Intelligent Transportation Systems: Integrating AI, IoT and Predictive Analytics for Sustainable Urban Mobility

Steven Eppinger

Intelligent Transportation Systems: Integrating AI, IoT and Predictive Analytics for Sustainable Urban Mobility

Author(s)	Steven Eppinger
Country	United States
Abstract	Rapid urbanisation, increasing vehicle ownership, traffic congestion, air pollution, road accidents, and inefficient transportation infrastructure have created significant challenges for sustainable urban development. Intelligent Transportation Systems (ITS) offer an integrated technological approach to improving the efficiency, safety, accessibility, and sustainability of urban mobility. The convergence of Artificial Intelligence (AI), the Internet of Things (IoT), and predictive analytics enables transportation systems to collect real-time data, identify mobility patterns, predict congestion, optimise traffic flows, and support intelligent decision-making. This paper examines the role of AI, IoT, and predictive analytics in developing sustainable urban transportation systems. A qualitative and conceptual research methodology is adopted based on an analysis of existing literature concerning intelligent transportation, smart cities, connected mobility, artificial intelligence, Internet of Things, predictive analytics, and sustainable transportation. The study identifies intelligent traffic management, predictive congestion control, smart parking, public transport optimisation, predictive maintenance, intelligent routing, and emission management as major applications of integrated ITS. The proposed framework demonstrates that IoT infrastructure provides real-time mobility data, AI transforms data into intelligent decisions, and predictive analytics enables proactive rather than reactive transportation management. However, challenges including data privacy, cybersecurity, interoperability, infrastructure costs, algorithmic bias, digital inequality, and institutional fragmentation can restrict implementation. The study concludes that successful ITS deployment requires not only technological integration but also coordinated governance, reliable infrastructure, citizen participation, data-sharing standards, and sustainability-oriented transportation policies. An integrated AI-IoT-predictive analytics framework can significantly contribute to safer, cleaner, more efficient, and resilient urban mobility.
Keywords	Intelligent Transportation Systems, Artificial Intelligence, Internet of Things, Predictive Analytics, Smart Cities, Urban Mobility, Sustainable Transportation, Traffic Management, Connected Vehicles.
Field	Engineering
Published In	Volume 5, Issue 2, March-April 2023
Published On	2023-04-16

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American Journal of Advanced Multidisciplinary Research and Innovation

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Intelligent Transportation Systems: Integrating AI, IoT and Predictive Analytics for Sustainable Urban Mobility

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