Evidence map›Paper›PMID 35957430›Full record

ArticleSensors (Basel, Switzerland)2022

Self-Sufficient Sensor Node Embedding 2D Visible Light Positioning through a Solar Cell Module.

Irene Cappelli, Federico Carli, Ada Fort, Federico Micheletti, Valerio Vignoli, Mara Bruzzi

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. The Structural and Electrochemical Properties of CuCoONanomaterials (Basel, Switzerland) · 2023
    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

6 authors.

Irene CappelliDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.ORCID 0000-0001-8660-7708
Federico CarliDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.ORCID 0000-0003-3891-9779
Ada FortDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.ORCID 0000-0003-0916-1516
Federico MichelettiDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.ORCID 0000-0001-7158-0442
Valerio VignoliDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.ORCID 0000-0003-2509-6566
Mara BruzziDepartment of Physics and Astronomy, University of Florence, 50019 Florence, Italy.ORCID 0000-0001-7344-8365

Funding

Fondazione Cassa di Risparmio di Firenze 45597 2020.1606
6 · The paper itself

Abstract

Nowadays, indoor positioning (IP) is a relevant aspect in several scenarios within the Internet of Things (IoT) framework, e.g., Industry 4.0, Smart City and Smart Factory, in order to track, amongst others, the position of vehicles, people or goods. This paper presents the realization and testing of a low power sensor node equipped with long range wide area network (LoRaWAN) connectivity and providing 2D Visible Light Positioning (VLP) features. Three modulated LED (light emitting diodes) sources, the same as the ones commonly employed in indoor environments, are used. The localization feature is attained from the received light intensities performing optical channel estimation and lateration directly on the target to be localized, equipped with a low-power microcontroller. Moreover, the node exploits a solar cell, both as optical receiver and energy harvester, provisioning energy from the artificial lights used for positioning, thus realizing an innovative solution for self-sufficient indoor localization. The tests performed in a ~1 m

Indexed as

SunlightHumansenergy harvestingindoor positioningIoTLoRaWANlow powerphotovoltaicultra-low powervisible light positioning

Identifiers

PMID35957430
PMCPMC9371190

What OpenQuestion holds

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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.