Evidence map›Paper›PMID 36560163›Full record

ArticleSensors (Basel, Switzerland)2022

Performance Evaluation of an IoT Sensor Node for Health Monitoring of Artwork and Ancient Wooden Structures.

Ada Fort, Elia Landi, Marco Mugnaini, Lorenzo Parri, Valerio Vignoli

Open access · goldAbstract 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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
2.9field-weighted citation impact, top 7% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

5 authors at 1 institution in 1 country.

Ada FortDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.ORCID 0000-0003-0916-1516
Elia LandiDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.ORCID 0000-0003-2797-481X
Marco MugnainiDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.
Lorenzo ParriDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.
Valerio VignoliDepartment of Information Engineering and Mathematical Sciences, University of Siena, 53100 Siena, Italy.ORCID 0000-0003-2509-6566
University of Siena · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, an IoT sensor node, based on smart Bluetooth low energy (BLE), for the health monitoring of artworks and large wooden structures is presented. The measurements from sensors on board the node are collected in real-time and sent to a remote gateway. The sensor node allows for the monitoring of environmental parameters, in particular, temperature and humidity, with accurate and robust integrated sensors. The developed node also embeds an accelerometer, which also allows other mechanical quantities (such as tilt) to be derived. This feature can be exploited to perform structural monitoring, exploiting the processing of data history to detect permanent displacements or deformations. The node is triggered by acceleration transients; therefore, it can also generate alarms related to shocks. This feature is crucial, for instance, in the case of transportation. The developed device is low-cost and has very good performance in terms of power consumption and compactness. A reliability assessment showed excellent durability, and experimental tests proved very satisfactory robustness against working condition variations. The presented results confirm that the developed device allows for the realization of pervasive monitoring systems, in the context of the IoT paradigm, with sensor nodes devoted to the monitoring of each artwork present in a museum or in a church.

Indexed as

AccelerationMuseumsHumidityReproducibility of ResultsTemperatureartwork monitoringenvironmental monitoringIoTsensor networkssmart sensorssupply chain visibilityvibration monitoring

Identifiers

PMID36560163
PMCPMC9781305
OpenAlexW4311494442

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.