Crossref DOIMemberCiteFactoropen accessissn
SJIF Impact Factor 8.659 | ISSN: 2582-3930
IJSREM Logo

International Journal of Scientific Research in Engineering and Management

(Gateway to Global Scholars - An International, Scholarly, Multi-Disciplinary, Open Access Journal)

Peer-Reviewed Journal Designed to Meet UGC's Quality Parameters

HomeCurrent IssuePast IssuesPay OnlineConferencesEditorial BoardAbout UsContact Us
IJSREM

Loading article...

Follow Us

  • Google Scholar
  • ResearchGate
  • Academia.edu
  • Mendeley
  • LinkedIn
  • Facebook
  • Instagram

Journal Policies

  • Peer Review Policy
  • Publication Ethics
  • Copyright Infringement
  • Refund & Cancellation Policy
  • Terms and Conditions
  • Privacy Policy

Journal Identifiers & Licenses

  • ISSN Verified: 2582-3930ISSN Verified: 2582-3930
  • Crossref DOI: 10.55041Crossref DOI: 10.55041
  • SJIF Ranking: 08.659SJIF Ranking: 08.659
  • Licensed under CC BY 4.0Licensed under CC BY 4.0
  • ISO Certification: 9001:2015ISO Certification: 9001:2015
  • Indexed & Cited In: Google ScholarIndexed & Cited In: Google Scholar

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

#62/1, New No 7, 1st Cross, 2nd Main, Ganganagar, R T Nagar, Bangalore North, Bangalore, Karnataka, India – 560032
[email protected]+91 93911 67991
logos
logos
Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 10:00 AM – 4:00 PM

+91 93911 67991

© 2026 IJSREM – International Journal of Scientific Research in Engineering and Management. This is an open-access journal. Articles are published under the Creative Commons Attribution (CC BY 4.0) License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

DisclaimerPrivacy PolicyTerms and Conditions
ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM62210

Intelligent Urban Transformation Using AI-Enabled Predictive Modeling and Data-Driven Planning Strategies

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM62210

Volume:

10 |

4 |

April 2026

Pages:

1-6

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM62210

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

Share this article:

Authors

MS

M. Sowmya

Amity Institute of information Technology

Amity university Raipur Chhattisgarh

Download Author Certificate
k

k.Megha

Amity Institute of information Technology

Amity university Raipur Chhattisgarh

Download Co-Author Certificate
DC

Devika Chowdhary

Amity Institute of information Technology

Amity university Raipur Chhattisgarh

Download Co-Author Certificate
Gv

Gulshan verma

Amity Institute of information Technology

Amity university Raipur Chhattisgarh

Download Co-Author Certificate
MK

Mahima Kumari

Amity Institute of information Technology

Amity university Raipur Chhattisgarh

Download Co-Author Certificate
ST

Shikha Tiwari

Amity Institute of information Technology

Amity university Raipur Chhattisgarh

Download Co-Author Certificate

Author Services & Downloads

Full ArticlesAcceptance Certificate

Abstract

The increase in rapid urbanization has created complex challenges that city planners must deal with. Examples of these challenges are traffic control, resource distribution and environmental sustainability. This-research paper proposes an AI-powered predictive framework utilizing machine-learning technology and real time data to predict future trends related to urbanization and assist virtual decision-makers through improved knowledge of their city environment. For example, this system uses data related to population growth, traffic flows, and environmental conditions for analytical purposes to detect changes that could lead to problems and provides strategic alternatives to address those issues before they occur. The system also integrates with GIS technology for improved visualization, spatial planning, and enhanced accuracy in locating and defining features associated with urbanization and city planning. This study shows that the use of AI-powered predictive intelligence provides increased efficiency, lower costs, and supports sustainable urban development; therefore contributes to the development of smart and resilient cities worldwide.

KEYWORDS

Keywords Artificial Intelligence Big Data Analytics Data Preprocessing Decision Support System Geographic Information Systems (GIS) Machine Learning Predictive Intelligence Smart Cities Sustainable Urban Development Urban Planning.

Cite This Article

M. Sowmya, k.Megha, Devika Chowdhary, Gulshan verma, Mahima Kumari, Shikha Tiwari, "Intelligent Urban Transformation Using AI-Enabled Predictive Modeling and Data-Driven Planning Strategies," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, pp. 1-6, April 2026. https://doi.org/10.55041/IJSREM62210

Full Article/Conclusion

According to the results of the proposed model framework supports successful predictive urban planning, but it is also highly affected by the quality and availability of the underlying data. Accuracy of prediction for examples where incomplete or inconsistent data is available will suffer. That being said, the model's performance is promising for actual use in the development of smart cities.[19]

References

[1] M. Batty, The New Science of Cities. Cambridge MA USA MIT Press 2013 Publisher: MIT Press 2013. [2] C. M. Bishop, Pattern Recognition and Machine Learning. New York NY USA Springer 2006 Publisher: Springer 2006. [3] T. M. Mitchell, Machine Learning. New York NY USA McGraw-Hill 1997 Publisher: McGraw-Hill 1997. [4] J. Han, M. Kamber, & J. Pei, Data Mining: Concepts and Techniques Third (3rd) Edition. Burlington MA USA Morgan Kaufmann 2011 Publisher: Morgan Kaufmann 2011. [5] Kitchin, R. (2014). The real-time city? Big data and smart urbanism. GeoJournal, 79(1), 1-14. [6] Zanella, A., Bui, N., A. et al. (2014). Internet of Things for smart cities. IEEE Internet of Things Journal, 1(1), 22-32. [7] M. Goodchild, Geographic information systems and science, International Journal of Geographic Information Science, 26(4), 571-580 2012. [8] Santana, E. F., et al., Software platforms for smart cities: concepts and challenges, IEEE Communications Magazine, 55(3), 32-39, 2017. [9] Nosratabadi et al. 2019, H., S., B., P. & Y., Z. State of the art survey of machine learning for smart cities, Sustainable Cities and Society, vol. 49, 101-110.  [10] Z. Yan et al., (2023). Intelligent urbanism with artificial intelligence in smart cities. Journal of Cloud Computing, 12, 179.

Editorial & Review Transparency

Publication Date

5/1/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

Documents

Review Report (Confidential)
Copyright Form (Office)

Article Metrics & Impact

Article Views

0

Total views since publication

PDF Downloads

3

Total downloads since publication

Geographic Reach

5

Indexing, Archiving & Preservation

Google Scholar
Academia
ResearchGate
Crossref
SSRN
Semantic Scholar
Thomson Reuters
WorldCat
Mendeley
OpenAlex
EBSCO
Zenodo

Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.

Ethics, Compliance & Transparency

Plagiarism Screening

This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.

Conflict of Interest

The authors declare no conflict of interest related to this research work.

Funding Information

No funding information available for this research.

Similar & Recommended Articles

Similar Articles by Topic

Related research in the same subject area

Loading similar articles...