Abstract: The COVID-19 crisis has transformed the importance of smart cities, highlighting the vital role of Information and Communications Technology (ICT) in crisis management and post-pandemic life. Originally a branding strategy, smart city technologies are now essential infrastructure facilitating remote work and online interactions. This urgency has prompted urban planners… read more
DownScaleBench for developing and applying a deep learning based urban climate downscaling- first results for high-resolution urban precipitation climatology over Austin, Texas
Abstract: Cities require finer-scale climate information for resilient infrastructure development and adaptation planning, beyond standard climate analysis. Urban downscaling, a complex and computationally intensive process, involves generating detailed climate data for cities and neighborhoods from coarser sources. This study presents the ‘DownScaleBench,’ a novel deep learning approach facilitating urban downscaling… read more
Artificial Intelligence & Smart City Ethics: A Systematic Review
Abstract: Smart city technologies offer unprecedented capabilities to track urban residents with great precision, raising significant ethical concerns regarding privacy and safety. This systematic review gathers and categorizes existing literature on the ethics of smart cities. Authors conducted a keyword search across 5 databases, identifying 34 academic publications from 2014… read more
Forecasting Traffic Speed during Daytime from Google Street View Images using Deep Learning
Abstract: Traffic forecasting is vital for urban planning, with deep learning methods excelling in capturing traffic patterns. However, obtaining comprehensive historical data remains challenging, especially for city-wide predictions. To overcome this, we used SceneGCN, a deep learning approach, for city-scale traffic speed forecasting. This method involves extracting scene features from… read more
Quantitative Approach to Assess Social Equity in Road Networks
Abstract: This study addresses the need to quantitatively assess social equity in road network performance, a challenge often approached qualitatively in existing literature. By proposing a quantitative approach and exploring numerical measures, the study aims to provide objective assessments. The approach is applied to street networks in Seattle and New… read more
Testing the Capability of AI Art Tools for Urban Design
Abstract: This study examined three AI image synthesis models—Dall-E 2, Stable Diffusion, and Midjourney—for generating urban design imagery from scene descriptions. 240 images were evaluated using a modified Sensibleness and Specificity Average (SSA) metric by two independent evaluators. Results revealed significant differences among the AI models, with varying scores across… read more
Housing market price movements under tech industry expansion during COVID-19
Abstract: This study investigates the impact of technology-based corporation relocations on housing prices during COVID-19 in Austin, Texas, and Seattle/Bellevue, Washington, focusing on Tesla and Amazon. Using a difference-in-difference (DID) method, changes in housing prices near and away from the new corporate locations are analyzed within 5-mile and 10-mile radii.… read more
Identifying Hospital Deserts in Texas Before and During the COVID-19 Outbreak
Abstract: In our study, we utilized GIS to analyze hospital visitor data from January to June of 2019 and 2020, focusing on the impact of the initial COVID-19 wave. We found that while most demographic groups experienced shifts in visitor levels, American Indian and Pacific Islander groups sometimes showed no… read more
A scoping review of the benefits of face mask use on pedestrian and bicyclist exposure to air pollutants
Abstract: A growing body of research suggests that pedestrians and bicyclists are exposed to substantial levels of harmful air pollutants, including particulate matter and carbon monoxide, during their daily commutes. Disposable and cloth face masks are well-known personal interventions for pedestrian and bicyclist pollutant exposure. However, there is a lack… read more
The Impact of Peer-to-peer Ridesharing on Travel Mode: Empirical Study of Uber Effects on Travel Mode in Seattle
Abstract: Peer-to-peer ridesharing, as a new travel mode, could be a potential solution to two major transportation issues: congestion and air pollution by reducing inefficient driving and promoting public transit ridership. Uber, as one of the leader transport network company, launched in San Francisco in 2010 and expanded around the… read more
