陳姿蓉
Tzu-JungChen
碩士論文（2018）
智能化食品安全監控與管理系統設計
Design of Smart Food Safety Monitoring and Management System
關鍵字 Keywords
食品安全、食安監控與管理系統、食安追溯系統、智能系統、資料科學、資料探勘
Food safety、Food safety monitoring and management system、Food safety traceability system、Smart system、Data science、Data mining
摘要
近年來，食安事件層出不窮，不僅造成社會不安、對人民健康造成危害，甚至重創國家形象與經濟發展，故食品安全管理已成為各國之重要政策。隨著資料科學(Data Science)與人工智慧(Artificial Intelligence, AI)的興起，系統智能化的理想已逐漸能夠實現，本研究期盼透過智能化系統的支援，解決食安問題，為人類帶來更多福祉。
本研究以食品安全理念為體，以策略、組織、流程、方法與技術為用，以產品生命週期(Product Life Cycle, PLC)為範圍，依據系統工程「全面性」、PDCA「持續改善」與風險管理「預防」之概念，設計一個「全方位食安管理模式」。針對此「全方位食安管理模式」分析其系統之功能需求，參考資料科學之概念以及人工智慧與機器學習之原理，規劃與設計「智能化食安監控與管理系統」之功能架構。並依該功能架構界定資料分析之需求、設計「資料分析架構」，運用資料探勘(Data Mining)與人工智慧技術，分析影響因子與影響因子之影響模式、進行影響因子整體之趨勢、變因與問題，以建置「資料分析機制」。最後，藉由案例驗證「全方位食品安全管理模式」之可行性與「資料分析架構」之正確性。
Abstract
In recent years, an endless stream of food safety incidents has emerged, causing social unrest, harming human health, and severely damaging the national image and economic development. Therefore, food safety management has become a crucial policy area for all countries. With the rise of data science and artificial intelligence, the concept of system intelligence has gradually been realized, and we intended to solve the problems of food safety through an intelligent system to thereby promote human welfare.
This study design a smart food safety monitoring and management system, which includes (1) comprehensive food safety management model by system engineering, PDCA and risk management; (2) functional architecture of smart food safety monitoring and management system by comprehensive food safety management model, data science and the principles of artificial intelligence and machine learning; (3) data analysis framework by defined this functional architecture’s requirement of data analysis and using data mining and artificial intelligence technology to establish data analysis mechanism. Finally, give an evaluation and implementation for the result.