Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)

<Previous Article In Volume
Next Article In Volume>

Artificial Intelligence Driven Predictive Analytics for Real Time Civic Engagement and Smart Decision Making in Future Urban Governance

Authors
M. Silpa Raj1, *, P. Sambasiva Rao2, G. K. Monica Nandini3, S. Sureshkumar4, Amit Kumar Mishra5, 6, G. Saritha7
1Assistant Professor, Department of Computer Science and Engineering (Cyber Security), CVR College of Engineering, Hyderabad, 501510, India
2Associate Professor, Department of CSE, Sri Vasavi Institute of Engineering & Technology (SVIET), Nandamuru, Pedana, Krishna District, Andhra Pradesh, India
3Assistant Professor, Department of Civil, Sona College of Technology, Salem, 636005, Tamil Nadu, India
4Assistant Professor, Department of Electronics and Communication Engineering, J.J. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India
5Assistant Professor, Computer Science and Engineering, Graphic Era Hill University, Dehradun, India
6Adjunct Professor, Graphic Era Deemed to Be University, Dehradun, Uttarakhand, 248002, India
7Associate Professor, Department of ECE, Sri Sai Ram Institute of Technology, Chennai, 600073, Tamil Nadu, India
*Corresponding author. Email: silparajm@gmail.com
Corresponding Author
M. Silpa Raj
Available Online 23 May 2025.
DOI
10.2991/978-94-6463-718-2_16How to use a DOI?
Keywords
Data-driven urban decision-making; AI in Governance; IoT in Smart Cities
Abstract

The pervasive increase in urbanization and technology has so far-in the light of insufficient bureaucracy structure-meant administrators to work to rely on AI based predictive norms for prompt resolution of real-time civic engagement. Traditional smart city frameworks lean heavily on data but are mostly retrospective with regards to their intentions, guided primarily by linear systems predictive of the behavior of agents that do little to address interactive services without the explicit guidance of AI decision frames. This study puts forth a framework for AI-enabled governance that leverages predictive analytics, big data, and immediate feedback systems from citizens to improve transparency, responsiveness, and inclusivity in urban governance. Using machine learning algorithms, IoT integration, and sentiment analysis, this framework predicts governance challenges, optimizes resource allocation, and encourages sustainable urban development. The study also addresses ethical AI implementation, data privacy, and equitable participation concerns to ensure a fair and unbiased decision-making process. The emerging model effectively links AI-generated insights with smart urban decision-making, thereby helping policymakers in dealing with urban problems more effectively. Results are in line with the future-proof AI-based governance approach which will enable the easement of public service delivery, crisis management and sustainable urban infrastructure building.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series
Advances in Computer Science Research
Publication Date
23 May 2025
ISBN
978-94-6463-718-2
ISSN
2352-538X
DOI
10.2991/978-94-6463-718-2_16How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - M. Silpa Raj
AU  - P. Sambasiva Rao
AU  - G. K. Monica Nandini
AU  - S. Sureshkumar
AU  - Amit Kumar Mishra
AU  - G. Saritha
PY  - 2025
DA  - 2025/05/23
TI  - Artificial Intelligence Driven Predictive Analytics for Real Time Civic Engagement and Smart Decision Making in Future Urban Governance
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 170
EP  - 182
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_16
DO  - 10.2991/978-94-6463-718-2_16
ID  - Raj2025
ER  -