A conceptual IoT-based model for monitoring environmental parameters in ecological tea gardens under carbon neutrality
カーボンニュートラル下での生態茶園における環境パラメータ監視のためのIoTベース概念モデル (AI 翻訳)
Chaoran Li
🤖 gxceed AI 要約
日本語
本論文は、茶園の炭素排出行動を監視するためのIoTベースのフレームワークを提案する。土壌炭素含有量、温度、湿度などの環境データを収集し、ファジィ論理に基づく分類で排出量を評価する。中国・武夷山の茶園での実験により、排出集約的なライフサイクル段階を特定し、改善策により排出強度が低減することを示した。
English
This paper proposes an IoT-based framework for monitoring carbon emission behavior in tea gardens. It collects environmental data (soil carbon, temperature, humidity) and uses fuzzy logic classification to categorize emission rates. Experiments in a Wuyi Mountains tea garden identify emission-intensive lifecycle stages and demonstrate that modified practices reduce emission intensity.
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
中国の茶園を事例とするが、日本の農業分野でのカーボンニュートラル施策（例：みどりの食料システム戦略）や、スマート農業によるGHG排出監視の観点から参考になる。ただし、日本のSSBJや有報との直接的な関連は薄い。
In the global GX context
This paper presents a monitoring framework for agricultural carbon emissions using IoT, relevant to global efforts in agricultural decarbonization. While focused on tea gardening in China, the approach can inform sustainable farming practices and carbon accounting in other regions.
👥 読者別の含意
🔬研究者:Researchers in agricultural carbon accounting and IoT-based environmental monitoring can adopt the fuzzy evaluation method for lifecycle emission assessment.
🏢実務担当者:Tea garden managers and agricultural firms can use IoT sensor networks to identify emission hotspots and adjust cultivation practices to reduce carbon footprint.
🏛政策担当者:Agricultural policymakers can leverage such monitoring frameworks to design carbon-neutral farming incentives and verify emission reductions.
📄 Abstract（原文）
Tea gardening contributes both to carbon sequestration and carbon emissions across different cultivation stages, necessitating precise monitoring for sustainable management. This study presents an internet of things (IoT)-based monitoring and evaluation framework for assessing carbon emission behavior in tea gardens using real-time environmental data. IoT sensors measuring soil carbon content, temperature, and humidity were deployed to collect observations across successive tea cultivation lifecycles. The collected data were analyzed using a fuzzy logic–based classification approach to categorize emission rates into standard, acceptable, and violating levels. Experimental evaluation, using data from an ecological tea garden in the Wuyi Mountains, China, demonstrates that emission-intensive lifecycle stages can be consistently identified. Modified practices applied to violating stages result in measurable reductions in emission intensity in subsequent lifecycle phases. These findings confirm that integrating IoT-based sensing with fuzzy evaluation enables effective identification and assessment of carbon emission behavior in tea gardening, providing empirically supported insights for emission-aware lifecycle management and environmental sustainability.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.25259/jksus_1083_2025first seen 2026-07-13 05:38:39
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