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Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture.
Cappelli, Irene; Fort, Ada; Pozzebon, Alessandro; Tani, Marco; Trivellin, Nicola; Vignoli, Valerio; Bruzzi, Mara.
Afiliação
  • Cappelli I; Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy.
  • Fort A; Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy.
  • Pozzebon A; Department of Information Engineering, University of Padova, 35131 Padova, Italy.
  • Tani M; Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy.
  • Trivellin N; Department of Industrial Engineering, University of Padova, 35131 Padova, Italy.
  • Vignoli V; Department of Information Engineering and Mathematics, University of Siena, 53100 Siena, Italy.
  • Bruzzi M; Department of Physics and Astronomy, University of Florence, 50019 Florence, Italy.
Sensors (Basel) ; 22(11)2022 May 26.
Article em En | MEDLINE | ID: mdl-35684666
ABSTRACT
This paper aims at demonstrating the energy self-sufficiency of a LoRaWAN-based sensor node for monitoring environmental parameters exploiting energy harvesting directly coming from the artificial light used in indoor horticulture. A portable polycrystalline silicon module is used to charge a Li-Po battery, employed as the power reserve of a wireless sensor node able to accurately monitor, with a 1-h period, both the physical quantities most relevant for the application, i.e., humidity, temperature and pressure, and the chemical quantities, i.e., O2 and CO2 concentrations. To this aim, the node also hosts a power-hungry NDIR sensor. Two programmable light sources were used to emulate the actual lighting conditions of greenhouses, and to prove the effectiveness of the designed autonomous system a LED-based custom designed solar simulator and a commercial LED light especially thought for plant cultivation purposes in greenhouses. Different lighting conditions used in indoor horticulture to enhance different plant growth phases, obtained as combinations of blue, red, far-red and white spectra, were tested by field tests of the sensor node. The energy self-sufficiency of the system was demonstrated by monitoring the charging/discharging trend of the Li-Po battery. Best results are obtained when white artificial light is mixed with the far-red component, closest to the polycrystalline silicon spectral response peak.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Silício / Tecnologia sem Fio Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Silício / Tecnologia sem Fio Idioma: En Ano de publicação: 2022 Tipo de documento: Article