Evidence map›Paper›PMID 38257587›Full record

ArticleSensors (Basel, Switzerland)2024

IoT Water Quality Monitoring and Control System in Moving Bed Biofilm Reactor to Reduce Total Ammonia Nitrogen.

Putu A Suriasni, Ferry Faizal, Wawan Hermawan, Ujang Subhan, Camellia Panatarani, I Made Joni

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
2.6field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 13 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Putu A SuriasniDepartment of Physics, Faculty of Mathematics and Natural Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia.
Ferry FaizalDepartment of Physics, Faculty of Mathematics and Natural Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia.ORCID 0000-0001-5660-1049
Wawan HermawanFunctional Nano Powder University Center of Excellence (FiNder U-CoE), Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia.
Ujang SubhanFunctional Nano Powder University Center of Excellence (FiNder U-CoE), Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia.
Camellia PanataraniDepartment of Physics, Faculty of Mathematics and Natural Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia.
I Made JoniDepartment of Physics, Faculty of Mathematics and Natural Science, Padjadjaran University, Jalan Raya Bandung-Sumedang KM 21, Sumedang 45363, West Java, Indonesia.ORCID 0000-0001-5949-3418
Padjadjaran University · ID

Funding

Padjadjaran University 1959/UN6.3.1/PT.00/2023Padjadjaran University 2203/UN6.3.1/PT.00/2022
6 · The paper itself

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.

Indexed as

AmmoniaInternet of ThingsAnimalsBiofilmsBioreactorsOxygenWater QualityAmmoniaOxygenbiofilterbubble diffuserInternet of Things (IoT)MBBRRASTAN

Identifiers

PMID38257587
PMCPMC10819107
OpenAlexW4390818482

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.