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Adaptive machine learning strategies for network calibration of IoT smart air quality monitoring devices.

, , , , , и . Pattern Recognit. Lett., (2020)

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Sergio Dellavalle

Sergio Moccia

Sérgio Campos

Sergio Scognamillo

Sergio Greco

 

Другие публикации лиц с тем же именем

A Global Multiunit Calibration as a Method for Large-Scale IoT Particulate Matter Monitoring Systems Deployments., , , , , , , и . IEEE Trans. Instrum. Meas., (2024)Adaptive machine learning strategies for network calibration of IoT smart air quality monitoring devices., , , , , и . Pattern Recognit. Lett., (2020)Optimal Field Calibration of Multiple IoT Low Cost Air Quality Monitors: Setup and Results., , , , , , , и . ICCSA (5), том 12253 из Lecture Notes in Computer Science, стр. 700-708. Springer, (2020)A Global Multi-Unit Calibration as a Method for Large Scale IoT Particulate Matter Monitoring Systems Deployments., , , , , , , и . CoRR, (2023)Influence of Concept Drift on Metrological Performance of Low-Cost NO2 Sensors., , , , , , и . IEEE Trans. Instrum. Meas., (2022)Hyper resoluted Air Quality maps in urban environment with crowdsensed data from intelligent low cost sensors., , , , , , , , и . ISOEN, стр. 1-4. IEEE, (2022)Crowdsensing IoT Architecture for Pervasive Air Quality and Exposome Monitoring: Design, Development, Calibration, and Long-Term Validation., , , , , , , , , и 3 other автор(ы). Sensors, 21 (15): 5219 (2021)