AI Medical Compendium Topic:
Environmental Monitoring

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Deep learning-based efficient drone-borne sensing of cyanobacterial blooms using a clique-based feature extraction approach.

The Science of the total environment
Recent advances in remote sensing techniques provide a new horizon for monitoring the spatiotemporal variations of harmful algal blooms (HABs) using hyperspectral data in inland water. In this study, a hierarchical concatenated variational autoencode...

Identification of pollution source and prediction of water quality based on deep learning techniques.

Journal of contaminant hydrology
Semi-arid rivers are particularly vulnerable and responsive to the impacts of industrial contamination. Prompt identification and projection of pollutant dynamics are crucial in the accidental pollution incidents, therefore required the timely inform...

Groundwater quality index development using the ANN model of Delhi Metropolitan City, India.

Environmental science and pollution research international
Groundwater is widely recognized as a vital source of fresh drinking water worldwide. However, the rapid, unregulated population growth and increased industrialization, coupled with a rise in human activities, have significantly harmed the quality of...

Evaluating long-term and high spatiotemporal resolution of wet-bulb globe temperature through land-use based machine learning model.

Journal of exposure science & environmental epidemiology
BACKGROUND: The increase in global temperature and urban warming has led to the exacerbation of heatwaves, which negatively affect human health and cause long-term loss of work productivity. Therefore, a global assessment in temperature variation is ...

Rapid detection of colored and colorless macro- and micro-plastics in complex environment via near-infrared spectroscopy and machine learning.

Journal of environmental sciences (China)
To better understand the migration behavior of plastic fragments in the environment, development of rapid non-destructive methods for in-situ identification and characterization of plastic fragments is necessary. However, most of the studies had focu...

Intrinsic and extrinsic techniques for quantification uncertainty of an interpretable GRU deep learning model used to predict atmospheric total suspended particulates (TSP) in Zabol, Iran during the dusty period of 120-days wind.

Environmental pollution (Barking, Essex : 1987)
Total suspended particulates (TSP), as a key pollutant, is a serious threat for air quality, climate, ecosystems and human health. Therefore, measurements, prediction and forecasting of TSP concentrations are necessary to mitigate their negative effe...

Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches.

Environmental research
Assessing eutrophication in coastal and transitional waters is of utmost importance, yet existing Trophic Status Index (TSI) models face challenges like multicollinearity, data redundancy, inappropriate aggregation methods, and complex classification...

Large-scale spatiotemporal deep learning predicting urban residential indoor PM concentration.

Environment international
Indoor PM pollution is one of the leading causes of death and disease worldwide. As monitoring indoor PM concentrations on a large scale is challenging, it is urgent to assess population-level exposure and related health risks to develop an easy-to-u...

Urban surface classification using semi-supervised domain adaptive deep learning models and its application in urban environment studies.

Environmental science and pollution research international
High-resolution urban surface information, e.g., the fraction of impervious/pervious surface, is pivotal in studies of local thermal/wind environments and air pollution. In this study, we introduced and validated a domain adaptive land cover classifi...

Applications of remote sensing vis-à-vis machine learning in air quality monitoring and modelling: a review.

Environmental monitoring and assessment
Environmental contamination especially air pollution is an exponentially growing menace requiring immediate attention, as it lingers on with the associated risks of health, economic and ecological crisis. The special focus of this study is on the adv...