106 citations as recorded by crossref.

1. Monitoring Gas Emissions in Agricultural Productions through Low-Cost Technologies: The POREM (Poultry-Manure-Based Bio-Activator for Better Soil Management through Bioremediation) Project Experience D. Suriano & F. Abulude
2. A Global Multiunit Calibration as a Method for Large-Scale IoT Particulate Matter Monitoring Systems Deployments S. De Vito et al.
3. Review of the Performance of Low-Cost Sensors for Air Quality Monitoring F. Karagulian et al.
4. Graph Learning Techniques Using Structured Data for IoT Air Pollution Monitoring Platforms P. Ferrer-Cid et al.
5. Stochastic Online Calibration of Low-Cost Gas Sensor Networks With Mobile References G. Tancev & F. Toro
6. Detecting Inaccurate Sensors on a Large-Scale Sensor Network Using Centralized and Localized Graph Neural Networks D. Wu et al.
7. Modular Air Quality Calibration and Forecasting Method for Low-Cost Sensor Nodes Y. Hashmy et al.
8. Learning Calibration Functions on the Fly: Hybrid Batch Online Stacking Ensembles for the Calibration of Low-Cost Air Quality Sensor Networks in the Presence of Concept Drift E. Bagkis et al.
9. Evaluating and improving the reliability of gas-phase sensor system calibrations across new locations for ambient measurements and personal exposure monitoring S. Vikram et al.
10. Development of low-cost air quality stations for next-generation monitoring networks: calibration and validation of NO2 and O3 sensors A. Cavaliere et al.
11. The Use of Low-Cost Gas Sensors for Air Quality Monitoring with Smartphone Technology: A Preliminary Study D. Suriano et al.
12. Unexpected Performance Improvements of Nitrogen Dioxide and Ozone Sensors by Including Carbon Monoxide Sensor Signal M. Hasan et al.
13. A dynamic spatial filtering approach to mitigate underestimation bias in field calibrated low-cost sensor air pollution data C. Heffernan et al.
14. The Relocation Problem of Field Calibrated Low-Cost Sensor Systems in Air Quality Monitoring: A Sampling Bias G. Tancev & C. Pascale
15. Efficient and Automated Generation of Orthogonal Atmospheres for the Characterization of Low-Cost Gas Sensor Systems in Air Quality Monitoring G. Tancev et al.
16. Spatial and temporal mapping of transport emissions and application of air quality models using low cost sensor data P. Pérez-Martínez et al.
17. Recalibration of low-cost O3 and PM2.5 sensors: linking practices to recent air sensor test protocols P. Gäbel & E. Hertig
18. Sens-BERT: A BERT-Based Approach for Enabling Transferability and Re-Calibration of Calibration Models for Low-Cost Sensors Under Reference Measurements Scarcity M. Narayana et al.
19. Low-cost system application for policy assessment: a case study from Berlin A. Caseiro et al.
20. Calibration and Inter-Unit Consistency Assessment of an Electrochemical Sensor System Using Machine Learning I. Apostolopoulos et al.
21. Low-cost sensors for atmospheric NO2 measurement: A review C. Ayvaz et al.
22. Evaluation of low-cost gas sensors to quantify intra-urban variability of atmospheric pollutants A. Baruah et al.
23. Application of the compact and useful PM2.5 instrument with gas sensors (CUPI-G) for high temporal and spatial resolution monitoring with weather factor integration A. Bhowmick et al.
24. Machine learning techniques to improve the field performance of low-cost air quality sensors T. Bush et al.
25. Cost-Efficient measurement platform and machine-learning-based sensor calibration for precise NO2 pollution monitoring A. Pietrenko-Dabrowska et al.
26. Development and evaluation of a robust temperature sensitive algorithm for long term NO2 gas sensor network data correction P. Wei et al.
27. Calibrations of Low-Cost Air Pollution Monitoring Sensors for CO, NO2, O3, and SO2 P. Han et al.
28. A novel spatiotemporal prediction approach to fill air pollution data gaps using mobile sensors, machine learning and citizen science techniques A. Baruah et al.
29. Review of low-cost sensors for indoor air quality: Features and applications M. Ródenas García et al.
30. Unravelling a black box: an open-source methodology for the field calibration of small air quality sensors S. Schmitz et al.
31. Transferability of machine-learning-based global calibration models for NO2 and NO low-cost sensors A. Abu-Hani et al.
32. Air pollution prediction system using XRSTH-LSTM algorithm H. Srivastava & S. Kumar Das
33. Estimation of Surface-Level NO2 Using Satellite Remote Sensing and Machine Learning: A review M. Siddique et al.
34. Low-Cost CO Sensor Calibration Using One Dimensional Convolutional Neural Network S. Ali et al.
35. Minimized Training of Machine Learning-Based Calibration Methods for Low-Cost O3 Sensors S. Tondini et al.
36. Calibration of Electrochemical Sensors for Nitrogen Dioxide Gas Detection Using Unmanned Aerial Vehicles R. Mawrence et al.
37. Data reconstruction applications for IoT air pollution sensor networks using graph signal processing P. Ferrer-Cid et al.
38. Learning to Identify Malfunctioning Sensors in a Large-Scale Sensor Network T. Lin et al.
39. Using A Low-Cost Sensor Array and Machine Learning Techniques to Detect Complex Pollutant Mixtures and Identify Likely Sources J. Thorson et al.
40. A Scalable Calibration Method for Enhanced Accuracy in Dense Air Quality Monitoring Networks A. Winter et al.
41. Indoor Air Sensing: A Study in Cost, Energy, Reliability and Fidelity in Sensing P. Sharma et al.
42. In-situ baseline calibration approach for enhanced data quality of large-scale air sensor monitoring networks H. Mei et al.
43. Calibration and performance evaluation of PM2.5 and NO2 air quality sensors for environmental epidemiology M. Chacón-Mateos et al.
44. When Does Geostatistical Interpolation Work? Monthly and Hourly Sensitivity of Ordinary Kriging for Urban Air Pollutant Mapping in Mexico City E. Hernández-Gress & D. Conchouso González
45. Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine Learning I. Vajs et al.
46. Air Pollution Monitoring via Wireless Sensor Networks: The Investigation and Correction of the Aging Behavior of Electrochemical Gaseous Pollutant Sensors I. Christakis et al.
47. Assessment of the impact of sensor error on the representativeness of population exposure to urban air pollutants T. Leo Hohenberger et al.
48. Data Driven Concept for Sensor Data Adaptation of Electrochemical Sensors for Mobile Air Quality Measurements E. Esatbeyoglu et al.
49. Assessment of air quality sensor system performance after relocation S. Zauli-Sajani et al.
50. Sustained Performance of Low-Cost Air Quality Sensors in Long-Term Deployments A. Winter et al.
51. Relevance of Drift Components and Unit-to-Unit Variability in the Predictive Maintenance of Low-Cost Electrochemical Sensor Systems in Air Quality Monitoring G. Tancev
52. Development of Air Quality Boxes Based on Low-Cost Sensor Technology for Ambient Air Quality Monitoring P. Gäbel et al.
53. Leveraging Temporal Information to Improve Machine Learning-Based Calibration Techniques for Low-Cost Air Quality Sensors S. Ali et al.
54. Advancements in Air Quality Monitoring Systems: A Comprehensive Review of Emerging Technologies for Enhancing Environmental Health S. Ahmed et al.
55. HMTC: A Hybrid Mamba-Transformer Model for Calibration of Low-Cost Air Quality Sensors G. Angelis et al.
56. IoT-based smart environmental control and air emission management in animal farming: A systematic review H. Ma et al.
57. Enhancing the Reliability of NO2 Monitoring Using Low-Cost Sensors by Compensating for Temperature and Humidity Effects D. Alejo Sánchez et al.
58. Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing S. Koziel et al.
59. Multisensor Data Fusion Calibration in IoT Air Pollution Platforms P. Ferrer-Cid et al.
60. Assessment of the Performance of a Low-Cost Air Quality Monitor in an Indoor Environment through Different Calibration Models D. Suriano & M. Penza
61. A Low-Cost Calibration Method for Temperature, Relative Humidity, and Carbon Dioxide Sensors Used in Air Quality Monitoring Systems R. González Rivero et al.
62. Field calibration and performance evaluation of low-cost sensors for monitoring airborne PM in the occupational mining environment A. Penchala et al.
63. Calibrating low-cost sensors to measure vertical and horizontal gradients of NO2 and O3 pollution in three street canyons in Berlin S. Schmitz et al.
64. Evaluation of Low-Cost CO2 Sensors Using Reference Instruments and Standard Gases for Indoor Use Q. Cai et al.
65. Advantages and limitations of the analytical methods currently employed for the assessment of inorganic pollutants in indoor and outdoor air M. Ródenas et al.
66. Long-term evaluation of commercial air quality sensors: an overview from the QUANT (Quantification of Utility of Atmospheric Network Technologies) study S. Diez et al.
67. Evaluation and calibration of low‐cost off‐the‐shelf particulate matter sensors using machine learning techniques M. Ghamari et al.
68. Mapping trends and analyzing key themes in low-cost sensors for air quality monitoring K. Alhasa et al.
69. Temporal Pattern-Based Denoising and Calibration for Low-Cost Sensors in IoT Monitoring Platforms X. Allka et al.
70. Statistical data pre-processing and time series incorporation for high-efficacy calibration of low-cost NO2 sensor using machine learning S. Koziel et al.
71. In search of an optimal in-field calibration method of low-cost gas sensors for ambient air pollutants: Comparison of linear, multilinear and artificial neural network approaches D. Topalović et al.
72. Design and Development of an Electronic Board for Supporting the Operation of Electrochemical Gas Sensors D. Suriano
73. First-Principles Algorithm for Air Quality Electrochemical Gas Sensors B. Ouyang
74. A Comparative Study of Calibration Methods for Low-Cost Ozone Sensors in IoT Platforms P. Ferrer-Cid et al.
75. Surface distributions and vertical profiles of trace gases (CO, O3, NO, NO2) in the Arctic wintertime boundary layer using low-cost sensors during ALPACA-2022 B. Barret et al.
76. Stationary and portable multipollutant monitors for high-spatiotemporal-resolution air quality studies including online calibration C. Buehler et al.
77. A calibration chamber framework for low-cost indoor air quality sensor validation H. Othman et al.
78. Exploring the inequality of the particulate matter exposure level of public bicycle scheme users using an agent-based model S. Hwang et al.
79. In situ drift correction for a low-cost NO2 sensor network J. Miech et al.
80. Mapping the spatial distribution of NO2 with in situ and remote sensing instruments during the Munich NO2 imaging campaign G. Kuhlmann et al.
81. Evaluating the Performance of Using Low-Cost Sensors to Calibrate for Cross-Sensitivities in a Multipollutant Network M. Levy Zamora et al.
82. A Densely-Deployed, High Sampling Rate, Open-Source Air Pollution Monitoring WSN B. Montrucchio et al.
83. Air quality measurement, prediction and warning using transfer learning based IOT system for ambient assisted living S. Sonawani & K. Patil
84. Long-term behavior and stability of calibration models for NO and NO2 low-cost sensors H. Kim et al.
85. Distributed Multi-Scale Calibration of Low-Cost Ozone Sensors in Wireless Sensor Networks J. Barcelo-Ordinas et al.
86. STCM: A spatio-temporal calibration model for low-cost air monitoring sensors Y. Zhang et al.
87. Garbage in, gospel out? – Air quality assessment in the UK planning system A. Mills & S. Peckham
88. On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction S. Koziel et al.
89. The Zurich Low-cost CO2 sensor network (ZiCOS-L): data processing, performance assessment and analysis of spatial and temporal CO2 dynamics L. Creman et al.
90. Smart Multi-Sensor Calibration of Low-Cost Particulate Matter Monitors E. Villanueva et al.
91. Sampling Trade-Offs in Duty-Cycled Systems for Air Quality Low-Cost Sensors P. Ferrer-Cid et al.
92. Low-cost urban carbon monitoring network and implications for china: a comprehensive review H. Jiang et al.
93. Integration and calibration of non-dispersive infrared (NDIR) CO2 low-cost sensors and their operation in a sensor network covering Switzerland M. Müller et al.
94. Air pollution measurement errors: is your data fit for purpose? S. Diez et al.
95. Dynamic calibration of low-cost PM2.5 sensors using trust-based consensus mechanisms S. Mahajan & D. Helbing
96. Reliability of Lower-Cost Sensors in the Analysis of Indoor Air Quality on Board Ships O. Schalm et al.
97. Calibration of SO2 and NO2 Electrochemical Sensors via a Training and Testing Method in an Industrial Coastal Environment S. Ahumada et al.
98. Establishing A Sustainable Low-Cost Air Quality Monitoring Setup: A Survey of the State-of-the-Art M. Narayana et al.
99. EEATC: A Novel Calibration Approach for Low-Cost Sensors M. Narayana et al.
100. Investigation of LASSO Regression Method as a Correction Measurements’ Factor for Low-Cost Air Quality Sensors I. Christakis et al.
101. High-performance machine-learning-based calibration of low-cost nitrogen dioxide sensor using environmental parameter differentials and global data scaling S. Koziel et al.
102. Improving the quantification of peak concentrations for air quality sensors via data weighting C. Frischmon et al.
103. Nitrogen Dioxide Monitoring by Means of a Low-Cost Autonomous Platform and Sensor Calibration via Machine Learning with Global Data Correlation Enhancement S. Koziel et al.
104. A fast calibration algorithm for Non-Dispersive Infrared single channel carbon dioxide sensor based on deep learning K. Mao et al.
105. A 30-month field evaluation of low-cost CO2 sensors using a reference instrument Q. Cai et al.
106. Annual NO2 as a Predictor of Hourly NO2 Variability: Do Defra UK’s Heuristics Make Sense? A. Mills & S. Peckham