ArticleSensors (Basel, Switzerland)2023
Development of Innovative Online Modularized Device for Turbidity Monitoring.
Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Remediation and upcycling of microplastics by algae with wastewater nutrient removal and bioproduction potential.Nature communications · 2025Article
- An Intelligent Water Monitoring IoT System for Ecological Environment and Smart Cities.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Given progress in water-quality analytical technology and the emergence of the Internet of Things (IoT) in recent years, compact and durable automated water-quality monitoring devices have substantial market potential. Due to susceptibility to the influence of interfering substances, which lowers measurement accuracy, existing automated online monitoring devices for turbidity, a key indicator of a natural water body, feature a single light source and are thus insufficient for more complicated water-quality measurement. The newly developed modularized water-quality monitoring device boasts dual light sources (VIS/NIR), capable of measuring the intensity of scattering, transmission, and reference light at the same time. Coupled with a water-quality prediction model, it can attain a good estimate for continuing monitoring of tap water (<2 NTU, error < 0.16 NTU, relative error < 19.6%) and environmental water samples (<400 NTU, error < 3.86 NTU, relative error < 2.3%). This indicates the optical module can both monitor water quality in low turbidity and provide water-treatment information alerts in high turbidity, thereby materializing automated water-quality monitoring.
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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.