Data-Driven Approaches to Urban Mobility

Sarah Okello Namusoke

Department of Computer Science Kampala International University Uganda

ABSTRACT

The advent of big data and advanced analytics is transforming urban mobility. This paper explores how data-driven approaches are enhancing urban transportation systems, focusing on data collection technologies, analytical techniques, and case studies of successful implementations. We review the integration of intelligent methods, such as neural networks, with urban data to create dynamic mobility solutions. Case studies from Helsinki and other cities highlight the practical applications and benefits of data-driven mobility strategies. The paper also discusses the challenges faced in implementing these solutions and suggests directions for future research to overcome these hurdles and fully exploit the potential of data-driven urban mobility.

Keywords: Urban Mobility, Big Data, Smart Cities, Neural Networks, Mobility as a Service (MaaS).

CITATION: Sarah Okello Namusoke. Data-Driven Approaches to Urban Mobility. Research Output Journal of Engineering and Scientific Research. 2024 3(1):67-70.