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Smart city article details

Title	Future Trends And Research Directions
ID_Doc	27553
Authors	Subrahmanyam S.
Year	2025
Published	Neural Networks and Graph Models for Traffic and Energy Systems
DOI	http://dx.doi.org/10.4018/979-8-3373-0290-4.ch014
Abstract	This chapter explores the transformative role of neural networks and graph models in optimizing traffic and energy systems within modern cities. As urban demands grow, advanced AI-d riven algorithms are essential for enhancing traffic management, incident prediction, and efficient energy distribution. The chapter reviews recent advancements, including convolutional neural networks, graph neural networks, and reinforcement learning, and discusses emerging challenges like data privacy, scalability, and the integration of IoT for real-time monitoring. Future research directions focus on quantum neural networks and sustainable urban planning, offering insights into developing resilient, efficient infrastructures for smart cities. © 2025, IGI Global Scientific Publishing. All rights reserved.
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