AIMC Topic: Environmental Monitoring

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Deep learning-driven investigation of nanoplastic impacts on soil protist behavior in soil chips.

Environmental pollution (Barking, Essex : 1987)
Nanoplastics are emerging environmental contaminants that increasingly threaten soil ecosystems, yet their effects on microbial behavior remain poorly understood. This is mainly due to the lack of experimental tools capable of directly observing micr...

Machine learning in ecotoxicology: Pollutant exposure levels and detection, biotoxicity and environmental behavior prediction.

The Science of the total environment
In recent years, the worsening problem of environmental pollution and the limitations of traditional toxicological assays have accelerated the adoption of machine learning (ML) in ecotoxicology. ML enables rapid and accurate prediction of pollutant e...

A hybrid ACO-random forest optimization framework for scalable microalgae biomass estimation using multispectral imaging.

Environmental monitoring and assessment
Accurate estimation of algal biomass is essential for monitoring ecosystem productivity, managing aquaculture systems, and optimizing bioresource applications. However, traditional in situ methods are labor-intensive and spatially limited, while remo...

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...

From passive prevention to proactive intervention: An AI-assisted integrated governance system for algal bloom monitoring and control.

Environmental research
Algal blooms, characterized by the excessive proliferation of microalgae in a freshwater or marine ecosystem, have evolved into a global ecological, health and economic crisis, which is often accompanied by the release of toxins and the damage of the...

A global analysis of the influence of shallow and deep groundwater tables on relationships between environmental parameters and heatwaves.

Environmental research
Heatwaves increasingly impact ecosystems, human health, and economic activities worldwide. As their frequency and intensity rise, understanding the mechanisms driving heatwave dynamics and interactions with land surface processes becomes crucial. Whi...

An Integrated Machine Learning and Remote Sensing Method for Predicting Cyanobacterial Blooms: A Case Study in China's lakes along a large-scale water diversion project.

Environmental management
Cyanobacterial blooms in lakes are a complex and challenging environmental issue worldwide. However, many existing studies on cyanobacterial bloom prediction were constrained by limited data availability, which poses significant challenges to the dev...

Explainable AI-driven interpretation of environmental drivers of tomato fruit expansion in smart greenhouses using IoT sensing.

Scientific reports
Tomato fruit expansion is a key physiological process that determines fruit size, marketability, and yield, yet its quantitative and threshold-based response to microclimatic factors in smart greenhouses has been insufficiently studied. This study de...

Advanced machine learning models for accurate water quality classification and WQI prediction: Implications for aquatic disease risk management.

The Science of the total environment
Accurate classification of water quality and precise prediction of the Water Quality Index (WQI) are essential for safeguarding aquatic ecosystems and mitigating disease risks in aquaculture. This study systematically evaluates multiple machine learn...

Explainable machine-learning-based predictions of blood lead levels and school drinking water contamination among children: a case study in Washington DC.

Scientific reports
Water quality degradation poses significant risks to human health, ecosystem, and community. Many cities continue to rely on outdated pipes and water distribution networks that are highly susceptible to leaks, corrosion, and lead contamination. The p...