Year: 2025
Type: article
Abstract: Large urban areas generate vast amounts of data that pose challenges inaccessibility and understanding. To address these challenges, our study introduces an innovative framework for Interactive Data Exploration within Smart City Analytics, centering around user needs and experiences. By leveraging intuitive visualization techniques, we allow users to dynamically engage with urban data, facilitating better comprehension and interaction. The framework incorporates user feedback to refine the exploratory experience, thereby enhancing accessibility and usability. We conducted user studies to evaluate its effectiveness, which demonstrated marked improvements in user satisfaction and understanding when compared to conventional static visualizations. The approach not only enriches users' grasp of smart city dynamics but also fosters community engagement in urban planning initiatives. Our results underscore the crucial role of user-centered design in transforming complex data into accessible insights for stakeholders involved in urban development.
Authors: Xiang Li, Lucas Evans, Xinyi Zhang
Institution: Long Island University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409206265