ArticleSensors (Basel, Switzerland)2025
Machine Learning-Based Calibration and Performance Evaluation of Low-Cost Internet of Things Air Quality Sensors.
Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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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.
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.
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Who cites it
7 citing papers in PubMed.
- An On-Device Edge AI Agent for Reference-Free Self-Diagnosis of Low-Cost Multi-Pollutant Sensors.Sensors (Basel, Switzerland) · 2026Article
- PM2.5/PM10 Forecasting System with Benchmarking of 44 Machine Learning Algorithms and Ensemble Learning Approaches.Sensors (Basel, Switzerland) · 2026Article
- Comparative Evaluation of Machine Learning and Hyperparameter Optimization Methods for Low-Cost COSensors (Basel, Switzerland) · 2026Article
- Machine Learning Applications with Sensors for Indoor Air Quality Research.Sensors (Basel, Switzerland) · 2026Review
- AI Methods in Sensor Calibration.Sensors (Basel, Switzerland) · 2026Review
- Article
- Machine Learning-Driven Sensitivity Analysis for a 2-Layer Printed Circuit Board Inductive Motor Position Sensor.Sensors (Basel, Switzerland) · 2026Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Low-cost air quality sensors (LCSs) are increasingly being used in environmental monitoring due to their affordability and portability. However, their sensitivity to environmental factors can lead to measurement inaccuracies, necessitating effective calibration methods to enhance their reliability. In this study, an Internet of Things (IoT)-based air quality monitoring system was developed and tested using the most commonly preferred sensor types for air quality measurement: fine particulate matter (PM
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Registered trials
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.