Evidence map›Paper›PMID 38384310›Full record

ArticleData in brief2024

Raw GNSS data collected using smartphones and low-cost receiver under optimal and sub-optimal conditions.

Julián Tomaštík, Matej Varga, Tim Everett

Abstract read
In one paragraph

Article in Data in brief, 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
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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

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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

3 authors.

Julián TomaštíkFaculty of Forestry, Technical University in Zvolen, T.G. Masaryka 24, Zvolen 96001, Slovakia.
Matej VargaETH Zurich, Institute of Geodesy and Photogrammetry, Stefano-Franscini-Platz 5, Zurich 8093, Switzerland.
Tim EverettRTK Consultants LLC, Niwot, CO 80503, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The miniaturisation and decrease of price are amongst the main current trends in the area of Global Navigation Satellite Systems (GNSS) receivers. Besides standalone receivers also receivers incorporated into Android devices can provide raw GNSS measurements thus enabling much wider options, formerly restricted to devices of much higher price. The article describes two datasets. The first was collected using a Xiaomi Mi 8 smartphone with and without application of a simple ground plane. In the second we compared a smartphone receiver (Google Pixel 5) with a standalone low-cost receiver (u-Blox ZED F9P). In both cases the datasets consist of multiple measurement sessions, also considering the conditions where the reception of GNSS signals was obstructed by trees' canopy. The datasets are focused on repeatability (multiple measurements), influence of external conditions (canopy and foliage state) and the devices used.

Indexed as

Adverse conditionsGlobal navigation satellite systemsLow-cost receiversRaw data

Identifiers

PMID38384310
PMCPMC10879807

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.