfahan metropolis by using the entropy model and the multi-indicator techniques of Critic and Mirca. In this research, a comparison has been made between the weighting method through the Shannon entropy model and the Critic weighting technique, and the weights obtained from these two models have been used in the Mirca technique. The data required for the study were collected from the Isfahan Metropolitan Statistical Office in 2023.
Results and Discussion
With the weight of the Critic model, using the Mirca technique and calculating the sum of the final values of the gap in the 11th district of Isfahan metropolis, it has obtained the highest score (0/0616). Region 10 with a score of (0/0243), region 5 with a score of (0/0252) and region 1 with a score of (0/0261) had a weak situation and obtained the lowest scores. With the weight of the entropy model, using the Mirca technique and calculating the sum of the final values of the gap in the 11th district of Isfahan metropolis, it has obtained the highest score (0/0632). Region 5 with a score of (0/0252), region 1 with a score of (0/0253) and region 10 with a score of (0/0282) have a weak situation and have obtained the lowest scores. The comparison of the scores obtained by the Mirca technique, whose weighting was based on Shannon's entropy model, shows more inequality between the 15 urban Regions of Isfahan.
The results of multi-interval spatial cluster analysis and K-function show that the score of the Mirca model for the indicators of intelligent transportation in the 15 regions of Isfahan city with the entropy model weight was scattered. The results of the multi-interval spatial cluster analysis of the Mirca multi-attribute technique for the indicators of intelligent transportation in the 15 regions of Isfahan metropolis with the critical model weight were scattered. The multi-interval spatial cluster analysis with the entropy model weight and the critical model weight shows a scattering pattern and no clustering is seen. The results of the group analysis show that 8 urban regions in Isfahan metropolis obtained weak scores in the field of intelligent transportation equipment and are in the red group and it is necessary to strengthen the indicators related to intelligent transportation equipment in them. Regions five, six, one, ten, three, four, seven, and eight are the main regions where intelligent transportation equipment should be the first priority in planning.
Conclusion
The rapid growth of urbanization in Iran's metropolises and large cities has created various problems due to the greater concentration of facilities in these cities. For this reason, urban planners consider smart cities as a tool to resolve these problems and obstacles in cities and improve the quality of urban life.
Key words: Smart City, Transportation, Isfahan Metropolis.
کلیدواژهها English
