REINFORCEMENT LEARNING EMPOWERED DIGITAL TWINS: PIONEERING SMART CITIES TOWARDS OPTIMAL URBAN DYNAMICS
Aatmaj Amol Salunke
Department of Computer Science & Engineering, School of Computer Science and Engineering, Manipal University Jaipur
Smart cities have emerged as a promising solution to address the challenges posed by rapid urbanization and the quest for sustainable urban development. To achieve optimal urban dynamics and enhance the quality of life for citizens, there is a growing need for innovative approaches that integrate cutting-edge technologies. This paper introduces the concept of Reinforcement Learning Empowered Digital Twins as a pioneering strategy for smart cities. By combining the power of digital twin technology with reinforcement learning algorithms, cities can create dynamic, real-time virtual representations that mirror urban systems and interact with the physical world. This integration enables data-driven decision-making, efficient resource management, and optimized traffic flow, ultimately leading to reduced congestion, decreased fuel consumption, and improved air quality. The paper explores the potential applications of reinforcement learning empowered digital twins in various smart city domains, such as intelligent transportation systems, energy management, and urban planning, but mainly with respect to traffic flow and optimisation particularly in the state of Chhattisgarh and its prospects. Moreover, it identifies research gaps and discusses future directions to unlock the full potential of this transformative approach in pioneering smart cities towards optimal urban dynamics. Various scientists have been focusing on this and suggest further investigation and examination as a response and have given their own assessments; this paper essentially discusses, and overviews created by 5 articles, Machine learning approaches for smart city applications: Emergence, challenges and opportunities  by Sonam Mehta, Bharat Bhushan & Raghvendra Kumar; Applications of artificial intelligence and machine learning in smart cities  by Zaib Ullah, Fadi Al-Turjman, Leonardo Mostarda, Roberto Gagliardi; Enabling cognitive smart cities using big data and machine learning: Approaches and challenges  by Mehdi Mohammadi, Ala Al-Fuqaha; A survey on algorithms for intelligent computing and smart city applications  by Zhao Tong, Feng Ye, Ming Yan, Hong Liu, Sunitha Basod; The Reversible Lane Network Design Problem (RL-NDP) for Smart Cities with Automated Traffic  by L ConceiÃ§Ã£o, GHA Correia, JP Tavares.
Keywords: Smart Cities, Digital Twins, Reinforcement Learning, Intelligent Transportation Systems, Urban Dynamics, Traffic Flow Optimization, Energy Consumption Management
Journal Name :
EPRA International Journal of Research & Development (IJRD)
Published on : 2023-08-01