サプライチェーンにおける炭素排出資源消費の最適化のための分散システム
A Distributed System for Optimization of Carbon Emitting Resource Consumption in Supply Chains (原題)
Salman Ali, Cedric Gondro, Qiben Yan, Wolfgang Banzhaf
🤖 gxceed AI 要約
日本語
断片化したサプライチェーン間でGHG排出を精緻に追跡・共同最適化するため、ブロックチェーン、IoT、分散データベースを組み合わせた分散型フレームワークを提案。プライバシーと透明性を両立しつつ、ローカルとグローバルの協働グループ形成を可能にする。拡張性・スケーラビリティを備え、複雑で分断されたチェーン全体の炭素フットプリント記録・監視・最適化を目指す。
English
The paper proposes a decentralized framework combining blockchain, IoT, and distributed databases to trace fine-grained GHG emissions across fragmented supply chains for joint resource-consumption optimization. It enables local and global collaboration groups while ensuring privacy and transparency, with extensibility and scalability for diverse data sources. The goal is flexible, collaborative carbon-footprint monitoring and optimization across complex, disjoint supply chains.
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
SSBJ基準・Scope3開示義務化を見据え、一次サプライヤーを超えた多段階の排出データ捕捉は日本企業の実務課題。食品・畜産など垂直統合が乏しい業界での応用可能性が高い。
In the global GX context
Aligns with ISSB/CSRD-driven demand for primary Scope 3 data and supply-chain due diligence. Offers a decentralized architecture relevant to global efforts on interoperable, privacy-preserving emissions tracing beyond tier-1 suppliers.
👥 読者別の含意
🔬研究者:分散台帳とIoTを組み合わせたScope3排出追跡の設計論として、データガバナンス研究に示唆。
🏢実務担当者:多段階サプライヤーからの排出データ収集・共同最適化の仕組みづくりに活用可能。
🏛政策担当者:Scope3開示制度設計における分散型データ基盤の可能性を検討する材料になる。
📄 Abstract（原文）
Industrialized supply chains significantly impact the environment by accelerated greenhouse gas emissions. As supply chains get complex, they suffer from fragmentation in terms of sharing knowledge among participants. Fragmented chains such as the meat business, encompasses sub-stages like feed production, processing, distribution and retail but incorporate bare minimum vertical integration. This hinders measurement of carbon footprint against products being shipped. Lack of in-frastructure to estimate emissions at different independent stages results in lost opportunity to minimize emissions from end-to-end. To address issues arising from isolated supply chain participants, we propose a decentralized framework leveraging blockchain functions, internet of things, and distributed databases to allow to capture fine-grained greenhouse gas emissions across supply chain for joint optimization of underlying resource consumption. The proposed framework facilitates formation of a mix of local and global collaboration groups for precise carbon emission tracing while ensuring privacy and transparency. Key frame-work features include system's extensibility and scalability for integration of diverse information sources, secure data capture mechanism, and propagation of data and policies via blockchain and internet of things infrastructure. Our proposed solution aims to offer a flexible, comprehensive, and collaborative approach to recording, monitoring and optimizing carbon footprint across complex disjoint supply chains, thereby promoting improved environmental oupnut management.
🔗 Provenance — このレコードを発見したソース
- openalex http://dx.doi.org/10.1109/isncc62547.2024.10758964first seen 2026-08-02 18:14:22 · last seen 2026-08-02 18:15:26
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