Blockchain and AI in University Procurement: A Smart E-Contract Model

With the rapid development of blockchain and artificial intelligence technologies, smart e-contract systems have great potential for application. This study proposes a new global contract processing architecture. It consists of an AI-driven decision layer for contract analysis, a blockchain execution layer for transaction processing, and a validation layer to maintain consistency. Experimental evaluations on a test platform processing 50,000 transactions show significant performance improvements of the architecture. Throughput was increased by 27% and latency was reduced by 35% compared to the core system. The architecture achieved 15,200 TPS under production workloads while maintaining 99.99% availability. Optimised deep learning pipelines (storage efficiency of 92%) and content error warning mechanisms (recovery time of 2.3 seconds) are important technical innovations. The system resource management module improved CPU utilisation by 24% and reduced memory overhead by 31%. These advances make contract processing more efficient, secure and scalable in large-scale environments.

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Publication Details

Published
2025-04-18
DOI
https://doi.org/10.1145/3744464.3744494
Primary Topic
Blockchain Technology Applications and Security
Type
article
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article

Blockchain and AI in University Procurement: A Smart E-Contract Model

Sai Yang, Fazhong Huang, Ying Hui Li, Tangqi Yao
3 links
Blockchain Technology Applications and Security
article

Blockchain and AI in University Procurement: A Smart E-Contract Model

Sai Yang, Fazhong Huang, Ying Hui Li, Tangqi Yao
article en

Abstract

With the rapid development of blockchain and artificial intelligence technologies, smart e-contract systems have great potential for application. This study proposes a new global contract processing architecture. It consists of an AI-driven decision layer for contract analysis, a blockchain execution layer for transaction processing, and a validation layer to maintain consistency. Experimental evaluations on a test platform processing 50,000 transactions show significant performance improvements of the architecture. Throughput was increased by 27% and latency was reduced by 35% compared to the core system. The architecture achieved 15,200 TPS under production workloads while maintaining 99.99% availability. Optimised deep learning pipelines (storage efficiency of 92%) and content error warning mechanisms (recovery time of 2.3 seconds) are important technical innovations. The system resource management module improved CPU utilisation by 24% and reduced memory overhead by 31%. These advances make contract processing more efficient, secure and scalable in large-scale environments.

University of International Business and Economics (CN), Beijing University of Civil Engineering and Architecture (CN)
Openalex Percentile: Top 76%
Blockchain Technology Applications and Security
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Blockchain and AI in University Procurement: A Smart E-Contract Model — Sai Yang, Fazhong Huang, et al. · (2025) | TGRS Research Map | TGRS