Lamp Energy Harvesting and Spectrum Analysis to Reduce Power Consumption in Smart Greenhouses

This research presents an energy-efficient monitoring system for smart greenhouses aimed at reducing power consumption and enhancing sustainability. The study focuses on optimizing the sampling time of monitored environmental parameters to minimize energy usage while maintaining data accuracy. Utilizing an optimal sampling approach significantly reduces energy consumption compared to fixed sampling intervals commonly used in commercial weather stations. Additionally, the implementation of an energy harvesting system, powered by solar panels, ensures the autonomy of sensors within the greenhouse, reducing the need for human intervention in battery replacement and recharging.

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Publication Details

Published
2024-09-26
DOI
https://doi.org/10.1109/cafe63183.2024.11069314
Citations
1
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
0.21
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article

Lamp Energy Harvesting and Spectrum Analysis to Reduce Power Consumption in Smart Greenhouses

Davide Adami, Stefano Giordano, Cristian Bua
1 citations
Energy Harvesting in Wireless Networks
0.21
article

Lamp Energy Harvesting and Spectrum Analysis to Reduce Power Consumption in Smart Greenhouses

Davide Adami, Stefano Giordano, Cristian Bua
article en
1 citations

Abstract

This research presents an energy-efficient monitoring system for smart greenhouses aimed at reducing power consumption and enhancing sustainability. The study focuses on optimizing the sampling time of monitored environmental parameters to minimize energy usage while maintaining data accuracy. Utilizing an optimal sampling approach significantly reduces energy consumption compared to fixed sampling intervals commonly used in commercial weather stations. Additionally, the implementation of an energy harvesting system, powered by solar panels, ensures the autonomy of sensors within the greenhouse, reducing the need for human intervention in battery replacement and recharging.

University of Pisa (IT)
Affordable and clean energy
Openalex Percentile: Top 43%
Energy Harvesting in Wireless Networks
0.21
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