↓ Skip to main content

A Global Multiunit Calibration as a Method for Large-Scale IoT Particulate Matter Monitoring Systems Deployments

Overview of attention for article published in IEEE Transactions on Instrumentation and Measurement, November 2023
Altmetric Badge

Mentioned by

twitter
1 X user

Readers on

mendeley
2 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A Global Multiunit Calibration as a Method for Large-Scale IoT Particulate Matter Monitoring Systems Deployments
Published in
IEEE Transactions on Instrumentation and Measurement, November 2023
DOI 10.1109/tim.2023.3331428
Authors

Saverio De Vito, Gerardo D’Elia, Sergio Ferlito, Girolamo Di Francia, Miloš D. Davidović, Duška Kleut, Danka Stojanović, Milena Jovaševic-Stojanović

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 October 2023.
All research outputs
#22,778,604
of 25,394,764 outputs
Outputs from IEEE Transactions on Instrumentation and Measurement
#2,575
of 2,654 outputs
Outputs of similar age
#292,783
of 357,085 outputs
Outputs of similar age from IEEE Transactions on Instrumentation and Measurement
#4
of 7 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,654 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 357,085 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.