ArticleSensors (Basel, Switzerland)2024
IoT Water Quality Monitoring and Control System in Moving Bed Biofilm Reactor to Reduce Total Ammonia Nitrogen.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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Who cites it
0 citing papers in PubMed, 13 citations in OpenAlex.
No citing paper in PubMed yet.
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Traditional aquaculture systems appear challenged by the high levels of total ammoniacal nitrogen (TAN) produced, which can harm aquatic life. As demand for global fish production continues to increase, farmers should adopt recirculating aquaculture systems (RAS) equipped with biofilters to improve the water quality of the culture. The biofilter plays a crucial role in ammonia removal. Therefore, a biofilter such as a moving bed biofilm reactor (MBBR) biofilter is usually used in the RAS to reduce ammonia. However, the disadvantage of biofilter operation is that it requires an automatic system with a water quality monitoring and control system to ensure optimal performance. Therefore, this study focuses on developing an Internet of Things (IoT) system to monitor and control water quality to achieve optimal biofilm performance in laboratory-scale MBBR. From 35 days into the experiment, water quality was maintained by an aerator's on/off control to provide oxygen levels suitable for the aquatic environment while monitoring the pH, temperature, and total dissolved solids (TDS). When the amount of dissolved oxygen (DO) in the MBBR was optimal, the highest TAN removal efficiency was 50%, with the biofilm thickness reaching 119.88 μm. The forthcoming applications of the IoT water quality monitoring and control system in MBBR enable farmers to set up a system in RAS that can perform real-time measurements, alerts, and adjustments of critical water quality parameters such as TAN levels.
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Registered trials
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