AIMC Topic: Sewage

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An intelligent system for precise management of coagulants in sludge conditioning: Inspired by the exploratory behavior in primates using senses.

Water research
Coagulation conditioning is a key step for sludge dewatering, while the control of optimal coagulant dosing is still a challenge. This study proposes an intelligent system for the precise management of coagulants (IIS) in sludge conditioning. This sy...

Surveillance of SARS-CoV-2 RNA in wastewater treatment plants in Türkiye, Istanbul: a long-term study and statistical analysis.

Environmental monitoring and assessment
Wastewater-based epidemiology (WBE) is a powerful method that allows community surveillance to identify diseases/pandemic dynamics in a city, especially in metropolitan areas with high overpopulation. This study investigated the detection and quantif...

Multi-agent large language model frameworks: Unlocking new possibilities for optimizing wastewater treatment operation.

Environmental research
Wastewater treatment plants (WWTPs) are highly complex systems where biological, chemical, and physical processes interact dynamically, creating significant operational challenges. Traditional modeling approaches, such as Activated Sludge Models (ASM...

Water level estimation in sewage pipes using texture-based methods and machine learning algorithms.

Water science and technology : a journal of the International Association on Water Pollution Research
Water companies use closed-circuit television (CCTV) to inspect the condition of sewage pipes. The reports generated by surveyors help companies to plan for the maintenance and rehabilitation of sewage pipes. A surveyor needs to record the water leve...

Effect of training sample size, image resolution and epochs on filamentous and floc-forming bacteria classification using machine learning.

Journal of environmental management
Computer vision techniques can expedite the detection of bacterial growth in wastewater treatment plants and alleviate some of the shortcomings associated with traditional detection methods. In recent years, researchers capitalized on this potential ...

Bayesian Optimization-Enhanced Reinforcement learning for Self-adaptive and multi-objective control of wastewater treatment.

Bioresource technology
Controllers of wastewater treatment plants (WWTPs) often struggle to maintain optimal performance due to dynamic influent characteristics and the need to balance multiple operational objectives. In this study, Reinforcement Learning (RL) algorithms a...

Semi-supervised learning-based identification of the attachment between sludge and microparticles in wastewater treatment.

Journal of environmental management
Monitoring the microparticle transfer process in wastewater treatment systems is crucial for improving treatment performance. Supervised deep learning methods show high performance to automatically detect particles, but they rely on vast amounts of l...

Automatic visual detection of activated sludge microorganisms based on microscopic phase contrast image optimisation and deep learning.

Journal of microscopy
The types and quantities of microorganisms in activated sludge are directly related to the stability and efficiency of sewage treatment systems. This paper proposes a sludge microorganism detection method based on microscopic phase contrast image opt...

Understanding the low-temperature drying process of sludge with machine learning in a sewage-source heat pump drying system.

Journal of environmental management
Heat pump drying technology based on sewage heat source is an eco-friendly sludge drying method. It can effectively reduce the pollution of natural water bodies by waste heat while reducing energy consumption. However, the drying characteristics of s...

Integrating machine learning, suspect and nontarget screening reveal the interpretable fates of micropollutants and their transformation products in sludge.

Journal of hazardous materials
Activated sludge enriches vast amounts of micropollutants (MPs) when wastewater is treated, posing potential environmental risks. While standard methods typically focus on target analysis of known compounds, the identity, structure, and concentration...