Evidence map›Paper›PMID 33916901›Full record

ArticleSensors (Basel, Switzerland)2021

Developing a Modern Greenhouse Scientific Research Facility-A Case Study.

Davor Cafuta, Ivica Dodig, Ivan Cesar, Tin Kramberger

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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. Article
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

4 authors.

Davor CafutaDepartment of Information Technology and Computing, Zagreb University of Applied Sciences, 10000 Zagreb, Croatia.ORCID 0000-0001-9105-6699
Ivica DodigDepartment of Information Technology and Computing, Zagreb University of Applied Sciences, 10000 Zagreb, Croatia.ORCID 0000-0002-3005-9949
Ivan CesarDepartment of Information Technology and Computing, Zagreb University of Applied Sciences, 10000 Zagreb, Croatia.
Tin KrambergerDepartment of Information Technology and Computing, Zagreb University of Applied Sciences, 10000 Zagreb, Croatia.ORCID 0000-0001-5585-970X

Funding

Hrvatska Zaklada za Znanost IP-2019-04
6 · The paper itself

Abstract

Multidisciplinary approaches in science are still rare, especially in completely different fields such as agronomy science and computer science. We aim to create a state-of-the-art floating ebb and flow system greenhouse that can be used in future scientific experiments. The objective is to create a self-sufficient greenhouse with sensors, cloud connectivity, and artificial intelligence for real-time data processing and decision making. We investigated various approaches and proposed an optimal solution that can be used in much future research on plant growth in floating ebb and flow systems. A novel microclimate pocket-detection solution is proposed using an automatically guided suspended platform sensor system. Furthermore, we propose a methodology for replacing sensor data knowledge with artificial intelligence for plant health estimation. Plant health estimation allows longer ebb periods and increases the nutrient level in the final product. With intelligent design and the use of artificial intelligence algorithms, we will reduce the cost of plant research and increase the usability and reliability of research data. Thus, our newly developed greenhouse would be more suitable for plant growth research and production.

Indexed as

AlgorithmsArtificial IntelligenceGreenhouse EffectReproducibility of Resultsartificial intelligencecloud computinginternet of thingssensors smart agriculture

Identifiers

PMID33916901
PMCPMC8067565

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.