The challenge to detect contaminants inside water solutions is addressed in this paper, through the use of an integrated, low-cost, smart and IoT platform, namely SENSIPLUS. In particular, the complete process from the sensing phase to classification and results analysis is provided with further investigations about the limitations of the current proposal and the description of a further processing technique that promises to improve classification accuracy. The classification is performed by adopting machine learning techniques, particularly Artificial Neural Network, that well fits the implementation on a low-cost microcontroller, as the one SENSIPLUS platform uses.
Chemicals Detection in Water by SENSIPLUS Platform: Current State and Ongoing Progress
Bourelly C.;Ferdinandi M.;Molinara M.;Ferrigno L.;
2020-01-01
Abstract
The challenge to detect contaminants inside water solutions is addressed in this paper, through the use of an integrated, low-cost, smart and IoT platform, namely SENSIPLUS. In particular, the complete process from the sensing phase to classification and results analysis is provided with further investigations about the limitations of the current proposal and the description of a further processing technique that promises to improve classification accuracy. The classification is performed by adopting machine learning techniques, particularly Artificial Neural Network, that well fits the implementation on a low-cost microcontroller, as the one SENSIPLUS platform uses.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
