Dhivya, S (2024) Optimizing Smart City Systems Using Artificial Intelligence Models. Optimizing Smart City Systems Using Artificial Intelligence Models, 20 (14). pp. 4285-4296. ISSN 1660-6795
Full text not available from this repository.Abstract
The increasing speed at cities are growing as well as the increasing requirement for sophisticated
usage of public assets has necessitated the development of smart cities, the capability of which
hinge on the availability of efficient and efficient communication networks. Hence, this research
focuses on applying deep learning methods such as LSTM, DQN, CNN and Autoencoders, and
GNN to incorporate AI in smart city communication networks. These methods solve important
problems such as predictive maintenance, traffic management, resource management, energy
consumption and data protection. LSTM predicts the failure of the infrastructures while DQN
manages traffic. Resource allocation at CNN is optimum, Autoencoders helps in improving security
of network, and GNN helps in scalability of IoT networks. Using AI as one of IoT and 5G, the
study also reveals the enhancements of urban sustainability, effectiveness, and reliability for smart
cities’ essential framework
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Machine Learning, Urban Infrastructure, Data Security, IoT, 5G, Smart Cities, and Communication Networks. |
| Divisions: | PSG College of Arts and Science > Department of Computer Science |
| Depositing User: | Dr. B Sivakumar |
| Date Deposited: | 17 Apr 2026 09:00 |
| Last Modified: | 17 Apr 2026 09:00 |
| URI: | https://ir.psgcas.ac.in/id/eprint/2803 |
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