[HTML][HTML] Street view imagery in urban analytics and GIS: A review
Street view imagery has rapidly ascended as an important data source for geospatial data
collection and urban analytics, deriving insights and supporting informed decisions. Such …
collection and urban analytics, deriving insights and supporting informed decisions. Such …
Automatic number plate recognition (ANPR) in smart cities: A systematic review on technological advancements and application cases
Abstract Automatic Number Plate Recognition (ANPR) technology has been intensively
engaged in managing the smartification and digitalization of cities in recent years as an …
engaged in managing the smartification and digitalization of cities in recent years as an …
Crowdsourcing bridge dynamic monitoring with smartphone vehicle trips
Monitoring and managing the structural health of bridges requires expensive specialized
sensor networks. In the past decade, researchers predicted that cheap ubiquitous mobile …
sensor networks. In the past decade, researchers predicted that cheap ubiquitous mobile …
Analysis of the implementation of urban computing in smart cities: A framework for the transformation of Saudi cities
Smart city development is gaining widespread acceptance as a means of mitigating urban
development problems. However, the implementation of smart cities faces challenges …
development problems. However, the implementation of smart cities faces challenges …
Mobile monitoring of urban air quality at high spatial resolution by low-cost sensors: impacts of COVID-19 pandemic lockdown
S Wang, Y Ma, Z Wang, L Wang, X Chi… - Atmospheric …, 2021 - acp.copernicus.org
The development of low-cost sensors and novel calibration algorithms provides new hints to
complement conventional ground-based observation sites to evaluate the spatial and …
complement conventional ground-based observation sites to evaluate the spatial and …
Hyperlocal environmental data with a mobile platform in urban environments
Environmental data with a high spatio-temporal resolution is vital in informing actions toward
tackling urban sustainability challenges. Yet, access to hyperlocal environmental data …
tackling urban sustainability challenges. Yet, access to hyperlocal environmental data …
[HTML][HTML] Combining Google traffic map with deep learning model to predict street-level traffic-related air pollutants in a complex urban environment
Background Traffic-related air pollution (TRAP) is a major contributor to urban pollution and
varies sharply at the street level, posing a challenge for air quality modeling. Traditional land …
varies sharply at the street level, posing a challenge for air quality modeling. Traditional land …
Tools and methods for monitoring the health of the urban greenery
Urban greenery supports cities in achieving Sustainable Development Goals, but it is
increasingly affected by multiple stressors impacting its health. Owing to the high costs of …
increasingly affected by multiple stressors impacting its health. Owing to the high costs of …
Key Themes, Trends, and Drivers of Mobile Ambient Air Quality Monitoring: A Systematic Review and Meta-Analysis
Mobile ambient air quality monitoring is rapidly changing the current paradigm of air quality
monitoring and growing as an important tool to address air quality and climate data gaps …
monitoring and growing as an important tool to address air quality and climate data gaps …
Networks and long-range mobility in cities: A study of more than one billion taxi trips in New York City
We analyze the massive data set of more than one billion taxi trips in New York City, from
January 2009 to December 2015. With these records of seven years, we generate an origin …
January 2009 to December 2015. With these records of seven years, we generate an origin …