Evidence map›Paper›PMID 34770653›Full record

ArticleSensors (Basel, Switzerland)2021

Flexible IoT Gas Sensor Node for Automated Life Science Environments Using Stationary and Mobile Robots.

Sebastian Neubert, Thomas Roddelkopf, Mohammed Faeik Ruzaij Al-Okby, Steffen Junginger, Kerstin Thurow

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 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

5 authors.

Sebastian NeubertInstitute of Automation, University of Rostock, 18119 Rostock, Germany.
Thomas RoddelkopfInstitute of Automation, University of Rostock, 18119 Rostock, Germany.
Mohammed Faeik Ruzaij Al-OkbyCenter of Life Science Automation (celisca), 18119 Rostock, Germany.ORCID 0000-0001-8084-6361
Steffen JungingerInstitute of Automation, University of Rostock, 18119 Rostock, Germany.
Kerstin ThurowCenter of Life Science Automation (celisca), 18119 Rostock, Germany.ORCID 0000-0002-3281-1065

Funding

European Research Council 856405
6 · The paper itself

Abstract

In recent years the degree of automation in life science laboratories increased considerably by introducing stationary and mobile robots. This trend requires intensified considerations of the occupational safety for cooperating humans, since the robots operate with low volatile compounds that partially emit hazardous vapors, which especially do arise if accidents or leakages occur. For the fast detection of such or similar situations a modular IoT-sensor node was developed. The sensor node consists of four hardware layers, which can be configured individually regarding basic functionality and measured parameters for varying application focuses. In this paper the sensor node is equipped with two gas sensors (BME688, SGP30) for a continuous TVOC measurement. In investigations under controlled laboratory conditions the general sensors' behavior regarding different VOCs and varying installation conditions are performed. In practical investigations the sensor node's integration into simple laboratory applications using stationary and mobile robots is shown and examined. The investigation results show that the selected sensors are suitable for the early detection of solvent vapors in life science laboratories. The sensor response and thus the system's applicability depends on the used compounds, the distance between sensor node and vapor source as well as the speed of the automation systems.

Indexed as

Biological Science DisciplinesRoboticsGasesHumansSolventsGasesSolventsautomationgas detectionIoTlaboratorylife sciencemobile robotsensor node

Identifiers

PMID34770653
PMCPMC8587426

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.