AIMC Topic: Wastewater

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Application of AI-based techniques for anomaly management in wastewater treatment plants: A review.

Journal of environmental management
Effective anomaly management of wastewater treatment plants (WWTPs) is crucial for environmental conservation and public health security. Traditional monitoring methods often struggle with challenges such as multivariate coupling, nonlinear dynamics,...

Synthesis and characterization of lignin-copper nanohybrids for colorimetric acetaminophen detection: a combined physical chemistry and machine learning study.

Physical chemistry chemical physics : PCCP
Acetaminophen ranks among the most widely used pharmaceutical and personal care products today. Following consumption, the drug and its metabolites are excreted into sewage systems, wastewater treatment plants, and various aquatic environments, leadi...

Machine Learning-Driven Dynamic Measurement of Environmental Indicators in Multiple Scenes and Multiple Disturbances.

Environmental science & technology
Digital city water management systems require extensive data sensing for various environmental indicators, yet measurement accuracy often falls short under diverse extreme conditions. This study proposes a chemical oxygen demand (COD) measurement met...

Comparing the applicability of de facto population markers for spatiotemporal trend analysis in wastewater-based epidemiology.

Journal of hazardous materials
Wastewater-based epidemiology is an effective public health approach that enables early detection, monitoring, and assessment of community health trends by analysing human excretion products in wastewater. Here, accurate population normalization is e...

Optimizing models for the prediction of one step ahead extreme flows to wastewater treatment plants using different synthetic sampling methods.

Journal of environmental management
High-flow events that significantly impact Water Resource Recovery Facility (WRRF) operations are rare, but accurately predicting these flows could improve treatment operations. Data-driven modeling approaches could be used; however, high flow events...

Escaping Historical Lock-in─Redesigning Wastewater Treatment Plants and Their Microbiomes for the 21st Century.

Environmental science & technology
Wastewater treatment plants (WWTPs) have gradually, over the last hundred years, been designed and extended to deal with a sequence of problems, including a) odor, b) suspended solids, c) organics, d) ammonia, e) nitrate and phosphate, and f) recalci...

Insight mechanism of ANN model for denitrification in spouted bed bioreactor.

Scientific reports
Numerous technologies have been developed to remove nitrate from wastewater due to its significant health and environmental impacts. In the present study, an isolate of Pseudomonas syringae was utilized to investigate the denitrification rate using i...

AI-driven wastewater management through comparative analysis of feature selection techniques and predictive models.

Scientific reports
The integration of artificial intelligence (AI) in wastewater treatment management offers a promising approach to optimizing effluent quality predictions and enhancing operational efficiency. This study evaluates the performance of machine learning m...

Early detection of emerging SARS-CoV-2 Variants from wastewater through genome sequencing and machine learning.

Nature communications
Genome sequencing from wastewater enables accurate and cost-effective identification of SARS-CoV-2 variants. However, existing computational pipelines have limitations in detecting emerging variants not yet characterized in humans. Here, we present a...

Machine learning-based identification of wastewater treatment plant-specific microbial indicators using 16S rRNA gene sequencing.

Scientific reports
Effluent released from municipal wastewater treatment plants reflects the microbial communities responsible for degrading and removing contaminants within the plants. Monitoring this effluent offers essential insights into its environmental impacts, ...