Design of energy-efficient lighting methods for vegetation landscape in the carbon neutrality perspective
カーボンニュートラルの観点からの植生景観のためのエネルギー効率の高い照明方法の設計 (AI 翻訳)
Xiaofei Lu, Yue Wang
🤖 gxceed AI 要約
日本語
本研究は、カーボンニュートラルの観点から、LED照明を用いた屋内農業システムにおけるエネルギー効率の高い照明方法を提案する。太陽光に基づく植生指数の計算方法を開発し、Light Spectrum Optimizer (LSO) を用いて最適化を行った。実験の結果、提案手法は朝・昼・夜の全ての時間帯で低い偏差率を示し、エネルギー適応と栄養供給の向上に貢献することが示された。
English
This study proposes an energy-efficient LED lighting method for indoor agricultural systems from a carbon neutrality perspective. It develops a method to compute vegetation indices based on sunlight, optimized using the Light Spectrum Optimizer (LSO). Results show low deviation rates at morning, afternoon, and night (2.13%, 2.71%, 2.88%), indicating improved energy adaptation and nutrient supply.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の植物工場や農業の省エネルギー化に関心が高まる中、本手法はLED照明の最適化を通じてコスト削減とカーボンニュートラル達成に寄与する可能性がある。
In the global GX context
This paper contributes to the global discourse on energy-efficient agriculture and carbon neutrality, offering an optimization method for LED lighting that can be applied in indoor farming systems worldwide.
👥 読者別の含意
🔬研究者:The Light Spectrum Optimizer method could be extended or compared with other optimization algorithms for energy efficiency in controlled environment agriculture.
🏢実務担当者:Indoor farm operators can apply the proposed LED lighting method to reduce energy consumption and improve plant growth efficiency.
📄 Abstract(原文)
Climate change research frequently emphasizes diminishing carbon emission in countries and cities; however, attaining carbon neutrality requires more contemplation. The Carbon Neutrality Challenge motivates individuals to estimate their carbon footprint and plant trees to recompense. LED lighting, with its energy efficacy, gives opportunities to elevate energy adaptation and nutrient supply in both terrestrial and extraterrestrial atmospheres. This study evaluates the potential of LEDs as an energy-efficient lighting source for indoor agricultural systems. The study suggests a method for computing vegetation indices based on sunlight. The proposed method employs a constant ‘standard whiteboard response ratio’ (CW), which is optimized using Light Spectrum Optimizer (LSO). This optimization mechanism gives greater outcomes compared to traditional algorithms. The CW value is measured using two cameras over 28 days. The method creates a VI estimate that is in line with the idea of carbon neutrality. The results show that the proposed method performs better at three times of the day, i.e. morning, afternoon and night. In the morning, the proposed mechanism attained a deviation rate of 2.13%. In the afternoon, the deviation rate for the suggested strategy is 2.71%, while it is 2.88% at night.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1080/17508975.2026.2676569first seen 2026-06-10 05:07:09 · last seen 2026-06-16 04:50:14
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