Food Quality Monitoring System Based on Smart Contracts and Evaluation Models

块链 计算机科学 智能合约 可执行文件 质量(理念) 生产(经济) 自动化 可靠性(半导体) 过程(计算) 计算机安全 数据质量 数据库 风险分析(工程) 嵌入式系统 可靠性工程 操作系统 运营管理 业务 工程类 机械工程 公制(单位) 哲学 功率(物理) 物理 认识论 量子力学 经济 宏观经济学
作者
Bin Yu,Ping Zhan,Ming Lei,Fang Zhou,Peng Wang
出处
期刊:IEEE Access [Institute of Electrical and Electronics Engineers]
卷期号:8: 12479-12490 被引量:57
标识
DOI:10.1109/access.2020.2966020
摘要

Currently, food quality has become a major concern for the food industry. To efficiently detect food quality problems during the production process, food enterprises must build quality monitoring systems. However, in a traditional quality monitoring system, data tampering and centralized storage have become barriers to reliability. In addition, due to lack of sufficient automation, traditional quality monitoring approaches are usually inefficient. Fortunately, blockchain is a promising technology that is tamper-proof and decentralized. Moreover, smart contracts, which are executable codes on the blockchain platform, are able to conduct transactions between mutually untrusted parties and are self-executing and self-verifying. By combining smart contracts and quality evaluation models, this paper presents an intelligent quality monitoring system for fruit juice production. This system has the characteristics of high automation and high reliability. In this system, response surface models are established based on preproduction data, and the optimal production condition for each stage is identified. During the actual production process, smart contracts are executed to record production data on a blockchain. These data serve as the inputs for evaluation models. Based on the evaluation outcome, smart contracts will decide whether the production process can be resumed or not. To evaluate the feasibility of the presented system, a prototype version of the quality monitoring system for flat peach juice production is implemented based on the Ethereum platform and executed in the Remix IDE.

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