Clarification of smart city criteria in order to reduce the effects of infectious diseases (case study of Tehran District 16 Municipality)

Eghbal, Sina; Eghbal, Nasim

doi:10.48306/jumee.2023.393195.1001

Clarification of smart city criteria in order to reduce the effects of infectious diseases (case study of Tehran District 16 Municipality)

Authors

Sina Eghbal ¹

Nasim Eghbal ²

¹ Department of urban planning, Faculty of art and architecture, The West Tehran Branch, Islamic Azad University, Tehran, Iran.

² Department of environmental engineering, Faculty of Technical and engineering, Science and research Tehran Branch, Islamic Azad University, Tehran, Iran

https://doi.org/10.48306/jumee.2023.393195.1001

Abstract

With the spread of the corona virus, smart cities were able to face and deal with the spread of this disease by using various types of digital technologies while providing the necessary services to citizens, by monitoring social distancing and home quarantine. In the meantime, the role of technology and the development of smart cities according to the crisis of infectious diseases became very important and the attention of governments and societies are attracted. The type of policy making and planning in the development of a smart city is different according to the local and regional conditions of each city, and it is an opportunity for municipalities to make changes in accordance with the goals of urban management and compatible with the needs of people and technological institutions. In this study, the main indicators that influence the policy of smart city development programs in order to manage and control the pandemic of infectious diseases, are collected and examined for Tehran Municipality. For this purpose, 25 different indicators were proposed and used for pairwise comparison of 3 main scenarios based on the Analytic Hierarchy Process (AHP). In total, the opinions of 20 experts in urban management in Tehran's 16th district municipality were used. According to the results, the second proposed scenario was chosen as the best option with a final score of 0.423. The effect of each criterion on each scenario was analyzed. Also, at the end, solutions for the development of smart city in Tehran are presented based on the results and suggested scenario.

Keywords

Tehran Municipality

Infectious Diseases

Smart City

Policy Making

AHP

1. Yin, C., et al., A literature survey on smart cities. Sci. China Inf. Sci., 2015. 58(10): p. 1-18. doi: 10.1007/s11432-015-5397-4

2. Kunzmann, K.R., Smart Cities After Covid-19: Ten Narratives. disP-The Planning Review, 2020. 56(2): p. 20-31. Doi:10.1080/02513625.2020.1794120

3. Inn, T.L., Smart city technologies take on COVID-19. World Health, 2020. 841.

4. Mouratidis, K., How COVID-19 reshaped quality of life in cities: A synthesis and implications for urban planning. Land Use Policy, 2021. 111: p. 105772. https://doi.org/10.1016/j.landusepol.2021.105772

5. Sharifi, A. and A.R. Khavarian-Garmsir, The COVID-19 pandemic: Impacts on cities and major lessons for urban planning, design, and management. Science of The Total Environment, 2020: p. 142391. https://doi.org/10.1016/j.scitotenv.2020.142391

6. Das, D. and J. Zhang, Pandemic in a smart city: Singapore’s COVID-19 management through technology & society. Urban Geography, 2021. 42(3): p. 408-416. https://doi.org/10.1080/02723638.2020.1807168

7. شاکری، ی.، کنکاشی بر فرصت ها و چالش های بیماری کرونا در محیط های شهری، دومین کنفرانس ملی مدیریت شهری، شهرسازی و معماری. 1399.

8. Anand, A., et al., Evaluation of sustainability indicators in smart cities for India using MCDM approach. Energy Procedia, 2017. 141: p. 211-215. https://doi.org/10.1016/j.egypro.2017.11.094

9. Zhu, S., D. Li, and H. Feng, Is smart city resilient? Evidence from China. Sustainable Cities and Society, 2019. 50: p. 101636. https://doi.org/10.1016/j.scs.2019.101636

10. Du, F., L. Zhang, and F. Du. Smart City Evaluation Index System: Based on AHP Method. in International conference on Big Data Analytics for Cyber-Physical-Systems. 2020. Springer. DOI: 10.1007/978-981-33-4572-0_81

11. شعبانی سیچانی، ن. و م. یزدانی، شهر و سلامت حمل ونقل در دوره ی ویروس کرونا, اولین همایش ملی تولید دانش سلامتی در مواجهه با کرونا و حکمرانی در جهان پسا کرونا. 1399.

12. جوان، ز. و ح. عامری سیاهویی، تاثیر بیماری کرونا بر روند تغییر سبک معماری و شهرسازی معاصر کلان شهرها(نمونه موردی تهران)، پنجمین همایش بین المللی عمران، معماری و شهر سبز پایدار. 1399.

13. پوراحمد و همکاران، شهر هوشمند: تبیین ضرورت ها و الزامات شهر تهران برای هوشمندی. نگرش های نو در جغرافیای انسانی (جعرافیای انسانی)، 1397. 10(2).

14. مشکینی، ا. و همکاران، تبیین راهبرد رشد هوشمند شهری در منطقه 19 کلان شهر تهران. هویت شهر، 1393. 8(20).

15. فرجی, ا., ز. یوسفی و م. علیان, تحلیل الگوهای رشد شهری با تأکید بر نظریه رشد هوشمند، مطالعه موردی، منطقه 22 کلان شهر تهران. معماری و شهرسازی پایدار, 1397، 6(1).

16. کنعانی مقدم, ث., و همکاران، تبیین رویکرد برنامه ریزی کاربری زمین شهری در شهر هوشمند با استفاده از روش پرامتی ( مطالعه موردی: منطقه 22 شهرداری شهر تهران). شهر ایمن, 1398، 6(2).

17. آزارش, م.ج., ارزیابی و تحلیل ارتقای کیفیت خدمات مدیریت شهری براساس زیرساخت های شهر هوشمند: مطالعه موردی: منطقه 13 شهرداری تهران, هفتمین کنفرانس ملی فناوری های نوین در مهندسی عمران، معماری و شهرسازی. 1399.

18. Saaty, T.L., Decision making—the analytic hierarchy and network processes (AHP/ANP). Journal of systems science and systems engineering, 2004, 13, p. 1-35. https://doi.org/10.1007/s11518-006-0151-5

19. Vahidi, H., et al., Fuzzy Analytical Hierarchy Process Disposal Method Selection for an Industrial State; Case Study Charmshahr. Arabian Journal for Science & Engineering (Springer Science & Business Media BV), 2014. 39(2). https://doi.org/10.1007/s13369-013-0691-1.

20. Padash, A., Modeling of environmental impact assessment based on RIAM and TOPSIS for desalination and operating units. Environmental energy and economic research, 2017. 1(1): p. 75-88. DOI: 10.22097/eeer.2017.46458

21. Chen, C.-H., A novel multi-criteria decision-making model for building material supplier selection based on entropy-AHP weighted TOPSIS. Entropy, 2020. 22(2): p. 259. https://doi.org/10.3390/e22020259

22. Erdogan, S.A., J. Šaparauskas, and Z. Turskis, Decision making in construction management: AHP and expert choice approach. Procedia engineering, 2017. 172: p. 270-276. https://doi.org/10.1016/j.proeng.2017.02.111

23. Chatterjee, P. and Ž. Stević, A two-phase fuzzy AHP-fuzzy TOPSIS model for supplier evaluation in manufacturing environment. Operational Research in Engineering Sciences: Theory and Applications, 2019. 2(1): p. 72-90.