Smart Cities and Data Science: Building Sustainable Urban Futures

Abstract

The concept of smart cities relies heavily on data science to optimize urban infrastructure and improve quality of life. This paper investigates how data-driven approaches, such as IoT sensor networks, traffic flow modeling, and energy consumption analytics, can contribute to sustainable urban development. By integrating data science with urban planning, environmental science, and social policy, we explore the potential of smart city technologies to address challenges such as congestion, pollution, and resource management. Case studies from Australian cities illustrate the benefits and challenges of implementing data science in urban planning. The paper emphasizes the need for interdisciplinary collaboration to create inclusive and sustainable smart cities.