The Role of AI in Urben Planning and Development

Background and objectives: The connection between artificial intelligence (AI) and urban planning is a burgeoning research area that has gained significant traction in recent years. Researchers have explored the potential of AI in various urban planning domains, including transportation planning, energy management, land-use planning, and building construction. One of the most prominent applications of AI in cities is traffic management. Researchers have developed systems that utilise sensors and computational units embedded in vehicles and road infrastructure to assess real-time traffic conditions on highways. Additionally, there are systems like C-Air leverage sensor data, the Internet of Things (IoT), and social media to predict traffic flow and propose management solutions. In the realm of environmental protection and air quality, AI plays a crucial role in monitoring and issuing alerts. Systems like C-Air employ microscopes and machine learning algorithms to analyse air quality and identify pollutants. These capabilities empower urban planners to create more sustainable and healthy cities. Energy management is another key area where AI finds application in cities. Utilising AI technology, researchers can predict electrical load and identify energy consumption patterns across different zones. Building characteristics, household size, and occupant demographics and the like are thus factored into these predictions. Similarly, AI-powered water management systems have the potential to detect leaks within distribution networks, thereby preventing water loss and promoting efficient water utilisation. Overall, the adoption of AI in smart city planning and management facilitates automated and intelligent decision-making across various domains. This not only enhances the quality of life for city residents but also contributes significantly to the sustainable development of urban environments. As such, this research aims to investigate the applications of AI in diverse urban planning domains and trace the evolution of this concept in previous studies.
Methods: This applied research utilises a two-pronged approach. First, a theoretical foundation is established by examining AI’s definition, applications in cities, and the challenges of integrating it into urban planning systems. This stage involves a descriptive analysis of relevant theoretical and empirical studies to understand the principles of AI-based urban development planning.
Second, a scientometric approach is employed using VOSviewer software. This method involves citation analysis and co-occurrence of keywords to identify the most prominent research areas related to AI and urban planning. The research population comprises 2337 articles on “artificial intelligence and urban planning” indexed in the ScienceDirect database, published from 1999 to the present. Analysis focuses on titles, abstracts, and keywords to generate a schematic representation of the research landscape.
Findings & Conclusion: The study delved into the intricate relationship between artificial intelligence (AI) and urban planning, drawing upon a comprehensive analysis of published literature. By examining 2337 articles indexed in the ScienceDirect database within the specified timeframe, the study identified six thematic clusters that profoundly impact AI’s role in shaping cities. The thematic clusters unveiled a remarkable shift in the research focus, transitioning from exploring AI’s fundamental concepts and mechanisms to embracing novel approaches for tackling urban challenges. The first cluster, encompassing the most frequently discussed keywords, highlighted pressing urban issues such as air pollution, transportation, resilience, and economic development, emphasising AI’s potential to revolutionize the digital landscape and urban environments. Overall, the identified clusters underscore the multifaceted applications of AI in urban planning, encompassing areas such as smart cities, data-driven planning, infrastructure management, citizen engagement, disaster management, and ethical considerations. These findings demonstrate AI’s transformative power in addressing critical urban challenges and promoting sustainable development. However, the study also underscores the need for careful consideration of AI’s ethical implications and the establishment of robust governance frameworks. This is crucial to ensure that AI is utilised responsibly and for the benefit of all urban residents. As cities and organisations embrace AI’s transformative potential, they must prioritise ethical practices, responsible data usage, and effective system management to maximise AI’s positive impact on urban planning and governance.