AIMC Topic: Cities

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A hybrid CNN-ViT based framework for automatic traffic actions detection in smart cities.

PloS one
It is crucial to automatically detect traffic accidents and hazardous situations in a timely and accurate manner. In this way, both individual security will be ensured and significant contributions will be made to economic efficiency and sustainable ...

Relationship between landslide susceptibility and social lag in Mexico City: The case of the west periphery.

PloS one
Landslides threaten sustainable development through economic and human losses. This study integrates machine learning methods to construct susceptibility maps, including topographic-hydrological indicators, to improve the inclusion of earthflow lands...

Integrating Google Earth Engine and machine learning for urban land use and land cover dynamics analysis.

Environmental monitoring and assessment
The accurate land use and land cover (LULC) classification in the data-scarce urbanized region of Peshawar remains challenging due to computational limitations, accuracy assessment, and traditional techniques. This study, for the first time, addresse...

Secure facial biometric authentication in smart cities using multimodal methodology.

Scientific reports
In recent times, in modern smart city environments, securing and maintaining facial biometric security is crucial for preventing unauthorized access to citizen data and safeguarding it from spoofing. This research proposes a multimodal deep learning ...

Prediction of urban heat island intensity based on multiple linear regression and deep learning.

PloS one
The rapid urbanization process has led to many prominent environmental issues in urban areas, resulting from a drastic change in land use. The Urban Heat Island (UHI) effect is of particular concern because it has a significant impact on the livabili...

CABNas-nir: A near-infrared classification for urban pipe network sludge on the fusion algorithm of NAS framework and active learning.

PloS one
Pipe network sludge is a complex pollutant aggregate deposited during long-term operation of urban sewage pipelines, and a key target for pollution control in environmental monitoring systems. Accurate source classification is critical for treatment ...

Geospatial modeling and forecasting of urban land use change using Google Earth Engine and machine learning.

PloS one
Urban expansion and Land Use Land Cover (LULC) change pose critical challenges for sustainable urban planning and risks to food security. This study analyzes multi-temporal Landsat imagery from 1990 to 2020 for five major cities, Islamabad, Karachi, ...

Forecasting urban air quality in Paris using ensemble machine learning: A scalable framework for environmental management.

PloS one
Urban air pollution poses a significant threat to public health and urban sustainability in megacities like Paris. We cast forecasting as a short-term, next-hour prediction task for PM2.5, NO, and CO, using hourly meteorology and recent pollutant his...

A Satellite-Driven Model for Monitoring Urban Material Metabolism, Embodied Emissions, and Carbonation.

Environmental science & technology
Urban systems are central to global material consumption and carbon emissions. However, systematically understanding urban metabolism remains a challenge due to the reliance on aggregated, top-down data which fails to capture fine-scale urban dynamic...

Evaluating machine learning models and imputation strategies for Air Quality Index forecasting in urban India.

Environmental monitoring and assessment
Accurate Air Quality Index (AQI) prediction is essential for timely health risk management in urban environments, yet challenges such as missing data and complex pollutant interactions limit the performance of traditional approaches. This study inves...