Advancements in smart transportation: A data analytics approach for urban mobility

The rapid advancement of digital technologies has transformed urban governance, giving rise to Smart Cities that integrate e-Governance and smart transportation systems to enhance efficiency, sustainability, and citizen engagement. This thesis explores the intersection of e-Governance and smart transportation in the development of Smart Cities, focusing on how digital governance frameworks improve mobility management, public service delivery, and urban planning. The study examines key e-Governance technologies such as blockchain, artificial intelligence (AI), cloud computing, and big data analytics that facilitate real-time decision-making, traffic optimization, and digital public services. It also analyses smart transportation solutions, including intelligent traffic management, electric mobility, public transport digitization, and autonomous vehicles, which are essential for reducing congestion and promoting sustainable urban mobility.

Using a mixed-method research approach, the study investigates global case studies from leading Smart Cities such as Singapore, Amsterdam, and Barcelona, evaluating their policy frameworks, technological innovations, and governance models. The research identifies key challenges such as cybersecurity risks, data privacy concerns, interoperability issues, and infrastructure funding gaps that hinder the seamless integration of e-Governance and smart transportation. The findings suggest that a comprehensive digital governance strategy, coupled with public-private partnerships and citizen-centric policies, is crucial for the successful implementation of smart transportation solutions. This study concludes by proposing a strategic framework for policymakers and urban planners to enhance digital governance, optimize transportation systems, and build more resilient, efficient, and people-centered Smart Cities.