AI for Enhancing Urban Mobility and Lowering Carbon Footprints: An In-Depth Review of Various Approaches

Abstract

In an era of growing urbanization and environmental concerns, sustainable urban mobility solutions are more crucial than ever. As cities and populations increase, traditional transportation systems encounter hitherto unseen challenges like gridlock, inefficiency, and elevated carbon emissions. Addressing these intricate issues requires creative solutions that leverage cutting-edge technologies. This study examines how artificial intelligence (AI), the internet of things (IoT), and machine learning (ML) can simultaneously reduce carbon footprints and enhance urban sustainability. The multidisciplinary focus of this work encompasses organizational, technological, and energy perspectives, recognizing that effective solutions require a thorough understanding of the interconnected systems driving urban mobility. From an organizational standpoint, the integration of AI with IoT promotes collaboration among various stakeholders, including individuals, corporations, and governmental entities. Collaboration is key to developing frameworks and policies that promote sustainable mobility practices. Through the use of real-time data gathering and analysis enabled by the convergence of AI, IoT, and ML, cities may enhance their public transportation systems, optimize traffic management, and improve customer experience. With the use of these technologies, urban planners and transportation engineers may design more efficient networks that satisfy the needs of various populations while reducing their negative effects on the environment. Last but not least, implementing smart technologies can result in a notable decrease in carbon emissions from an energy standpoint. Cities can move toward a more sustainable future by boosting the development of renewable energy sources, encouraging the use of electric vehicles, and optimizing energy consumption in transportation systems. This review highlights the value of an interdisciplinary approach in tackling the problems of contemporary cities by shedding light on the synergies between AI, IoT, and ML in the context of urban mobility. We intend to add to the current conversation on sustainable urban development and stimulate creative solutions for a cleaner, more effective urban environment by thoroughly analyzing these technologies and their implications. In order to ensure that technological improvements support organizational and energy-related goals, this project aims to educate industry stakeholders, legislators, and urban planners on practical approaches to sustainable urban mobility. We draw attention to the difficulties and viewpoints of each approach.