Mobile Edge AI Framework for Real-Time ESG Compliance Auditing through NLP and Blockchain Ledger Verification

The Mobile Edge artificial intelligence (AI) framework is introduced as an environmental, social, and governance (ESG) verification system that integrates natural language processing (NLP) and permissioned blockchain to facilitate near-real-time ESG compliance auditing. A lightweight transformer model is employed to identify ESG-related claims and extract relevant indicators, numerical values, units, locations, and reporting times. Extracted claims are structured and recorded on the blockchain to ensure verifiable, tamper-resistant records. A discrepancy assessment mechanism then classifies each claim as supported, partially supported, contradictory, or unsupported. The prototype was evaluated using a synthetic Kaggle dataset containing 11,000 annual company records from 1,000 organizations across nine regions and multiple sectors. The ESG classification model achieved a true positive rate of approximately 93.2%, with F1-scores of 0.945, 0.915, and 0.895 for environmental, social, and governance claims, respectively. Claim verification rates ranged from 93.1% to 98.4%. Edge deployment reduced verification latency to 124 ms compared to 231 ms in the cloud environment, representing a 46.3% reduction. These findings indicate that the framework can enable proactive ESG auditing, enhance claim traceability, accelerate verification, and deliver explainable compliance-risk signals.

Authors

Publication Details

Journal
International Journal of Interactive Mobile Technologies (iJIM)
Published
2026-10-27
DOI
https://doi.org/10.3991/ijim.v20i20.63187
Primary Topic
Topic Modeling
Type
article
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article

Mobile Edge AI Framework for Real-Time ESG Compliance Auditing through NLP and Blockchain Ledger Verification

Hendragunawan Sardjan Thayf, Mursalim Nohong, Baginda Hamzah, - Nur Alamzah et al.
2 links
International Journal of Interactive Mobile Technologies (iJIM)
Topic Modeling
article

Mobile Edge AI Framework for Real-Time ESG Compliance Auditing through NLP and Blockchain Ledger Verification

Hendragunawan Sardjan Thayf, Mursalim Nohong, Baginda Hamzah, - Nur Alamzah, Adel Abdulwadood Taher
article en

Abstract

The Mobile Edge artificial intelligence (AI) framework is introduced as an environmental, social, and governance (ESG) verification system that integrates natural language processing (NLP) and permissioned blockchain to facilitate near-real-time ESG compliance auditing. A lightweight transformer model is employed to identify ESG-related claims and extract relevant indicators, numerical values, units, locations, and reporting times. Extracted claims are structured and recorded on the blockchain to ensure verifiable, tamper-resistant records. A discrepancy assessment mechanism then classifies each claim as supported, partially supported, contradictory, or unsupported. The prototype was evaluated using a synthetic Kaggle dataset containing 11,000 annual company records from 1,000 organizations across nine regions and multiple sectors. The ESG classification model achieved a true positive rate of approximately 93.2%, with F1-scores of 0.945, 0.915, and 0.895 for environmental, social, and governance claims, respectively. Claim verification rates ranged from 93.1% to 98.4%. Edge deployment reduced verification latency to 124 ms compared to 231 ms in the cloud environment, representing a 46.3% reduction. These findings indicate that the framework can enable proactive ESG auditing, enhance claim traceability, accelerate verification, and deliver explainable compliance-risk signals.

International Journal of Interactive Mobile Technologies (iJIM)Vol. 20(20)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Topic Modeling
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