Rainfall monsoons and the resulting flooding have always been cataclysmic disasters that
have heightened global concerns in light of climate change. Flood susceptibility modeling is …

An accurate understanding of noise perception is important for urban planning, noise
management and public health. However, the visual and acoustic urban landscapes are …

Flash floods are one of the worst natural disasters, causing massive economic losses and
many deaths. Creating a flood susceptibility map (FSM) that pinpoints the areas most at risk …

Driver drowsiness leads to fatal road traffic accidents. The effects of drowsy driving on
electroencephalogram (EEG) signal are well visible. Accordingly, classifying EEG signal …

Urbanization's impact on climate is increasingly recognized as a significant public health
challenge, particularly for respiratory conditions like asthma. Despite progress in …

Recurring wildfires pose a critical global issue as they undermine social and economic
stability and jeopardize human lives. To effectively manage disasters and bolster community …

This research aimed to conduct Spatio-temporal modeling of people's olfactory perception in
the Tehran city using a machine learning-based approach considering the importance of …

This study addresses the critical need for comprehensive multi-pollution modeling in urban
environments by employing Geospatial Artificial Intelligence (GeoAI) techniques …

Dust pollution poses significant risks to human health, air quality, and food safety,
necessitating the identification of dust occurrence and the development of dust susceptibility …

To mitigate the impact of dust on human health and the environment, it is crucial to create a
model and map that identifies the areas susceptible to dust. The present study focused on …