2 papers
eess.SP2020
Adaptive machine learning strategies for network calibration of IoT smart air quality monitoring devices
Saverio De Vito, Girolamo Di Francia, Elena Esposito +3
Air Quality Multi-sensors Systems (AQMS) are IoT devices based on low cost chemical microsensors array that recently have showed capable to provide relatively accurate air pollutan…
cs.AI2017
Calibrating chemical multisensory devices for real world applications: An in-depth comparison of quantitative Machine Learning approaches
S. De Vito, E. Esposito, M. Salvato +4
Chemical multisensor devices need calibration algorithms to estimate gas concentrations. Their possible adoption as indicative air quality measurements devices poses new challenges…