Smart City Gnosys
Smart city article details
| Title | Responsible Artificial Intelligence Hyper-Automation With Generative Ai Agents For Sustainable Cities Of The Future |
|---|---|
| ID_Doc | 46129 |
| Authors | De Silva D.; Mills N.; Moraliyage H.; Rathnayaka P.; Wishart S.; Jennings A. |
| Year | 2025 |
| Published | Smart Cities, 8, 1 |
| DOI | http://dx.doi.org/10.3390/smartcities8010034 |
| Abstract | Highlights: What are the main findings? Smart Cities as Hyper-Connected Digital Environments generate large and diverse data streams and repositories that do not consistently translate into insights and decisions. A Responsible AI Hyper-Automation framework with Generative AI agents is developed and evaluated to address these complex challenges. What are the implications of the main findings? The developed AI framework is effective when grounded on five core technical capabilities with an independent cognitive engine for hyper-automated agentic AI that feeds into human-in-the-loop processes. The framework provides a prototypical setting for university cities of the future to provide direction, guidance, and standards for sustainable and safe smart cities of the future. Smart cities are Hyper-Connected Digital Environments (HCDEs) that transcend the boundaries of natural, human-made, social, virtual, and artificial environments. Human activities are no longer confined to a single environment as our presence and interactions are represented and interconnected across HCDEs. The data streams and repositories of HCDEs provide opportunities for the responsible application of Artificial Intelligence (AI) that generates unique insights into the constituent environments and the interplay across constituents. The translation of data into insights poses several complex challenges originating in data generation and then propagating through the computational layers to decision outcomes. To address these challenges, this article presents the design and development of a Hyper-Automated AI framework with Generative AI agents for sustainable smart cities. The framework is empirically evaluated in the living lab setting of a ‘University City of the Future’. The developed AI framework is grounded on the core capabilities of acquisition, preparation, orchestration, dissemination, and retrospection, with an independent cognitive engine for hyper-automation of these AI capabilities using Generative AI. Hyper-automation output feeds into a human-in-the-loop process prior to decision-making outcomes. More broadly, this framework aims to provide a validated pathway for university cities of the future to take up the role of prototypes that deliver evidence-based guidelines for the development and management of sustainable smart cities. © 2025 by the authors. |
| Author Keywords | artificial intelligence; generative AI; hyper-automation; smart cities; university city of the future |
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