A Data-Driven AI Framework to Improve Urban Mobility and Traffic Congestion in Smart Cities

One of the most talked-about problems at the start of the twenty-first century is effective transportation, which is one of the numerous challenges the globe is experiencing. Technology is playing a critical role in helping to tackle the current transportation problems as smart cities evolve. Smart cities feature the modernized form of civilization worldwide as they leverage increasing technological advancement, including Artificial Intelligence, in running city initiatives alongside addressing urban challenges. Traffic forms a major challenge in urban development due to various factors, such as poor planning. The innovative approaches, exemplified by integrating shop and delivery options in smart cities, will alleviate traffic congestion challenges. This research study pinpoints the Actor-Network Theory (ANT) principles and pragmatism as the guiding approaches in the research and enhancing the integration. The data collection methods included in the research included interviews, reports, and media content essential for understanding the complex interrelations of smart city initiatives. As depicted in the data analysis, the ANT and pragmatic framework form the foundation of shaping the future urban landscapes.