Smart Cities, Urban Finance, and Connected Public Service Ecosystems: A Framework for AI-Driven Smart Governance

Authors

  • C.V. Suresh Babu Department of Information Technology, Hindustan Institute of Technology and Science, Bay Range Campus, Padur, Chennai, India Author
  • Harish S Department of Information Technology, Hindustan Institute of Technology and Science, Bay Range Campus, Padur, Chennai, India Author
  • Srivarshan J Department of Information Technology, Hindustan Institute of Technology and Science, Bay Range Campus, Padur, Chennai, India Author
  • Lokeshwaran R Department of Information Technology, Hindustan Institute of Technology and Science, Bay Range Campus, Padur, Chennai, India Author

DOI:

https://doi.org/10.63503/aisem.59

Keywords:

Smart Governance, Urban Finance, Artificial Intelligence, Internet of Things, Fiscal Resilience, Digital Twin, Predictive Analytics, Sustainable Urbanism

Abstract

In order for cities to continue growing while at the same time integrating urban finance with a new breed of technology (e.g., AI and IoT), the connected intelligence model is quickly becoming the model with which cities can grow. This chapter proposes a governance framework based upon AI that will enable greater transparency, improved efficiency, and enhanced financial resilience. This white paper has moved away from traditional systems toward an innovative model based on data-driven practices, incorporating the citizen-consumer aspect of city services through strong public-private partnerships. In addition to addressing digital and cybersecurity divides, this research shows how predictive analytics and digital twins will enhance resource allocation practices. This research provides local/state and federal government officials with an outline for creating city environments that are inclusive, sustainable, resilient, and financially successful.

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Published

2026-10-25

Issue

Connected Intelligence in Finance & Public Services: Integrating AI, Big Data, and Digital Platforms for Smart Governance

Section

Articles