Environmental Science › Water Science and Technology

Water Quality Monitoring Technologies

Works Count: 70881

Wikipedia

Description

This cluster of papers focuses on real-time monitoring of water quality, aquaculture management, and environmental sensing using advanced technologies such as sensor networks, IoT, and computer vision. The research covers topics including smart sensors, wireless monitoring, fish behavior analysis, and remote sensing for environmental monitoring.

Keywords

Water Quality Monitoring; Aquaculture; Sensor Networks; IoT; Computer Vision; Fish Behavior Analysis; Smart Sensors; Wireless Monitoring; Remote Sensing; Environmental Monitoring

Automated taxonomic classification of phytoplankton sampled with imaging‐in‐flow cytometry

2007-06-01

Heidi M. Sosik , Robert Olson

High‐resolution photomicrographs of phytoplankton cells and chains can now be acquired with imaging‐in‐flow systems at rates that make manual identification impractical for many applications. To address the challenge for automated … High‐resolution photomicrographs of phytoplankton cells and chains can now be acquired with imaging‐in‐flow systems at rates that make manual identification impractical for many applications. To address the challenge for automated taxonomic identification of images generated by our custom‐built submersible Imaging FlowCytobot, we developed an approach that relies on extraction of image features, which are then presented to a machine learning algorithm for classification. Our approach uses a combination of image feature types including size, shape, symmetry, and texture characteristics, plus orientation invariant moments, diffraction pattern sampling, and co‐occurrence matrix statistics. Some of these features required preprocessing with image analysis techniques including edge detection after phase congruency calculations, morphological operations, boundary representation and simplification, and rotation. For the machine learning strategy, we developed an approach that combines a feature selection algorithm and use of a support vector machine specified with a rigorous parameter selection and training approach. After training, a 22‐category classifier provides 88% overall accuracy for an independent test set, with individual category accuracies ranging from 68% to 99%. We demonstrate application of this classifier to a nearly uninterrupted 2‐month time series of images acquired in Woods Hole Harbor, including use of statistical error correction to derive quantitative concentration estimates, which are shown to be unbiased with respect to manual estimates for random subsamples. Our approach, which provides taxonomically resolved estimates of phytoplankton abundance with fine temporal resolution (hours for many species), permits access to scales of variability from tidal to seasonal and longer.

View PDF Chat

Pond Aquaculture Water Quality Management

1998-01-01

Claude E. Boyd , Craig S. Tucker

The Physiology of Fishes

2020-08-10

Suzanne Currie , David H. Evans

Muscle Plasticity Grant B. McClelland and Graham R. Scott Cardiovascular System A. Kurt Gamperl and Holly A. Shiels Membranes and Metabolism James S. Ballantyne Oxygen Sensing Michael G. Jonz Intestinal … Muscle Plasticity Grant B. McClelland and Graham R. Scott Cardiovascular System A. Kurt Gamperl and Holly A. Shiels Membranes and Metabolism James S. Ballantyne Oxygen Sensing Michael G. Jonz Intestinal Transport Martin Grosell Gill Ionic Transport, Acid-Base Regulation, and Nitrogen Excretion Pung-Pung Hwang and Li-Yih Lin Endocrine Disruption Heather J. Hamlin Thermal Stress Suzanne Currie and Patricia M. Schulte Physiology of Social Stress in Fishes Christina Sorensen, Ida Beitnes Johansen, and Oyvind Overli Pain Perception Victoria A. Braithwaite Chemoreception Warren W. Green and Barbara S. Zielinski Active Electroreception Signals, Sensing, and Behavior John E. Lewis Cardiac Regeneration Viravuth P. Yin Neuronal Regeneration Ruxandra F. Sirbulescu and Gunther K.H. Zupanc

Wastewater engineering : treatment and reuse

2004-01-01

Metcalf , Eddy

1. Wastewater Engineering: An Overview 2. Constituents in Wastewater 3. Analysis and Selection of Wastewater Flowrates and Constituent Loadings 4. Introduction to Process Analysis and Selection 5. Physical Unit Operations … 1. Wastewater Engineering: An Overview 2. Constituents in Wastewater 3. Analysis and Selection of Wastewater Flowrates and Constituent Loadings 4. Introduction to Process Analysis and Selection 5. Physical Unit Operations 6. Chemical Unit Processes 7. Fundamentals of Biological Treatment 8. Suspended Growth Biological Treatment Processes 9. Attached Growth and Combined Biological Treatment Processes 10. Anaerobic Suspended and Attached Growth Biological Treatment Processes 11. Advanced Wastewater Treatment 12. Disinfection Processes 13. Water Reuse 14. Treatment, Reuse, and Disposal of Solids and Biosolids 15. Issues Related to Treatment-Plant Performance Appendixes A Conversion Factors B Physical Properties of Selected Gases and the Composition of Air C Physical Properties of Water D Solubility of Dissolved Oxygen in Water as a Function of Salinity and Barometric Pressure E MPN Tables and Their Use F Carbonate Equilibrium G Moody Diagrams for the Analysis of Flow in Pipes

Assessing biological integrity in running waters : a method and its rationale

1986-09-01

James R. Karr

Reducing the potential environmental impact of tank aquaculture effluents through intensification and recirculation

2003-08-12

Raul H. Piedrahita

Automated Irrigation System Using a Wireless Sensor Network and GPRS Module

2013-08-19

Joaquín Gutiérrez , Juan Francisco Villa-Medina , Alejandra Nieto‐Garibay +1 more

An automated irrigation system was developed to optimize water use for agricultural crops. The system has a distributed wireless network of soil-moisture and temperature sensors placed in the root zone … An automated irrigation system was developed to optimize water use for agricultural crops. The system has a distributed wireless network of soil-moisture and temperature sensors placed in the root zone of the plants. In addition, a gateway unit handles sensor information, triggers actuators, and transmits data to a web application. An algorithm was developed with threshold values of temperature and soil moisture that was programmed into a microcontroller-based gateway to control water quantity. The system was powered by photovoltaic panels and had a duplex communication link based on a cellular-Internet interface that allowed for data inspection and irrigation scheduling to be programmed through a web page. The automated system was tested in a sage crop field for 136 days and water savings of up to 90% compared with traditional irrigation practices of the agricultural zone were achieved. Three replicas of the automated system have been used successfully in other places for 18 months. Because of its energy autonomy and low cost, the system has the potential to be useful in water limited geographically isolated areas.

Impacts of desalination plant discharges on the marine environment: A critical review of published studies

2010-05-05

David A. Roberts , Emma L. Johnston , Nathan A. Knott

Optical Aspects of Oceanography

1975-06-01

A.J. Allnutt

(1975). Optical Aspects of Oceanography. Optica Acta: International Journal of Optics: Vol. 22, No. 6, pp. 561-561. (1975). Optical Aspects of Oceanography. Optica Acta: International Journal of Optics: Vol. 22, No. 6, pp. 561-561.

Handbook of Computations for Biological Statistics of Fish Populations

1960-12-30

Lawrence B. Slobodkin , W. E. Ricker

An imaging-in-flow system for automated analysis of marine microplankton

1998-01-01

CK Sieracki , Michael E. Sieracki , CS Yentsch

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 168:285-296 (1998) - doi:10.3354/meps168285 … MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 168:285-296 (1998) - doi:10.3354/meps168285 An imaging-in-flow system for automated analysis of marine microplankton Christian K. Sieracki*, Michael E. Sieracki, Charles S. Yentsch Bigelow Laboratory for Ocean Sciences, PO Box 475 McKown Point, West Boothbay Harbor, Maine 04575, USA *E-mail: [email protected] ABSTRACT: Present automated systems for counting and measuring marine plankton include flow cytometers and in situ plankton video recorders. Neither of these approaches are optimal for the microplankton cells which range in size from 20 to 200 µm and can be fewer than 104 l-1. We describe here an instrument designed for rapid counting, imaging and measuring of individual cells and particles in the microplankton size range from cultures and natural populations. It uses a unique optical element to extend the depth of focus of the imaging lens, allowing a sample stream flow rate of 1 ml min-1. The instrument stores a digital image of each particle along with real time fluorescence and size measurements. An interactive cytogram links a dot-plot of the size and fluorescence data to the stored cell images, allowing rapid characterization of populations. We have tested the system on live phytoplankton cultures and bead standards, proving the system counting and sizing accuracy and precision. The system provides images and size distributions for cultures or natural marine samples. It has been used successfully at sea to continuously monitor particles while underway. It may prove useful in studies of plankton community structure, ocean optics and monitoring for harmful algal species. KEY WORDS: Imaging · Flow cytometer · Microplankton · Binary optical element · Cell counting · Cell sizing · Natural populations · High rate · Cultures Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 168. Publication date: July 09, 1998 Print ISSN:0171-8630; Online ISSN:1616-1599 Copyright © 1998 Inter-Research.

View PDF Chat

Target strength of an individual fish at any aspect

1977-12-01

Richard H. Love

A set of empirical equations has been developed for use in determining the target strength or acoustic cross section of an individual fish at any insonified aspect as a function … A set of empirical equations has been developed for use in determining the target strength or acoustic cross section of an individual fish at any insonified aspect as a function of fish size and insonifying frequency in the range 1?L/λ? 100, where L is fish length and λ is acoustic wavelength. The equations were developed by interpolating experimental data obtained by insonifying individual fish as they were rotated about one of their principal axes. It was found that acoustic cross section σ is proportional to slightly less than L2 for each aspect, indicating that σ is approximately proportional to insonified area. Since σ is almost proportional to L2, a modified set of empirical equations was developed with σ exactly proportional to L2, thus eliminating the dependence of σ on frequency. The resulting errors are relatively minor and in some situations the modified equations lead to considerable simplifications which make their use quite convenient.

SIGNIFICANCE OF CARBONATES IN IRRIGATION WATERS

1950-02-01

Frank M. Eaton

A review of permissible limits of drinking water

2012-01-01

Avinash Puri , M. Kumar

Water is one of the prime necessities of life. We can hardly live for a few days without water. In a man's body, 70-80% is water. Cell, blood, and bones … Water is one of the prime necessities of life. We can hardly live for a few days without water. In a man's body, 70-80% is water. Cell, blood, and bones contain 90%, 75%, and 22% water, respectively. The general survey reveals that the total surface area of earth is 51 crore km(2) out of which 36.1 crore km(2) is covered sea. In addition to this, we get water from rivers, lakes, tanks, and now on hills. In spite of such abundance, there is a shortage of soft water in the world. Physicochemical parameter of any water body plays a very important role in maintaining the fragile ecosystem that maintains various life forms. Present research paper deals with various water quality parameter, chlorides, dissolved oxygen, total iron, nitrate, water temperature, pH, total phosphorous, fecal coli form bacteria, and adverse effect of these parameters on human being.

An Introduction to Environmental Biophysics

1977-10-01

Sherwood B. Idso

Advances in on-line drinking water quality monitoring and early warning systems

2010-09-07

Michael V. Storey , Bram van der Gaag , Brendan P. Burns

A manual on methods for the assessment of secondary productivity in fresh waters

1972-03-01

John Downing , F. H. Rigler

USE OF SALINE IRRIGATION WATER

1963-06-01

W. P. Kelley

Quantifying absorption by aquatic particles: A multiple scattering correction for glass-fiber filters

1993-09-01

Joan S. Cleveland , A. D. Weidemann

Absorption spectra measured for aquatic particles concentrated onto glass-fiber filters require a correction for the increase in pathlength caused by multiple scattering in the glass-fiber filter. A multiple scattering correction … Absorption spectra measured for aquatic particles concentrated onto glass-fiber filters require a correction for the increase in pathlength caused by multiple scattering in the glass-fiber filter. A multiple scattering correction was calculated from optical density spectra for 48 phytoplankton cultures of seven species representing a variety of cell sizes, pigment groups, and cell-wall types. The relationship between optical density in suspensions and on filters was not wavelength-dependent. Differences between blank filters were always spectrally neutral. Small differences between relationships for single species were inconclusive. Given the absence of wavelength-dependent effects, we report a single general quadratic relationship, ODsusp(λ) = 0.378 ODfilt(λ) + 0.523 ODfilt(λ)2 (r2 = 0.988), for correcting glass-fiber filter spectra. For independent samples, the average error in predicting ODsusp(λ) with this algorithm at any wavelength was 2%. Greatest errors were in spectral regions of low absorption. Absorption spectra for particles concentrated onto glass-fiber filters can be quantitatively corrected for multiple scattering within this limit. Applicability of the algorithm to field samples of varied composition was enhanced by using a large number of spectra and a range of cell types in algorithm development.

View PDF Chat

Anaerobic wastewater treatment

1986-12-01

Perry L. McCarty , Daniel P. Smith

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTAnaerobic wastewater treatmentPerry L. McCarty and Daniel P. SmithCite this: Environ. Sci. Technol. 1986, 20, 12, 1200–1206Publication Date (Print):December 1, 1986Publication History Published online1 May 2002Published inissue … ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTAnaerobic wastewater treatmentPerry L. McCarty and Daniel P. SmithCite this: Environ. Sci. Technol. 1986, 20, 12, 1200–1206Publication Date (Print):December 1, 1986Publication History Published online1 May 2002Published inissue 1 December 1986https://pubs.acs.org/doi/10.1021/es00154a002https://doi.org/10.1021/es00154a002research-articleACS PublicationsRequest reuse permissionsArticle Views3892Altmetric-Citations341LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts

Urban hydrology and water management – present and future challenges

1999-03-01

Janusz Niemczynowicz

Application of carbon nanotube technology for removal of contaminants in drinking water: A review

2009-10-13

Venkata K.K. Upadhyayula , Shuguang Deng , Martha C. Mitchell +1 more

Real-time remote monitoring of water quality: a review of current applications, and advancements in sensor, telemetry, and computing technologies

2004-03-01

Howard B. Glasgow , JoAnn M. Burkholder , Robert E. Reed +2 more

Water and Aqueous Solutions

1972-12-01

J. Nix

Water and waste water filtration. Concepts and applications

1971-11-01

Kuan-Mu Yao , Mohammad T. Habibian , Charles R. O’Melia

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTWater and waste water filtration. Concepts and applicationsKuan-Mu Yao, Mohammad T. Habibian, and Charles R. O'MeliaCite this: Environ. Sci. Technol. 1971, 5, 11, 1105–1112Publication Date (Print):November 1, … ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTWater and waste water filtration. Concepts and applicationsKuan-Mu Yao, Mohammad T. Habibian, and Charles R. O'MeliaCite this: Environ. Sci. Technol. 1971, 5, 11, 1105–1112Publication Date (Print):November 1, 1971Publication History Published online1 May 2002Published inissue 1 November 1971https://pubs.acs.org/doi/10.1021/es60058a005https://doi.org/10.1021/es60058a005research-articleACS PublicationsRequest reuse permissionsArticle Views8630Altmetric-Citations1348LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose Get e-Alerts

View PDF Chat

Water quality guidelines for the management of pond fish culture

2013-01-01

Anita Bhatnagar , P Anusuya Devi

The Optimum fish production is totally dependent on the physical, chemical and biological qualities of water to most of the extent. Hence, successful pond management requires an understanding of water … The Optimum fish production is totally dependent on the physical, chemical and biological qualities of water to most of the extent. Hence, successful pond management requires an understanding of water quality. Water quality is determined by variables like temperature, transparency, turbidity, water colour, carbon dioxide, pH, alkalinity, hardness, unionised ammonia, nitrite, nitrate, primary productivity, BOD, plankton population etc. In the present chapter water quality management principles in fish culture have been reviewed to make aware the fish culturist and environmentalist about the important water quality factors that influence health of a pond and are required in optimum values to increase the fish yields to meet the growing demands of present day scenario of the world, when the food resources are in a state of depletion and the population pressure is increasing on these resources.

The Aquarius/SAC-D Mission: Designed to Meet the Salinity Remote-Sensing Challenge

2008-03-01

Gary Lagerloef , F. R. Colomb , Davide Le Vine +7 more

View PDF Chat

A New Method for Estimating the Freshness of Fish

1959-01-01

Tsuneyuki SAITO , K.I. Arai , Minoru MATSUYOSHI

View PDF Chat

A Manual on Methods for Measuring Primary Production in Aquatic Environments.

1970-07-01

John Lund , Richard A. Vollenweider

Experimental Methods in Wastewater Treatment

2016-04-04

Mark C.M. van Loosdrecht , Per Halkjær Nielsen , Carlos M. López-Vázquez +1 more

Over the past twenty years, the knowledge and understanding of wastewater treatment has advanced extensively and moved away from empirically-based approaches to a fundamentally-based first-principles approach embracing chemistry, microbiology, and … Over the past twenty years, the knowledge and understanding of wastewater treatment has advanced extensively and moved away from empirically-based approaches to a fundamentally-based first-principles approach embracing chemistry, microbiology, and physical and bioprocess engineering, often involving experimental laboratory work and techniques. Many of these experimental methods and techniques have matured to the degree that they have been accepted as reliable tools in wastewater treatment research and practice. For sector professionals, especially the new generation of young scientists and engineers entering the wastewater treatment profession, the quantity, complexity and diversity of these new developments can be overwhelming, particularly in developing countries where access to advanced level laboratory courses in wastewater treatment is not readily available. In addition, information on innovative experimental methods is scattered across scientific literature and only partially available in the form of textbooks or guidelines. This book seeks to address these deficiencies. It assembles and integrates the innovative experimental methods developed by research groups and practitioners around the world and broadly applied in wastewater treatment research and practice. Experimental Methods in Wastewater Treatment book forms part of the internet-based curriculum in sanitary engineering at UNESCO-IHE and, as such, may also be used together with video recordings of methods and approaches performed and narrated by the authors, including guidelines on best experimental practices. The book is written for undergraduate and postgraduate students, researchers, laboratory staff, plant operators, consultants, and other sector professionals. ISBN: 9781780404752 (eBook) ISBN: 9781780404745 (Print)

View PDF Chat

A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques

2016-08-16

Mohammad Haji Gholizadeh , Assefa M. Melesse , Lakshmi N. Reddi

Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative … Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water's surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD).

View PDF Chat

Precision fish farming: A new framework to improve production in aquaculture

2017-11-14

Martin Føre , Kevin Frank , Tomás Norton +7 more

Aquaculture production of finfish has seen rapid growth in production volume and economic yield over the last decades, and is today a key provider of seafood. As the scale of … Aquaculture production of finfish has seen rapid growth in production volume and economic yield over the last decades, and is today a key provider of seafood. As the scale of production increases, so does the likelihood that the industry will face emerging biological, economic and social challenges that may influence the ability to maintain ethically sound, productive and environmentally friendly production of fish. It is therefore important that the industry aspires to monitor and control the effects of these challenges to avoid also upscaling potential problems when upscaling production. We introduce the Precision Fish Farming (PFF) concept whose aim is to apply control-engineering principles to fish production, thereby improving the farmer's ability to monitor, control and document biological processes in fish farms. By adapting several core principles from Precision Livestock Farming (PLF), and accounting for the boundary conditions and possibilities that are particular to farming operations in the aquatic environment, PFF will contribute to moving commercial aquaculture from the traditional experience-based to a knowledge-based production regime. This can only be achieved through increased use of emerging technologies and automated systems. We have also reviewed existing technological solutions that could represent important components in future PFF applications. To illustrate the potential of such applications, we have defined four case studies aimed at solving specific challenges related to biomass monitoring, control of feed delivery, parasite monitoring and management of crowding operations.

View PDF Chat

Standard methods for the examination of water and wastewater: 20th ed

2000-01-01

Water science and technology

1973-09-01

Smart Water Management Platform: IoT-Based Precision Irrigation for Agriculture

2019-01-11

Carlos Kamienski , Juha-Pekka Soininen , Markus Taumberger +5 more

The smart management of freshwater for precision irrigation in agriculture is essential for increasing crop yield and decreasing costs, while contributing to environmental sustainability. The intense use of technologies offers … The smart management of freshwater for precision irrigation in agriculture is essential for increasing crop yield and decreasing costs, while contributing to environmental sustainability. The intense use of technologies offers a means for providing the exact amount of water needed by plants. The Internet of Things (IoT) is the natural choice for smart water management applications, even though the integration of different technologies required for making it work seamlessly in practice is still not fully accomplished. The SWAMP project develops an IoT-based smart water management platform for precision irrigation in agriculture with a hands-on approach based on four pilots in Brazil and Europe. This paper presents the SWAMP architecture, platform, and system deployments that highlight the replicability of the platform, and, as scalability is a major concern for IoT applications, it includes a performance analysis of FIWARE components used in the Platform. Results show that it is able to provide adequate performance for the SWAMP pilots, but requires specially designed configurations and the re-engineering of some components to provide higher scalability using less computational resources.

View PDF Chat

Efficient Water Quality Prediction Using Supervised Machine Learning

2019-10-24

Umair Ahmed , Rafia Mumtaz , Hirra Anwar +3 more

Water makes up about 70% of the earth’s surface and is one of the most important sources vital to sustaining life. Rapid urbanization and industrialization have led to a deterioration … Water makes up about 70% of the earth’s surface and is one of the most important sources vital to sustaining life. Rapid urbanization and industrialization have led to a deterioration of water quality at an alarming rate, resulting in harrowing diseases. Water quality has been conventionally estimated through expensive and time-consuming lab and statistical analyses, which render the contemporary notion of real-time monitoring moot. The alarming consequences of poor water quality necessitate an alternative method, which is quicker and inexpensive. With this motivation, this research explores a series of supervised machine learning algorithms to estimate the water quality index (WQI), which is a singular index to describe the general quality of water, and the water quality class (WQC), which is a distinctive class defined on the basis of the WQI. The proposed methodology employs four input parameters, namely, temperature, turbidity, pH and total dissolved solids. Of all the employed algorithms, gradient boosting, with a learning rate of 0.1 and polynomial regression, with a degree of 2, predict the WQI most efficiently, having a mean absolute error (MAE) of 1.9642 and 2.7273, respectively. Whereas multi-layer perceptron (MLP), with a configuration of (3, 7), classifies the WQC most efficiently, with an accuracy of 0.8507. The proposed methodology achieves reasonable accuracy using a minimal number of parameters to validate the possibility of its use in real time water quality detection systems.

View PDF Chat

Comparative analysis of surface water quality prediction performance and identification of key water parameters using different machine learning models based on big data

2019-12-31

Kangyang Chen , Hexia Chen , Chuanlong Zhou +7 more

The biology of temporary waters

2007-07-01

Water A Comprehensive Treatise

1975-01-01

Felix Franks

UF FLMNH Ichthyology

2024-01-01

Rob Robins

The UF Fish Collection, dating to 1917, contains 214,205 lots and 2,300,803 specimens. Included are representatives of 8,250 species from 400 families. The collection includes 93 primary types and approximately … The UF Fish Collection, dating to 1917, contains 214,205 lots and 2,300,803 specimens. Included are representatives of 8,250 species from 400 families. The collection includes 93 primary types and approximately 1,600 lots of secondary types representing 563 species. Also in the collection are 5,825 specimens of disarticulated and articulated skeletons representing 875 species. Especially notable are historic collections of large and important marine fishes as well as rapidly growing collections of freshwater fishes from Southeast Asia. In 2006, the museum expanded its program to archive frozen tissue samples with a newly established UF Genetic Resources Collection. Tissues of fishes are stored in -20ºC freezers and number 4,150 samples of 900 species. All specimens and tissues are databased online and available for loan.

Water and Aqueous Solutions

1992-01-01

Arieh Ben‐Naim

A Study of Water Quality Monitoring System With Internet of Things and Machine Learning Regression Techniques

2025-06-25

Sujan Chandra Roy , Md Ashraful Islam , Ripa Sarkar +3 more | Cureus Journal of Computer Science.

Improving the accuracy of remotely sensed TSS and turbidity using quality enhanced water reflectance by a statistical resampling technique

2025-06-25

Kunwar Abhishek Singh , Dongryeol Ryu , Meenakshi Arora +2 more | International Journal of Applied Earth Observation and Geoinformation

Enhanced ammonia nitrogen filtration using NaOH-activated Manihot utilissima peel carbon: Application in recirculating aquaculture systems for Nile tilapia

2025-06-25

Said Ali Akbar , Muhammad Hasan , Zulkarnain Jalil +3 more | Chemosphere

Implementation of Internet of Things-based Water Monitoring System in Vertical System based Crab Farming

2025-06-25

Purba Daru Kusuma , Helmy Widyantara , Muhammad Dwi Hariyanto +2 more | Jurnal Abdimas

Crab is one of protein resource with high economic value. The vertical system is a crab farming method that provides several advantages including increasing space utility, minimizing crab mortality that … Crab is one of protein resource with high economic value. The vertical system is a crab farming method that provides several advantages including increasing space utility, minimizing crab mortality that is affected by cannibalism, and improving precision farming. As a continuation of 2024 research under the strategic collaboration (Katalis) scheme, a community service project has been conducted by implementing the Internet of Things (IoT) based water monitoring system to support precision farming in vertical system-based crab farming. Surabaya crab supermarket has become the partner in this community service. The objective of this activity is to implement this prototype in the real crab farming environment to investigate its effectiveness. This activity also gives experience for students at Telkom University that are involved in this project of implementing the developed precision farming system in the real environment despite the laboratories scale environment. Moreover, this project is also important to give insight from the crab farmer regarding the real problems that occur in crab farming. In the future, the system can be expanded by adding more features including the machine learning method to give predictions regarding the water quality and the growth of the crabs.

Water Pollution Monitoring, Modeling, and Management

2025-06-24

Yiting Luo , Rongkui Su | Water

Water pollution remains one of the most pressing environmental challenges of our time [...] Water pollution remains one of the most pressing environmental challenges of our time [...]

Dynamic in situ counting of farmed Holothurians based on improved YOLOv8s-ByteTrack

2025-06-24

Kexin Liu , Fang Wang , Sheng-Cheng Hong +3 more | Aquaculture International

IoT-based smart water metering and quality checking system

2025-06-24

M Vijayasabariswari , R Abinaya , V. Hemalatha +2 more | World Journal of Advanced Research and Reviews

Water scarcity is a critical global issue that demands coordinated efforts at all levels to ensure sustainable management and equitable access. A country's water utility relies on a well-functioning distribution … Water scarcity is a critical global issue that demands coordinated efforts at all levels to ensure sustainable management and equitable access. A country's water utility relies on a well-functioning distribution system, which includes water sources, treatment plants, reservoirs, pipelines, and consumers. Effective management requires consideration of water availability, quality, quantity, and reliability. As scarcity intensifies, strict regulation and accountability become essential. Various frameworks have been developed to automate different stages of water distribution. Emerging technologies, including the Internet of Things (IoT), Artificial Intelligence (AI), and Information and Communication Technology (ICT), play a key role in monitoring, analyzing, and managing water distribution networks. This study explores the impact of IoT on water distribution by analyzing modern IoT-based designs, monitoring solutions, and control mechanisms. It introduces IoTA4IWNet, an intelligent IoT-driven water network that enables real-time monitoring, automation, and regulation of water distribution. By integrating smart sensors, the system ensures optimal water flow control, minimizes waste, and enhances efficiency. Cloud-based data analytics provide real-time insights into consumption trends, leak detection, and predictive maintenance, allowing proactive decision-making. A data-driven approach enhances infrastructure resilience, reduces operational inefficiencies, and promotes long-term sustainability. IoT-driven automation in water distribution not only improves efficiency but also ensures responsible water usage. This innovative framework supports global water conservation efforts and aligns with sustainability objectives. In conclusion, leveraging IoT, AI, and ICT creates an advanced, automated, and intelligent water distribution system that fosters sustainability, enhances resource efficiency, and addresses the global water crisis effectively

Review Study on Dirt Removal Using Mechanical Cleaning Technique: Semiautomatic and Automatic

2025-06-24

José Tarcízio Gomes Filho , Patrícia Miranda , José Rogério Maciel Ferreira Filho +3 more | Revista de Gestão Social e Ambiental

Objective: To carry out a literature review to identify the main studies found on mechanical cleaning techniques, divided into semi-automatic and automatic, which may or may not use water to … Objective: To carry out a literature review to identify the main studies found on mechanical cleaning techniques, divided into semi-automatic and automatic, which may or may not use water to remove dirt from photovoltaic modules. Theoretical Framework: The research is based on the analysis of scientific articles and publications on specialized websites in recent years, to identify publications on mechanical cleaning techniques according to inclusion and exclusion criteria. Method: The methodology adopted is an integrative review of the literature using published scientific articles and technical information taken from reliable websites as sources for research, including searches for titles relevant to the topic, as well as abstracts and articles relevant to the research. Results and Discussion: The results obtained revealed that the applications of the techniques in some studies showed efficiency of up to 25% in cleaning modules, using Arduino UNO microcontrollers combined with sensors and rotating brushes to remove dirt, developing a cleaning robot prototype, in addition to carrying out mechanical tests to verify the conservation status of the surface of the modules. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence mechanical cleaning techniques. These implications may include the way dirt is removed from photovoltaic modules. Originality/Value: This study contributes to the literature with the main mechanical cleaning methods developed in recent years, combining the use or not of water to remove dirt in photovoltaic systems.

Domestic wastewater treatment using modified tripikon-S with pumice filters as support media

2025-06-23

Nico Halomoan , Siti Syakinah , Prayatni Soewondo +3 more | Journal of Ecological Engineering

Heart Rate Monitoring System for Fish Larvae Using Interframe Luminance Difference

2025-06-23

Emi Yuda , Naoya Morikawa , Yutaka Yoshida +1 more | Applied Sciences

Danionella, a transparent freshwater species belonging to the Cyprinidae family, has emerged as a valuable model organism in biological and medical research due to its optical transparency. The cardiovascular system … Danionella, a transparent freshwater species belonging to the Cyprinidae family, has emerged as a valuable model organism in biological and medical research due to its optical transparency. The cardiovascular system of Danionella larvae provides a unique opportunity for non-invasive heart rate monitoring in aquatic animals. Traditional approaches for evaluating larval heart rate often require manual or semi-automated definition of the cardiac region in video recordings. In this study, we developed a simplified heart rate monitoring system that estimates heartbeat activity by analyzing interframe luminance differences in video sequences of Danionella larvae. Our system successfully measured heart rates in the range of 150–155 beats per minute (bpm), consistent with previous findings reporting rates between 140 and 200 bpm. The non-invasive nature of this method offers significant advantages for high-throughput screening and long-term physiological monitoring. Furthermore, this system has potential applications in evaluating environmental stressors, supporting survival and health assessments, and guiding habitat management strategies to ensure stable populations of adult fish in both natural and laboratory settings.

An ensemble-driven machine learning framework for enhanced water quality classification

2025-06-23

Preet Singh , Taniya Hasija , Salil Bharany +4 more | Discover Sustainability

Deep learning driven multispectral fusion technology for water quality monitoring in Litopenaeus vannamei cultivation

2025-06-23

Jian Wang , Yin Zhang | Journal of Water Process Engineering

YOLO-PWSL-Enhanced Robotic Fish: An Integrated Object Detection System for Underwater Monitoring

2025-06-23

Lihua Lei , Ying Tang , Weidong Zhang +2 more | Applied Sciences

In recent years, China has been promoting aquaculture, but extensive water pollution caused by production activities and climate changes has resulted in losses exceeding 4.6 × 107 kg of aquatic … In recent years, China has been promoting aquaculture, but extensive water pollution caused by production activities and climate changes has resulted in losses exceeding 4.6 × 107 kg of aquatic products. Widespread water pollution from production activities is a key issue that needs to be addressed in the aquaculture industry. Therefore, dynamic monitoring of water quality and fish-specific solutions are critical to the growth of fry. Here, a low-cost, small, and real-time monitorable bionic robotic fish based on YOLO-PWSL (PConv, Wise-ShapeIoU, and LGFB) is proposed to achieve intelligent control of aquaculture. The bionic robotic fish incorporates a caudal fin for propulsion and adaptive buoyancy control for precise depth regulation. It is equipped with various types of sensors and wireless transmission equipment, which enables managers to monitor water parameters in real time. It is also equipped with YOLO-PWSL, an improved underwater fish identification model based on YOLOv5s. YOLO-PWSL integrates three key enhancements. In fact, we designed a multilevel attention fusion block (LGFB) that enhances perception in complex scenarios, to optimize the accuracy of the detected frames, the Wise-ShapeIoU loss function was used, and in order to reduce the parameters and FLOPs of the model, a lightweight convolution method called PConv was introduced. The experimental results show that it exhibits excellent performance compared with the original model: the [email protected] (mean average precision at the 0.5 IoU threshold) of the improved model reached 96.1%, the number of parameters and the amount of calculation were reduced by 1.8 M and 3.1 G, respectively, and the detected leakage was effectively reduced. In the future, the system will facilitate the monitoring of water quality and fish species and their behavior, thereby improving the efficiency of aquaculture.

A Low-Cost, Open-Source, 3D-Printed, Compact, In Situ, Automatic Water Sampler for Environmental Surveillance

2025-06-23

Miao Wang , Canwei Pang , Baiqian Shi +6 more | ACS ES&T Water

Research on Metrological Detection Device for Ultrasonic Sensor for Evaporation Measurement

2025-06-23

Tiantian Zhou , Mingming Wei , Xingwang Chen +2 more | MAPAN

Analysis of Treatment Unit Selection in The Design of The Water Treatment Plant (III) Karawang Branch, East Karawang District

2025-06-22

Malvin Liandi , Rositayanti Hadisoebroto , Winarni Winarni | INFOMATEK

The Drinking Water Treatment Plant (III) Karawang Branch was developed to increase production capacity and ensure an adequate water supply for the Karawang Service Area. The raw water for this … The Drinking Water Treatment Plant (III) Karawang Branch was developed to increase production capacity and ensure an adequate water supply for the Karawang Service Area. The raw water for this plant is sourced from the West Branch North Tarum Channel (STUB) and has a design production capacity of 100 L/s. The design aims to implement optimal treatment processes to meet the required drinking water quality standards. This study investigates the selection of treatment units for the plant, focusing on raw water quality as the primary criterion to meet the drinking water standards stipulated by Ministry of Health Regulation No. 2 Year 2023. Key water quality parameters that do not meet these standards include total suspended solids (TSS), total dissolved solids (TDS), chemical oxygen demand (COD), biochemical oxygen demand (BOD), dissolved oxygen (DO), sulfide, color, detergent, fecal coliform, and total coliform. The selection of treatment units was conducted using the Water Quality-Based Approach, which considers specific contaminants in the raw water, along with the Literature-Based Approach, involving a review of existing water treatment plants and their efficiency in similar settings. The chosen treatment units include an intake system, hydraulic coagulation, hydraulic flocculation, sedimentation with plate settlers, dual-media rapid sand filtration, chlorination disinfection, and a ground reservoir for water storage. This study contributes to ensuring a sustainable and safe drinking water supply for the Karawang region through an integrated water treatment system.

Low visibility underwater biological target detection based on the improved YOLOV5s

2025-06-22

Huixian Lin , Haidong Deng , Hong Du +2 more | The Visual Computer

Using Hybrid Machine Learning to Predict Wastewater Effluent Quality and Ensure Treatment Plant Stability

2025-06-21

Zhaoyang Xiong , Xingyang Liu , Thomas Igou +2 more | Water

The accurate prediction of wastewater quality parameters is pivotal for evaluating the treatment stability of processes and for ensuring regulatory compliance in wastewater treatment plants. A singular machine learning model … The accurate prediction of wastewater quality parameters is pivotal for evaluating the treatment stability of processes and for ensuring regulatory compliance in wastewater treatment plants. A singular machine learning model often faces challenges in fully capturing and extracting the complex nonlinear relationships inherent in multivariate time series data. To overcome this limitation, this study proposes a dual hybrid modeling framework that effectively integrates LSTM and XGBoost models, leveraging their complementary strengths. The first hybrid model refines the residues to utilize the information, whereas the second hybrid model enhances the input features by extracting temporal dependencies. A comparative analysis against three standalone models reveals that the proposed hybrid framework consistently outperforms them in both predictive accuracy and generalization ability across four key effluent indicators—chemical oxygen demand, ammonia nitrogen, total nitrogen, and total phosphorus. These results demonstrate that the proposed hybrid machine learning framework has great potential to be used to evaluate process stability in wastewater treatment plants, paving a way for smarter, more resilient, and more sustainable wastewater management, which will improve ecological integrity and regulatory compliance.

High-precision counting method of moving sheep flock based on YOLOV8n-MEB + ByteTrack-CD and diversion channel

2025-06-21

Yi Xue , Yinggang Shen , Dandan Ma +7 more | Computers and Electronics in Agriculture

ANALISIS KUALITAS AIR SUNGAI SEPAKU SEBAGAI PENYEDIA AIR BERSIH DI IBU KOTA NUSANTARA (IKN), KALIMANTAN TIMUR

2025-06-21

Fachruddin Azwari , Martha Ekawati Siahaya , Kemala Hadidjah +2 more | Jurnal Nusa Sylva

Sepaku River is one of the primary water resources planned to meet the raw water needs of Nusantara Capital City (IKN) in East Kalimantan, Indonesia. This study aims to analyze … Sepaku River is one of the primary water resources planned to meet the raw water needs of Nusantara Capital City (IKN) in East Kalimantan, Indonesia. This study aims to analyze the water quality of the Sepaku River based on physical, chemical, and microbiological parameters, and to evaluate the differences in water quality at three locations: upstream, midstream, and downstream. The parameters analyzed include pH, Total Suspended Solids (TSS), Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Total Coliform. Data were collected through field surveys and laboratory tests, and analyzed using One-Way ANOVA and Spearman's Rank Correlation. The results show that while the pH levels still meet the water quality standards, TSS, BOD, and Total Coliform exceed the established thresholds. The ANOVA test indicates a significant difference in TSS among the sampling locations, while other parameters show widespread contamination. The Spearman Correlation reveals significant relationships between TSS and BOD, and between BOD and Total Coliform. These findings indicate that pollution in the Sepaku River is complex and interrelated across different parameters. Therefore, integrated and ecosystem-based water quality management is required to support the provision of safe and sustainable raw water for Nusantara Capital City.

Arowana cultivation water quality forecasting with multivariate fuzzy timeseries and internet of things

2025-06-20

Alauddin Maulana Hirzan , April Firman Daru , Lenny Margaretta Huizen | Computer Science and Information Technologies

Water quality plays a crucial role in the growth and survival of arowana fish, with imbalances in key parameters (pH, temperature, turbidity, dissolved oxygen, and conductivity) leading to increased mortality … Water quality plays a crucial role in the growth and survival of arowana fish, with imbalances in key parameters (pH, temperature, turbidity, dissolved oxygen, and conductivity) leading to increased mortality rates. While previous studies have introduced various monitoring models using Arduino IDE and intrinsic approaches, they lack predictive capabilities, leaving cultivators unable to take proactive measures. To address this gap, this study develops a predictive model integrating the internet of things (IoT) with a fuzzy time series (FTS) algorithm. Through rigorous evaluation and validation, the proposed FTS-multivariate T2 model demonstrated superior performance, achieving an exceptionally low error rate of 0.01704%, outperforming decision tree (0.13410%), FTS-multivariate T1 (0.88397%), and linear regression (20.91791%). These findings confirm that FTS-multivariate T2 not only accurately predicts water quality but also significantly reduces the mean absolute percentage error, providing a robust solution for sustainable arowana aquaculture.

HydroNet: A Novel Hybrid CNN-Transformer Architecture for High-Precision Water Quality Classification with Feature Fusion

2025-06-20

| International journal of intelligent engineering and systems

Application of AI and ML in Water Quality Monitoring System

2025-06-20

Pragati Priyadarshinee | Apple Academic Press eBooks

Sustainable wastewater treatment with AI: a path to enhanced hygiene and environmental protection

2025-06-20

K. Anbarasu , Yuvarajan Devarajan | Process Safety and Environmental Protection

Quantifying turbidity dynamics in lake water using OLS regression: A landsat 8 OLI-based remote sensing approach

2025-06-20

Imran Ahmad , Amnah A. Alasgah , Martina Zeleňáková +3 more | Journal of Hydrology Regional Studies

Reviewing seas of data: Integrating image‐based bio‐logging and artificial intelligence to enhance marine conservation

2025-06-20

Marianna Chimienti , Akiko Kato , Vahid Seydi +7 more | Methods in Ecology and Evolution

Abstract Conservation of marine ecosystems can be improved through a better understanding of ecosystem functioning, particularly the cryptic underwater behaviours and interactions of marine predators. Image‐based bio‐logging devices (including images, … Abstract Conservation of marine ecosystems can be improved through a better understanding of ecosystem functioning, particularly the cryptic underwater behaviours and interactions of marine predators. Image‐based bio‐logging devices (including images, videos and active acoustic) are increasingly used to monitor wildlife movements, foraging behaviours and their environment, but generate complex datasets needing efficient analytical tools. We review advances in image‐based bio‐logging technology for ecological studies on marine fauna. Emphasis is placed on the diversity of data collected, merging research questions, challenges in image processing, and integration of Artificial Intelligence (AI) methods. Image‐based system issues, such as exposure, focus, blurriness, colour balance, moving background, perspective and scale variability are even more challenging in underwater images where conditions change constantly and cannot be controlled. We list computer vision tools and algorithms available for analyses of underwater images, including enhanced tracking algorithms that recognise objects and treat images as a time series. Although AI and computer vision methods offer ample and robust analytical solutions for (semi‐) automated image processing, their uptake by marine ecologists has been slow. Collaboration among ecologists, modellers, statisticians, engineers and computer scientists is needed to integrate ecological questions, data selection and computational methodology. We propose a four‐phase framework for image data processing and analysis (video checking and manipulation, image processing, image labelling and model development) accompanied by detailed python code. We also outline the additional complications in aligning the diverse scalar movement metrics from bio‐loggers along with image‐based data, such as acceleration, depth and location, which typically are collected at different resolutions. Building analytical frameworks for on‐board image data collection (e.g. lightweight models) is also explored. We advocate for a collaborative research community at the Ecology‐AI interface, emphasising sharing and exchange of both data and tools to drive cross‐disciplinary innovation. Beyond the Ecology‐AI interface, we pave the path for the application of insights from image‐based bio‐logging technology enabling collaboration among scientists, conservation managers, and policymakers. Systematic applications of computer vision tools to image‐based bio‐logging technology will enhance the power these data hold, informing about the status of marine ecosystems, testing and developing ecological theory and aiding conservation.

Design of IoT-Based Water Quality Monitoring System in Freshwater Ornamental Fish Ponds

2025-06-20

Shania Bakhtiar Paturusi , Andi Susilo | Journal Technology Information and Data Analytic

This study focuses on designing an IoT-enabled monitoring system to enhance water quality management in freshwater ornamental fish ponds, with an emphasis on tracking temperature, pH, and total dissolved solids … This study focuses on designing an IoT-enabled monitoring system to enhance water quality management in freshwater ornamental fish ponds, with an emphasis on tracking temperature, pH, and total dissolved solids (TDS). Utilizing an ESP32 microcontroller along with DS18B20, pH, and TDS sensors, the system collects and transmits real-time water quality data via the Blynk platform. The findings demonstrate that the system effectively monitors temperature, pH, and TDS levels, initiating corrective actions like activating a water heater or solenoid valve when needed. By automating these processes, the system minimizes the need for manual checks, improves resource efficiency, and supports optimal guppy fish farming conditions.

CMUNet neural network-based water body survey management upstream of hydropower station

2025-06-19

Yanling Qiu , H. Tian , A. P. Xuliang Duan +2 more | Earth Science Informatics

Natural Coagulants as an Efficient Alternative to Chemical Ones for Continuous Treatment of Aquaculture Wastewater

2025-06-19

Isabella T. Tomasi , Rui A.R. Boaventura , Cidália M.S. Botelho | Applied Sciences

Aquaculture effluents are a growing source of water pollution, releasing suspended solids, organic matter, nitrogen, and phosphorus into aquatic environments. Recirculating aquaculture systems (RASs) have emerged as a more sustainable … Aquaculture effluents are a growing source of water pollution, releasing suspended solids, organic matter, nitrogen, and phosphorus into aquatic environments. Recirculating aquaculture systems (RASs) have emerged as a more sustainable solution, allowing water to be continuously treated and reused. Within RASs, coagulation–flocculation is a key treatment step due to its simplicity and effectiveness. Tannin-based coagulants have gained attention as natural alternatives to traditional chemical agents. Although natural coagulants have been studied in aquaculture, only a few works explore their use in continuous-flow systems. This study evaluates a chestnut shell-based (CS) coagulant applied in continuous mode for the post-treatment of aquaculture effluent. The performance of CS was compared with Tanfloc, aluminum sulfate, and ferric chloride in removing color and dissolved organic carbon (DOC). At natural pH (6.5) and 50 mg·L−1, CS and Tanfloc achieved color removal of 61.0% and 65.5%, respectively, outperforming chemical coagulants. For DOC, Tanfloc and chemical coagulants removed 45–50%, while CS removed 32%. All coagulants removed over 90% of phosphorus, but nitrogen removal was limited (30–40%). These results highlight the potential of tannin-derived coagulants, particularly from agro-industrial residues, as sustainable solutions for aquaculture wastewater treatment in continuous systems.

Hierarchical pyramid refined U-Net for creating the first 2 m resolution multi-class national-scale spatial distribution dataset of offshore observable marine aquaculture in China

2025-06-19

Yanlin Chen , Guojin He , Ranyu Yin +2 more | International Journal of Digital Earth

Decentralized Communication-Free Controller for Synchronous Solar-Powered Water Pumping with Emulated Neighbor Sensing

2025-06-18

Roungsan Chaisricharoen , Wanus Srimaharaj , Punnarumol Temdee +2 more | Sensors

Solar-powered pumping systems using series pumps are commonly applied in the delivery of water to remote agricultural regions, particularly in hilly tropical terrain. The synchronization of these pumps typically depends … Solar-powered pumping systems using series pumps are commonly applied in the delivery of water to remote agricultural regions, particularly in hilly tropical terrain. The synchronization of these pumps typically depends on reliable communication; however, dense vegetation, elevation changes, and weather conditions often disrupt signals. To address these limitations, a fully decentralized, communication-free control system is proposed. Each pumping station operates independently while maintaining synchronized operation through emulated neighbor sensing. The system applies a discrete-time control algorithm with virtual sensing that estimates neighboring pump statuses. Each station consists of a solar photovoltaic (PV) array, variable-speed drive, variable inlet valve, reserve tank, and local control unit. The controller adjusts the valve positions and pump power based on real-time water level measurements and virtual neighbor sensing. The simulation results across four scenarios, including clear sky, cloudy conditions, temporary outage, and varied irradiance, demonstrated steady-state operation with no water overflow or shortage and a steady-state error less than 4% for 3 m3 transfer. The error decreased as the average power increased. The proposed method maintained system functionality under simulated power outage and variable irradiance, confirming its suitability for remote agricultural areas where communication infrastructure is limited.

Image Segmentation and Measurement of Trout Using a Convolutional Neural Network and Transformer Architecture

2025-06-18

J. E. Cruz , Luis Baca , Raúl Ovidio Castillo Pinto +3 more | Applied Sciences

Aquaculture plays a vital role in meeting global food demands, necessitating technological innovations for sustainable production. This study investigates deep learning-based semantic image segmentation for enhanced monitoring of rainbow trout … Aquaculture plays a vital role in meeting global food demands, necessitating technological innovations for sustainable production. This study investigates deep learning-based semantic image segmentation for enhanced monitoring of rainbow trout (Oncorhynchus mykiss) in Puno, Peru. We conducted three experiments using UNET and UNETR architectures, varying image resolution, loss functions, and optimizers on a dataset of 1200 high-resolution images. Experiment 1, with UNET and 256 × 256 pixel images, achieved an IoU of 0.942854 after 20 epochs, using MSELoss and Adam, demonstrating superior segmentation accuracy. Experiment 2, utilizing UNET with 512 × 512 pixel images, resulted in an IoU of 0.803244 after 50 epochs, with L1Loss and Adam, indicating satisfactory performance despite increased complexity. Experiment 3, employing UNETR with 256 × 256 pixel images, yielded lower IoU scores, with a best IoU of 0.253928, highlighting the challenge of training Transformer-based models with limited data. A critical aspect of this study was the use of a coin as a scale reference in all experiments, enabling precise conversion of pixel measurements to physical dimensions. This, combined with OpenCV for contour detection, allowed for accurate fish size estimations, validated by comparisons with real images. The results underscore UNET’s effectiveness for aquaculture image segmentation, while also emphasizing data requirements for UNETR. This approach provides a non-invasive, automated method for monitoring fish growth and health, contributing to sustainable aquaculture practices.

Predictive modelling of aquaculture water quality using IoT and advanced machine learning algorithms

2025-06-18

Md. Abdullah Al Mamun Hridoy , Chiara Bordin , A. Masood +1 more | Results in Chemistry

A microtiter plate method to optimize the concentration and exposure time of potassium permanganate (KMnO4) for disinfecting fishing nets

2025-06-18

Madhusudana Rao Badireddy , Ahamed Basha Kusunur , P. Viji | Aquaculture International

Water Quality Classification Using SVM And XGBoost Method

2025-06-18

Beldar Faijan Shaikh Akil | INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT

– This project focuses on the classification of water quality using machine learning methods—Support Vector Machine (SVM) and XGBoost. The system uses various chemical indicators like pH, dissolved oxygen, turbidity, … – This project focuses on the classification of water quality using machine learning methods—Support Vector Machine (SVM) and XGBoost. The system uses various chemical indicators like pH, dissolved oxygen, turbidity, and conductivity to predict the water quality status. The dataset is preprocessed and important features are extracted before being passed into the models. After evaluating multiple models, XGBoost showed higher accuracy and robustness compared to SVM. The system aims to help environmental authorities monitor and improve water resources more effectively. Key Words: Water Quality, Machine Learning, SVM, XGBoost, Classification

Flexible multimode sensing system for fish stress quantitative monitoring under adversity stress

2025-06-17

Wentao Huang , Branko Glamuzina , Goran Stojanović +2 more | Computers and Electronics in Agriculture

Effect of air inlet velocity on air water harvester with small tube evaporator

2025-06-17

Mirmanto Mirmanto , Anang Suriatman , Made Nuarsa | Global Journal of Engineering and Technology Advances

During the dry season, parts of Indonesia experience drought and clean water crises. One of the efforts to obtain clean water was by presenting a machine called air-water harvester. The … During the dry season, parts of Indonesia experience drought and clean water crises. One of the efforts to obtain clean water was by presenting a machine called air-water harvester. The amount of water mass produced depended on several variables such as RH, intake air temperature, type of condensing unit, intake air velocity and engine power. This study aims to determine the performance of the air-water harvester at various inlet air velocities. The dependent variables expected were the mass of water produced, COP, and the amount of heat absorbed from the air. This research was carried out experimentally with the working fluid refrigerant R134a. The compressor used was a rotary type 1 PK compressor. This study varied the air velocity entering the evaporator, namely 1.5 m/s, 3 m/s and 4.5 m/s. The results showed that the highest mass of water was 0.728 kg. Meanwhile, the highest COP was 5.13, and the total heat transfer rate absorbed by the evaporator was 160.38 W. All were obtained at the air velocity of 4.5 m/s.

Hybrid deep learning and machine learning framework for high-precision water quality prediction in urban systems

2025-06-17

Tian Huang , Ka Yin Chau , Zhan Su +1 more | Environment Development and Sustainability

Satiety index detection for individual juvenile fish based on fitted abdominal curve

2025-06-17

Yao Wu , Xiaochan Wang , Xiaolei Zhang +5 more | Computers and Electronics in Agriculture

YOLOv8-BaitScan: A Lightweight and Robust Framework for Accurate Bait Detection and Counting in Aquaculture

2025-06-17

Jiandong Li , Zehao Zhang , Yanan Wei +1 more | Fishes

Excessive bait wastage is a major issue in aquaculture, leading to higher farming costs, economic losses, and water pollution caused by bacterial growth from unremoved residual bait. To address this … Excessive bait wastage is a major issue in aquaculture, leading to higher farming costs, economic losses, and water pollution caused by bacterial growth from unremoved residual bait. To address this problem, we propose a bait residue detection and counting model named YOLOv8-BaitScan, based on an improved YOLO architecture. The key innovations are as follows: (1) By incorporating the channel prior convolutional attention (CPCA) into the final layer of the backbone, the model efficiently extracts spatial relationships and dynamically allocates weights across the channel and spatial dimensions. (2) The minimum points distance intersection over union (MPDIoU) loss function improves the model’s localization accuracy for bait bounding boxes. (3) The structure of the Neck network is optimized by adding a tiny-target detection layer, which improves the recall rate for small, distant bait targets and significantly reduces the miss rate. (4) We design the lightweight detection head named Detect-Efficient, incorporating the GhostConv and C2f-GDC module into the network to effectively reduce the overall number of parameters and computational cost of the model. The experimental results show that YOLOv8-BaitScan achieves strong performance across key metrics: The recall rate increased from 60.8% to 94.4%, mAP@50 rose from 80.1% to 97.1%, and the model’s number of parameters and computational load were reduced by 55.7% and 54.3%, respectively. The model significantly improves the accuracy and real-time detection capabilities for underwater bait and is more suitable for real-world aquaculture applications, providing technical support to achieve both economic and ecological benefits.

Integrated Sensor Platform for Real-time Monitoring of Nitrate, Ammonium, Temperature, and pH in Aquatic Environments

2025-06-16

Syed Azeem Inam , Shah Zayed Riam , Md Najmul Islam +4 more | Talanta