Contaminants detection and classification through a customized IoT-based platform: A case study
Authors: Gianni Cerro, Giovanni Betta, Marco Ferdinandi, Luigi Ferrigno, Mario Molinara, IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE, Betta, Giovanni, Cerro, Gianni, Ferdinandi, Marco, Ferrigno, Luigi, Molinara, Mario, Horizon 2020 research and innovation programme under grant agreement SYSTEM No. 787128
Abstract
Internet of Things (IoT) is involving more and more fields where monitoring actions and fast and reliable data communication are simultaneously needed. Inside the general class of monitoring applications, those related to pollutant detection and classification are currently faced by many researchers and companies. Several approaches are being proposed in the literature, but lots of open issues and challenges are still to be handled before deploying a commonly considered optimum system. This contribution proposes a novel low-cost and highly flexible platform which is intended to tackle such challenges adopting ad-hoc hardware and software techniques. The proposed solution is applied to air and water contaminant detection case studies. The paper provides the reader with an innovative system in the field of pollution monitoring and focuses the attention on limitations, challenges and possible improvements needed to obtain reliable contaminant detection and, consequently, improve life quality.
BibTeX
@article{giannicerro2019contaminants,
title={Contaminants detection and classification through a customized IoT-based platform: A case study},
author={Gianni Cerro and Giovanni Betta and Marco Ferdinandi and Luigi Ferrigno and Mario Molinara and IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE and Betta, Giovanni and Cerro, Gianni and Ferdinandi, Marco and Ferrigno, Luigi and Molinara, Mario and Horizon 2020 research and innovation programme under grant agreement SYSTEM No. 787128},
year={2019},
doi={10.1109/MIM.2019.8917902}
}