AIMC Topic: Cities

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Feature Selection and Pedestrian Detection Based on Sparse Representation.

PloS one
Pedestrian detection have been currently devoted to the extraction of effective pedestrian features, which has become one of the obstacles in pedestrian detection application according to the variety of pedestrian features and their large dimension. ...

Using wavelet-feedforward neural networks to improve air pollution forecasting in urban environments.

Environmental monitoring and assessment
The paper presents the screening of various feedforward neural networks (FANN) and wavelet-feedforward neural networks (WFANN) applied to time series of ground-level ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM10 and PM2.5 fractions...

Identifying factors influencing trace metal concentrations in urban residential soil using an optimal parameter-based geographical detector model.

Environmental research
Australia's national citizen science program VegeSafe has collected and analysed over 26,000 residential garden soil samples for their trace metal concentrations, enabling a more comprehensive understanding of the factors influencing contamination. H...

Made in China 2025: Artificial intelligence intervention and urban green economy development.

Journal of environmental management
Against the backdrop of the profound adjustment of the global industrial structure and the rise of the Fourth Industrial Revolution, the contradiction between rapid economic growth and ecological environmental protection has become increasingly promi...

Quantifying role of source variations on PM-bound toxic components under climate change: Measurement at multiple sites during 2018-2022 in a Chinese megacity.

Journal of hazardous materials
Understanding the response of PM-bound toxic components to source variations under climate change is crucial for public health protection. However, the lack of long-term and multi-site observational data of toxic components limits such efforts. Here,...

Human-perceived vs actual built environment: Using human-centred GeoAI and street view images to support urban planning in Australia.

Journal of environmental management
In alignment with the United Nations Sustainable Development Goals, the pursuit of safe and sustainable cities that promote well-being across all age groups has become a core objective in urban planning and environmental management. The built environ...

Does AI-driven innovation improve green productivity? The role of heterogeneous information infrastructure.

Journal of environmental management
Artificial intelligence (AI) 's rapid advancement presents opportunities and challenges for achieving sustainable development goals. In particular, understanding how AI can enhance green productivity is crucial for promoting high-quality, low-carbon ...

Building efficiency: How the national AI innovation pilot zones enhance green energy utilization? Evidence from China.

Journal of environmental management
Improving energy efficiency is a pivotal strategy for achieving energy conservation, emission reduction, and green development goals, while also serving as a critical indicator for evaluating high-quality economic growth and sustainable development. ...

A high-resolution GIS and machine learning approach for targeted disease management and localized risk assessment in an urban setup: A case study from Bhopal, Central India.

Acta tropica
Predicting dengue distribution based on environmental factors is crucial for effective vector control and management as environmental factors like temperature, demographics, and artificial changes such as roads and buildings significantly influence d...

Data-Driven Detection of Nocturnal Pollen Fragmentation Triggered by High Humidity in an Urban Environment.

Environmental science & technology
Biological particulate matter (BioPM) in the urban environment can affect human health and climate. Pollen, a key BioPM component, produces smaller particles when fragmented, significantly impacting public health. However, detecting pollen fragmentat...