Articles | Volume 12, issue 9
© Author(s) 2019. This work is distributed underthe Creative Commons Attribution 4.0 License.
Gaussian process regression model for dynamically calibrating and surveilling a wireless low-cost particulate matter sensor network in Delhi
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13 citations as recorded by crossref.
- Evaluation of optical particulate matter sensors under realistic conditions of strong and mild urban pollution A. Masic et al. 10.5194/amt-13-6427-2020
- Learning-Based Adaptive Sensor Selection Framework for Multi-Sensing WSN S. Ghosh et al. 10.1109/JSEN.2021.3069264
- Wildfire smoke impacts on indoor air quality assessed using crowdsourced data in California Y. Liang et al. 10.1073/pnas.2106478118
- Estimating ground-level PM2.5 using micro-satellite images by a convolutional neural network and random forest approach T. Zheng et al. 10.1016/j.atmosenv.2020.117451
- A Review of Low-Cost Particulate Matter Sensors from the Developers’ Perspectives B. Alfano et al. 10.3390/s20236819
- Review of urban computing in air quality management as smart city service: An integrated IoT, AI, and cloud technology perspective A. Kaginalkar et al. 10.1016/j.uclim.2021.100972
- Domain Adaptation-Based Deep Calibration of Low-Cost PM₂.₅ Sensors S. Jha et al. 10.1109/JSEN.2021.3118454
- A Gaussian Process Method with Uncertainty Quantification for Air Quality Monitoring P. Wang et al. 10.3390/atmos12101344
- Local PM2.5 Hotspot Detector at 300 m Resolution: A Random Forest–Convolutional Neural Network Joint Model Jointly Trained on Satellite Images and Meteorology T. Zheng et al. 10.3390/rs13071356
- Evaluation of nine machine learning regression algorithms for calibration of low-cost PM2.5 sensor V. Kumar & M. Sahu 10.1016/j.jaerosci.2021.105809
- Air Quality Enhancement Districts: democratizing data to improve respiratory health K. Stevens et al. 10.1007/s13412-021-00670-9
- Edge Intelligence Framework for Data-Driven Dynamic Priority Sensing and Transmission S. Ghosh et al. 10.1109/TGCN.2021.3136139
- Robust statistical calibration and characterization of portable low-cost air quality monitoring sensors to quantify real-time O<sub>3</sub> and NO<sub>2</sub> concentrations in diverse environments R. Sahu et al. 10.5194/amt-14-37-2021
Latest update: 03 Jun 2023