In this paper a network architecture for the monitoring of NO2 emissions in the industrial scenarios is presented. The proposed system is based on chemoresistive gas sensors realized by mixing nano-composite of ZnO, doped by Al (5%) and Co3O4. The obtained compound presents appreciable sensitivity to NO2 exposure at room temperature which makes it suitable for low-power applications. The sensor is embedded in an IoT framework exploiting the Long Range (LoRa) LPWAN connectivity with the associated LoRaWAN protocol, granting data transmission over a wide area. Thus, the acquired data will be forwarded to a Cloud platform to be collected and remotely managed.

Addabbo, T., Fort, A., Mugnaini, M., Panzardi, E., Pozzebon, A., Hjiri, M., et al. (2020). A Low Cost Resistive Gas Sensor Network Based on Zn-Al Doped and Co3O4 Nanopowder Composite. In Sensors and Microsystems. AISEM 2019 (pp.163-168). Cham : Springer [10.1007/978-3-030-37558-4_24].

A Low Cost Resistive Gas Sensor Network Based on Zn-Al Doped and Co3O4 Nanopowder Composite

Addabbo T.;Fort A.;Mugnaini M.;Panzardi E.
;
Pozzebon A.;
2020-01-01

Abstract

In this paper a network architecture for the monitoring of NO2 emissions in the industrial scenarios is presented. The proposed system is based on chemoresistive gas sensors realized by mixing nano-composite of ZnO, doped by Al (5%) and Co3O4. The obtained compound presents appreciable sensitivity to NO2 exposure at room temperature which makes it suitable for low-power applications. The sensor is embedded in an IoT framework exploiting the Long Range (LoRa) LPWAN connectivity with the associated LoRaWAN protocol, granting data transmission over a wide area. Thus, the acquired data will be forwarded to a Cloud platform to be collected and remotely managed.
2020
978-3-030-37557-7
978-3-030-37558-4
Addabbo, T., Fort, A., Mugnaini, M., Panzardi, E., Pozzebon, A., Hjiri, M., et al. (2020). A Low Cost Resistive Gas Sensor Network Based on Zn-Al Doped and Co3O4 Nanopowder Composite. In Sensors and Microsystems. AISEM 2019 (pp.163-168). Cham : Springer [10.1007/978-3-030-37558-4_24].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/1113400