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صفحه اصلی
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International Conference on Artificial Intelligence; City, Industry and Health
Applications of Artificial Intelligence in Food Quality and Safety Control
نویسندگان :
Nasrin Hesami
1
Hadiseh Dehghan
2
1- Islamic Azad University, Shahreza Branch
2- Islamic Azad University, Shahreza Branch
کلمات کلیدی :
Artificial Intelligent،Food،Quality Control
چکیده :
The global food industry faces increasing pressure to ensure the safety, quality, and traceability of its products amidst complex supply chains and rising consumer expectations. Traditional quality control methods, often reliant on manual inspection and laboratory testing, struggle to meet these demands efficiently and accurately. Artificial Intelligence (AI), encompassing machine learning (ML) and deep learning (DL), offers transformative potential by enabling automated, data-driven approaches to food quality assessment. This review synthesizes findings from recent literature (based on provided abstracts and snippets) to provide a comprehensive overview of AI applications in food quality and safety. Key applications discussed include pathogen and contaminant detection, automated defect sorting, objective sensory evaluation, shelf-life prediction, supply chain optimization, and HACCP monitoring. The enabling technologies, including computer vision, advanced sensors (biosensors, nanosensors), spectroscopy, hyperspectral imaging, IoT, and specific ML/DL algorithms (SVM, CNNs, etc.), are examined. Furthermore, critical challenges related to data, cost, regulation, security, and expertise are addressed. Finally, the review outlines future perspectives, highlighting trends towards hybrid models, increased automation, and enhanced traceability, concluding that AI is poised to play an increasingly central role in shaping the future of food quality and safety assurance.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.4.4