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Overcoming Smart City Barriers Using Multi-Modal Interpretive Structural Modeling

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Abstract

Massive urbanization and resource scarcity are global phenomena for which researchers around the world see urban transformation into a smart city as the most viable solution. Yet urban planners face many hurdles in transforming cities. These include economic factors such as the high cost of infrastructure development and maintenance, social paradigms, governance, and environmental issues that limit government ambitions. To design an optimal strategy for creating a smart city, the various barriers must be identified and prioritized. The various barriers to the successful implementation of the smart city mission were identified using an extensive literature review and expert opinions. To understand the complex interdependencies among these barriers, the interpretive structural modeling method (ISM) was used. MICMAC analyzed the ISM model to classify the barriers. Indian cities vary greatly in terms of infrastructure, size, population, and available facilities. Therefore, the impact of the barriers and their interdependencies also vary. The author has extended the study and used the fuzzy approach MICMAC to improve the model by incorporating the variations observed when the city category changes. This study will help urban developers and planners to identify the relationship between barriers and design strategic planning to make the city smarter.

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Data Availability

Data available on request from the authors.

Code Availability

Code available on request from the authors

Notes

  1. https://www.financialexpress.com/money/smart-cities-are-all-about-sustainable-development/1303428/

  2. https://www.jagranjosh.com/general-knowledge/explained-classification-of-indian-cities-into-tiers-reason-categorization-and-other-details-1629375309-1

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Authors and Affiliations

  1. Amity School of Engineering and Technology, Amity University Uttar Pradesh, Uttar Pradesh, India

    Renuka Nagpal, Deepti Mehrotra & Rajni Sehgal

  2. Department of Mathematics and Computer Science, Brandon University, Brandon, R7A 6A9, Canada

    Gautam Srivastava

  3. Research Center for Interneural Computing, China Medical University, Taichung, 40402, Taiwan, Republic of China

    Gautam Srivastava

  4. Western Norway University of Applied Sciences, Bergen, Norway

    Jerry Chun-Wei Lin

Authors
  1. Renuka Nagpal
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  2. Deepti Mehrotra
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  3. Rajni Sehgal
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  4. Gautam Srivastava
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  5. Jerry Chun-Wei Lin
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Contributions

Renuka Nagpal: Conceptualization, Methodology, Software, Data curation, Validation, Investigation, Visualization, Writing – original draft. Deeptoi Mehrotra: Supervision, Conceptualization, Methodology, Investigation, Writing – review & editing. Rajni Sehgal: Supervision, Methodology, Validation, Writing – review & editing. Gautam Srivastava: Methodology, Validation, Writing – review & editing. Jerry Lin: Methodology, Writing – review & editing.

Corresponding author

Correspondence to Gautam Srivastava.

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For this type of study formal consent was not required. This manuscript does not contain any studies with human participants or animals performed by any of the authors.

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Nagpal, R., Mehrotra, D., Sehgal, R. et al. Overcoming Smart City Barriers Using Multi-Modal Interpretive Structural Modeling. J Sign Process Syst 95, 253–269 (2023). https://doi.org/10.1007/s11265-022-01751-w

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