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Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185431/ https://www.ncbi.nlm.nih.gov/pubmed/35684666 http://dx.doi.org/10.3390/s22114046 |
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author | Cappelli, Irene Fort, Ada Pozzebon, Alessandro Tani, Marco Trivellin, Nicola Vignoli, Valerio Bruzzi, Mara |
author_facet | Cappelli, Irene Fort, Ada Pozzebon, Alessandro Tani, Marco Trivellin, Nicola Vignoli, Valerio Bruzzi, Mara |
author_sort | Cappelli, Irene |
collection | PubMed |
description | 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., O(2) and CO(2) 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. |
format | Online Article Text |
id | pubmed-9185431 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91854312022-06-11 Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture Cappelli, Irene Fort, Ada Pozzebon, Alessandro Tani, Marco Trivellin, Nicola Vignoli, Valerio Bruzzi, Mara Sensors (Basel) Article 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., O(2) and CO(2) 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. MDPI 2022-05-26 /pmc/articles/PMC9185431/ /pubmed/35684666 http://dx.doi.org/10.3390/s22114046 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Cappelli, Irene Fort, Ada Pozzebon, Alessandro Tani, Marco Trivellin, Nicola Vignoli, Valerio Bruzzi, Mara Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture |
title | Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture |
title_full | Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture |
title_fullStr | Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture |
title_full_unstemmed | Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture |
title_short | Autonomous IoT Monitoring Matching Spectral Artificial Light Manipulation for Horticulture |
title_sort | autonomous iot monitoring matching spectral artificial light manipulation for horticulture |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9185431/ https://www.ncbi.nlm.nih.gov/pubmed/35684666 http://dx.doi.org/10.3390/s22114046 |
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