Prediction of Pseudomonas aeruginosa abundance in drinking water distribution systems using machine learning DOI

Qiao-Mei Zhou,

Yukang Li, Min Wang

et al.

Process Safety and Environmental Protection, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 1, 2024

Language: Английский

Towards sustainable industrial development: modelling the quality, scaling potential and corrosivity of groundwater using GIS, spatial statistics, soft computing and index-based methods DOI
Johnson C. Agbasi, Mahamuda Abu, Johnbosco C. Egbueri

et al.

Environment Development and Sustainability, Journal Year: 2024, Volume and Issue: unknown

Published: June 21, 2024

Language: Английский

Citations

18

Artificial intelligence in microplastic detection and pollution control DOI
Jin Hui,

Fanhao Kong,

Xiangyu Li

et al.

Environmental Research, Journal Year: 2024, Volume and Issue: 262, P. 119812 - 119812

Published: Aug. 16, 2024

Language: Английский

Citations

13

Comparative Analysis of Design Parameters Impacting the Performance of Pyramidal and Spherical Solar Stills: A Review DOI Creative Commons
Faiz T.Jodah, Wissam H. Alawee, Hayder A. Dhahad

et al.

Desalination and Water Treatment, Journal Year: 2024, Volume and Issue: 319, P. 100545 - 100545

Published: June 19, 2024

Population growth, urbanization, and the effects of climate change all exacerbate problem global water scarcity, which poses a serious obstacle to sustainable development. Solar distillation emerges as critical solution, converting brackish or saline into potable using alternative energy. Despite wealth information on solar still adaptations, identifying most efficient design for residential industrial settings remains challenging. Hence, comparative analysis various designs is essential, considering practical financial aspects. This study aims showcase work researchers who are trying make systems more productive by looking at new techniques used in spherical pyramidal stills. The goal this research identify variables that influence efficiency, enabling achievement desired results with ease. Researchers have investigated interventions, such integrating moving parts other components, modifying basin's shape size, incorporating filaments wick, reducing surface tension through use floats balls, magnetic fields, improving electric field. According research, field (220 mT) above below basin increases molecular motion evaporation, resulting 41 % efficiency gain. Spherical stills don't require tracking because their uniform exposure radiation makes them than pyramid Reviews find adding rotating ball phase-changing materials significantly enhances stills, making best design. Mirrors reflect sunlight; an overview related literature shows it leads additional production. Future will focus comprehending annual production rates associated costs, aiming enhance our application strategies technology.

Language: Английский

Citations

8

Harnessing Deep Learning for Real-Time Water Quality Assessment: A Sustainable Solution DOI Open Access
Selma Toumi, Sabrina Lekmine, Nabil Touzout

et al.

Water, Journal Year: 2024, Volume and Issue: 16(23), P. 3380 - 3380

Published: Nov. 24, 2024

This study presents an innovative approach utilizing artificial intelligence (AI) for the prediction and classification of water quality parameters based on physico-chemical measurements. The primary objective was to enhance accuracy, speed, accessibility monitoring. Data collected from various samples in Algeria were analyzed determine key such as conductivity, turbidity, pH, total dissolved solids (TDS). These measurements integrated into deep neural networks (DNNs) predict indices sodium adsorption ratio (SAR), magnesium hazard (MH), percentage (SP), Kelley’s (KR), potential salinity (PS), exchangeable (ESP), well Water Quality Index (WQI) Irrigation (IWQI). DNNs model, optimized through selection activation functions hidden layers, demonstrated high precision, with a correlation coefficient (R) 0.9994 low root mean square error (RMSE) 0.0020. AI-driven methodology significantly reduces reliance traditional laboratory analyses, offering real-time assessments that are adaptable local conditions environmentally sustainable. provides practical solution resource managers, particularly resource-limited regions, efficiently monitor make informed decisions public health agricultural applications.

Language: Английский

Citations

7

Microbial drinking water monitoring now and in the future DOI Creative Commons
Thomas Pluym, Fien Waegenaar, Bart De Gusseme

et al.

Microbial Biotechnology, Journal Year: 2024, Volume and Issue: 17(7)

Published: July 1, 2024

Abstract Over time, humanity has addressed microbial water contamination in various ways. Historically, individuals resorted to producing beer combat the issue. Fast forward 19th century, and we witnessed a scientific approach by Robert Koch. His groundbreaking gelatine plating method aimed identify quantify bacteria, with proposed limit of 100 colony‐forming units per millilitre (CFU/mL) avoid Cholera outbreaks. Despite considerable advancements techniques through experimentation media compositions growth temperatures, reliance on century‐old for safety remains state‐of‐the‐art. Even though most countries succeed qualitative at end production centres, it is difficult control, guarantee, same quality during distribution. Rather than focusing solely specific sampling points, propose holistic examination entire network ensure comprehensive safety. Current practices leave room uncertainties, especially given low concentrations pathogens. Innovative methods like flow cytometry cytometric fingerprinting offer ability detect changes microbiome drinking water. Additionally, molecular emerging sequencing technologies, such as third‐generation (MinION), mark significant leap forward, enhancing detection limits emphasizing identification unwanted genes rather bacteria/microorganisms itself. last decades, there been realization that distribution networks are complex ecosystems that, beside comprise viruses, protozoans even isopods. Sequencing find eukaryotic DNA necessary monitor network. Or will artificial intelligence, big data machine learning prove be way go (microbial) monitoring? In essence, time transcend embrace modern technologies our from consumption.

Language: Английский

Citations

5

Automation of on-site microbial water quality monitoring from source to tap: challenges and perspectives DOI Creative Commons
Jean‐Baptiste Burnet, Katalin Demeter, Philip S. Brenner

et al.

Water Research, Journal Year: 2025, Volume and Issue: 274, P. 123121 - 123121

Published: Jan. 11, 2025

Language: Английский

Citations

0

Recent progress in highly effective electrocoagulation-coupled systems for advanced wastewater treatment DOI Creative Commons
Thi Kim Cuong Phu, Phi Long Nguyen, Thi Viet Bac Phung

et al.

iScience, Journal Year: 2025, Volume and Issue: 28(3), P. 111965 - 111965

Published: Feb. 7, 2025

Electrocoagulation (EC) has been a well-known technology for wastewater treatment over the past centuries, owing to its straightforward equipment requirements and highly effective contaminant removal efficiency. This literature review emphasizes influence of several input variables in EC system such as electrode materials, applied current, pH, supporting electrolyte, inner-electrode distance on effluent efficiency energy consumption. Besides that, depending intrinsic properties effluents, is recommended hybridize with other methods physical-, biological-, chemical-, electrochemical order enhance performance reduce Subsequently, comprehensive analysis presented, including power consumption, evaluation synergistic effect multiple using statistical methods. Finally, this discusses future perspectives environmentally friendly utilization post-EC treated sludges, development renewable energy-driven systems, challenges management by artificial intelligence.

Language: Английский

Citations

0

Unlocking IoT and Machine Learning’s Potential for Water Quality Assessment: An Extensive Analysis and Future Directions DOI

Shivendra Dubey,

Sakshi Dubey,

Kapil Raghuwanshi

et al.

Water Conservation Science and Engineering, Journal Year: 2025, Volume and Issue: 10(1)

Published: Feb. 7, 2025

Language: Английский

Citations

0

Advancing groundwater sustainability: strategy combining hydro-chemical analysis, pollution mitigation, and community-based water resource governance DOI

Kusam Kusam,

Diksha Kumari,

Shally Pandit

et al.

Groundwater for Sustainable Development, Journal Year: 2025, Volume and Issue: unknown, P. 101433 - 101433

Published: March 1, 2025

Language: Английский

Citations

0

Development and Implementation of a Software Information System for Biological Wastewater Treatment DOI
Andrii Safonyk, Сергій Полюхович, Олена Полюхович

et al.

Lecture notes on data engineering and communications technologies, Journal Year: 2025, Volume and Issue: unknown, P. 83 - 97

Published: Jan. 1, 2025

Language: Английский

Citations

0