Calibration of Low-Cost LoRaWAN-Based IoT Air Quality Monitors Using the Super Learner Ensemble: A Case Study for Accurate Particulate Matter Measurement

Calibration of Low-Cost LoRaWAN-Based IoT Air Quality Monitors Using the Super Learner Ensemble: A Case Study for Accurate Particulate Matter Measurement

This study calibrates an affordable, solar-powered LoRaWAN air quality monitoring prototype using the research-grade Palas Fidas Frog sensor. Motivated by the need for sustainable air quality monitoring in smart city initiatives, this work integrates low-cost, self-sustaining sensors with research-g...

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Bibliographic Details
Main Authors: Gokul Balagopal, Lakitha Wijeratne, John Waczak, Prabuddha Hathurusinghe, Mazhar Iqbal, Daniel Kiv, Adam Aker, Seth Lee, Vardhan Agnihotri, Christopher Simmons, David J. Lary
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Sensors
Subjects:
machine learning
data science
statistics
regression
calibration
optimization
Online Access:https://www.mdpi.com/1424-8220/25/5/1614

Internet

https://www.mdpi.com/1424-8220/25/5/1614

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