Cognitive Digital Twin Technologies for Predictive Community Collaboration Data Driven Smart Decision Making and Next Level Urban Intelligence

M. SilpaRaj; O. Sathish; K. C. Rajeswari; K. Sivakumar; Kamal Kant Joshi; A. Buckshumiyan

doi:10.2991/978-94-6463-718-2_153

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Cognitive Digital Twin Technologies for Predictive Community Collaboration Data Driven Smart Decision Making and Next Level Urban Intelligence

Authors

M. SilpaRaj¹^{, *}, O. Sathish², K. C. Rajeswari³, K. Sivakumar⁴, Kamal Kant Joshi⁵^{, 6}, A. Buckshumiyan⁷

¹Assistant Professor, Department of Computer Science and Engineering (Cyber Security), CVR College of Engineering, Hyderabad, Telangana, India

²Assistant Professor, Department of Mechanical Engineering, Akshaya College of Engineering and Technology, Kinathukadavu, Coimbatore, Tamil Nadu, India

³Associate Professor, Department of CSE, Sona College of Technology, Salem, Tamil Nadu, India

⁴Professor, Department of Management Studies, J.J. College of Engineering and Technology, Tiruchirappalli, Tamil Nadu, India

⁵Professor, Department of Allied Science, Graphic Era Hill University, Dehradun, India

⁶Adjunct Professor, Graphic Era Deemed to Be University, Dehradun, Uttarakhand, India

⁷Associate Professor, Department of Mechanical Engineering, New Prince Shri Bhavani College of Engineering and Technology, Chennai, Tamil Nadu, India

^*Corresponding author. Email: silparajm@gmail.com

Corresponding Author

M. SilpaRaj

Available Online 23 May 2025.

DOI: 10.2991/978-94-6463-718-2_153 How to use a DOI?
Keywords: Cognitive Digital Twin; Smart Cities; Predictive Community Collaboration; Data-Driven Decision Making; AI in Urban Planning
Abstract: Modern cities are becoming denser and more complex and require innovative resolution pathways for effective decisions and sustainable urbanisation. The integration of Cognitive Digital Twin (CDT) technologies coupled with data-driven smart decision-making and predictive community collaboration opens an exciting new paradigm for next-level urban intelligence. This study investigates the incorporation of AI-augmented digital twins into urban planning, governance, and community engagement, while also advocating for data privacy, scalability, ethical AI, and computational efficiency in the implementation. This study proposes a novel approach on improving predictive analytics and adaptive policymaking in smart cities by utilizing real-time multi-modal data sources, decentralized AI frameworks, and participatory governance models. Highlights result in standardization of digital twin architectures, assurance of AI transparency, and collective decisions of sustainable urban ecosystem. This preliminary study lays the groundwork for cognitive urban intelligence development maintaining the equilibrium between technological, social, and moral interrogation.
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.

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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_153 How to use a DOI?
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

ris enw bib

TY  - CONF
AU  - M. SilpaRaj
AU  - O. Sathish
AU  - K. C. Rajeswari
AU  - K. Sivakumar
AU  - Kamal Kant Joshi
AU  - A. Buckshumiyan
PY  - 2025
DA  - 2025/05/23
TI  - Cognitive Digital Twin Technologies for Predictive Community Collaboration Data Driven Smart Decision Making and Next Level Urban Intelligence
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 1857
EP  - 1867
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_153
DO  - 10.2991/978-94-6463-718-2_153
ID  - SilpaRaj2025
ER  -

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