Evidence map›Paper›PMID 42198045›Full record

ArticleSensors (Basel, Switzerland)2026

An Intelligent IoT-Based Predictive Control System for Water Quality and Energy Management in Koi Aquaculture.

Kunyanuth Kularbphettong, Nutthapat Kaewrattanapat, Nareenart Raksuntorn

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. Review
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

3 authors.

Kunyanuth KularbphettongComputer Science Program, Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok 10300, Thailand.ORCID 0000-0003-2796-0514
Nutthapat KaewrattanapatDigital Technology for Education Program, Faculty of Education, Suan Sunandha Rajabhat University, Bangkok 10300, Thailand.
Nareenart RaksuntornComputer Science Program, Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok 10300, Thailand.

Funding

Suan Sunandha Rajabhat University 1970
6 · The paper itself

Abstract

Reducing energy consumption while maintaining stable water quality remains a major challenge in ornamental aquaculture. This study proposes an integrated predictive and energy-aware aquaculture management framework combining Internet of Things (IoT) sensing, Long Short-Term Memory (LSTM)-based prediction, Digital Twin (DT) simulation, and Cyber-Physical System (CPS) control. Real-time sensor networks monitored dissolved oxygen (DO), ammonia (NH

Indexed as

Cyber-Physical SystemsDigital Twinenergy-aware managementIoT-based sensingLSTMpredictive controlsmart aquaculture

Identifiers

PMID42198045
PMCPMC13210448

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.