ArticleEnvironmental monitoring and assessment2022
Online water quality monitoring based on UV-Vis spectrometry and artificial neural networks in a river confluence near Sherfield-on-Loddon.
Article in Environmental monitoring and assessment, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Advancements in Monitoring Water Quality Based on Various Sensing Methods: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- An open-source spectral measurement platform for plant reflectance and material identification.HardwareX · 2026Article
- Integrating Artificial Intelligence in Environmental Monitoring: A Paradigm Shift in Data-Driven Sustainability.EcoHealth · 2026Review
- A Portable UV-LED/RGB Sensor for Real-Time Bacteriological Water Quality Monitoring Using ML-Based MPN Estimation.Biosensors · 2025Article
- Spectrochip-based Calibration Curve Modeling (CCM) for Rapid and Accurate Multiple Analytes Quantification in Urinalysis.Heliyon · 2024Article
- Using Surrogate Parameters to Enhance Monitoring of Community Wastewater Management System Performance for Sustainable Operations.Sensors (Basel, Switzerland) · 2024Article
- Development of statistical regression and artificial neural network models for estimating nitrogen, phosphorus, COD, and suspended solid concentrations in eutrophic rivers using UV-Vis spectroscopy.Environmental monitoring and assessment · 2023Article
- Reflectance Spectroscopy for the Classification and Prediction of Pigments in Agronomic Crops.Plants (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Water quality monitoring is very important in agricultural catchments. UV-Vis spectrometry is widely used in place of traditional analytical methods because it is cost effective and fast and there is no chemical waste. In recent years, artificial neural networks have been extensively studied and used in various areas. In this study, we plan to simplify water quality monitoring with UV-Vis spectrometry and artificial neural networks. Samples were collected and immediately taken back to a laboratory for analysis. The absorption spectra of the water sample were acquired within a wavelength range from 200 to 800 nm. Convolutional neural network (CNN) and partial least squares (PLS) methods are used to calculate water parameters and obtain accurate results. The experimental results of this study show that both PLS and CNN methods may obtain an accurate result: linear correlation coefficient (R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.