A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors

A Systematic Study of Popular Software Packages and AI/ML Models for Calibrating In Situ Air Quality Data: An Example with Purple Air Sensors

Accurate air pollution monitoring is critical to understand and mitigate the impacts of air pollution on human health and ecosystems. Due to the limited number and geographical coverage of advanced, highly accurate sensors monitoring air pollutants, many low-cost and low-accuracy sensors have been d...

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Bibliographic Details
Main Authors: Seren Smith, Theodore Trefonides, Anusha Srirenganathan Malarvizhi, Shyra LaGarde, Jiakang Liu, Xiaoguo Jia, Zifu Wang, Jacob Cain, Thomas Huang, Mohammad Pourhomayoun, Grace Llewellyn, Wai Phyo, Sina Hasheminassab, Joe Roberts, Kevin Marlis, Daniel Q. Duffy, Chaowei Yang
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Sensors
Subjects:
sensors
air quality
calibration
particulate matter
AI/ML
model accuracy
Online Access:https://www.mdpi.com/1424-8220/25/4/1028
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