Evidence map›Paper›PMID 37631662›Full record

ArticleSensors (Basel, Switzerland)2023

Image-Based Sensor for Liquid Level Monitoring during Bottling with Application to Craft and Home-Brewing.

Josip Musić, Ivo Stančić, Barbara Džaja, Vesna Pekić

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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
–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

0 citing papers in PubMed.

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

4 authors.

Josip MusićFaculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, R. Boškovića 32, 21000 Split, Croatia.ORCID 0000-0002-9185-5762
Ivo StančićFaculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, R. Boškovića 32, 21000 Split, Croatia.ORCID 0000-0001-9607-1791
Barbara DžajaDepartment of Professional Studies, University of Split, Kopilica 5, 21000 Split, Croatia.ORCID 0000-0002-7106-2095
Vesna PekićFaculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, R. Boškovića 32, 21000 Split, Croatia.

Funding

European regional development fund (ERDF) Innovation KK.03.2.2.03.0326
6 · The paper itself

Abstract

Although craft and home brewing have fueled the beer renaissance in the last decade, affordable, reliable, and simple sensing equipment for such breweries is limited. Thus, this manuscript is motivated by the improvement of the bottle-filling process in such settings with the objective of developing a liquid level sensor based on a novel application of the known optical phenomena of light refraction. Based on the different refraction indices of liquid and air (and critical angle based on Snell's law), along with a novel LED light source positioning, a reliable liquid level sensor system was built with the aid of an embedded microcontroller. The used operating principle is general and can be used in applications other than the proposed one. The proposed method was extensively tested in a laboratory and limited production settings with a speed of 7 Hz using different liquids and container shapes. It was compared for accuracy to other sensing principles such as ultrasound, infrared, and time-of-flight. It demonstrated comparable or better performance with a height error ranging between -0.1534 mm in static conditions and 1.608 mm for realistic dynamic conditions and good repeatability on the production line with a 4.3 mm standard deviation of the mean.

Indexed as

bottlinghome-brewingliquid level measurementmachine visionoptical refractionoptoelectronic sensors

Identifiers

PMID37631662
PMCPMC10459823

What OpenQuestion holds

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LicenceCC BY
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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.