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BLOCKCHAIN-ENABLED TRACEABILITY SYSTEMS FOR SUSTAINABLE AGRICULTURAL SUPPLY CHAINS INTEGRATION WITH IOT AND CARBON ACCOUNTING STANDARDS

ブロックチェーン対応トレーサビリティシステム:持続可能な農業サプライチェーンのためのIoTと炭素会計基準の統合 (AI 翻訳)

Maria Papadaki

Zenodo (CERN European Organization for Nuclear Research)ジャーナル2026-06-29#サプライチェーンOrigin: Global経営インパクト: 調達リスク対象セクター: agriculture
DOI: 10.5281/zenodo.21045376
原典: https://doi.org/10.5281/zenodo.21045376

🤖 gxceed AI 要約

日本語

IoTセンサーデータとブロックチェーンを統合し、農業サプライチェーンのトレーサビリティと炭素会計を自動化する参照アーキテクチャを提案。CSRD等の規制要件に対応し、スマートコントラクトによる排出量計算とデータ整合性検証を実現する。パイロット実装で実用性を評価する博士研究計画。

English

Proposes a blockchain-IoT reference architecture for sustainable agricultural supply chains that automates traceability and carbon footprint accounting aligned with CSRD and similar regulatory standards. Addresses oracle mechanisms, data standardization, smart contracts for emission calculations, scalability, and privacy, with pilot validation planned in agri-food 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

日本ではSSBJ基準等のサステナビリティ情報開示義務化が進み、サプライチェーン排出量の信頼性ある計測・検証が課題となっている。農産品のトレーサビリティと炭素会計を統合する本方式は、日本の食品・農業企業のScope3対応や輸出時のESG証明にも応用可能な視点を提供する。

In the global GX context

Aligns with global regulatory pressure for verifiable Scope 3 emissions and CSRD-aligned reporting. Contributes to emerging scholarship on blockchain-enabled carbon accounting and supply-chain transparency, offering design guidance for interoperable, tamper-proof systems that can support transition finance and disclosure assurance.

👥 読者別の含意

🔬研究者:ブロックチェーン-IoTと炭素会計を組み合わせた設計手法とセンサー・オラクル信頼性の検証方法を参考にできる。

🏢実務担当者:農産物サプライチェーンの炭素排出量を自動で報告するためのスマートコントラクト雛形と参照アーキテクチャを活用できる。

🏛政策担当者:サステナビリティ報告におけるIoTデータとブロックチェーン保証の相互運用性の標準化ニーズを示している。

📄 Abstract(原文)

Consumer demand for food provenance and tightening regulatory requirements for sustainability reporting, particularly carbon accounting under frameworks such as the EU Corporate Sustainability Reporting Directive, are driving the need for transparent and verifiable agricultural supply chains. While Internet of Things (IoT) sensors have advanced significantly in monitoring farm conditions, logistics, and storage, the data they produce often remains fragmented and susceptible to tampering. Blockchain technology offers an immutable, decentralized ledger capable of creating a tamper-proof chain of custody from farm to consumer. When integrated with IoT data streams and standardized carbon accounting methodologies, blockchain-enabled systems can provide end-to-end traceability, automated carbon footprint calculation, and credible sustainability verification. This PhD research report proposes the design, development, and validation of integrated blockchain-IoT frameworks for sustainable agricultural supply chains with explicit linkage to carbon accounting standards. The work addresses key informatics challenges including reliable oracle mechanisms for sensor data, data standardization and interoperability, smart contract design for traceability events and carbon calculations, scalability, privacy considerations, and alignment with regulatory reporting requirements. Building on systematic reviews of blockchain in food traceability and emerging work on blockchain for carbon footprint tracking, the research aims to deliver a practical, scalable architecture validated through pilot implementations in representative agri-food chains. Key contributions include a modular reference architecture integrating IoT sensing, blockchain traceability, and carbon accounting; smart contract frameworks for automated event recording and emission calculations; methods for verifiable data input from physical sensors; and empirical evaluation of traceability completeness, data integrity, carbon accounting accuracy, and stakeholder usability. The report emphasizes both theoretical rigor in system design and experimental grounding through real-world pilots, positioning the work to support immediate commercial applications and regulatory compliance in sustainable agriculture.

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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。