An End to End Indoor Air Monitoring System Based on Machine Learning and SENSIPLUS Platform

An End to End Indoor Air Monitoring System Based on Machine Learning and SENSIPLUS Platform

In the framework of indoor air monitoring, this paper proposes an Internet of Things ready solution to detect and classify contaminants. It is based on a compact and low-power integrated system including both sensing and processing capabilities. The sensing is composed of a sensor array on which ele...

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Bibliographic Details
Main Authors: Mario Molinara, Marco Ferdinandi, Gianni Cerro, Luigi Ferrigno, Ettore Massera
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Contaminant detection
air monitoring
sensor networks
neural networks
deep learning
IoT
Online Access:https://ieeexplore.ieee.org/document/9064782/

Internet

https://ieeexplore.ieee.org/document/9064782/

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