Robotics & Machine Learning Daily News2024,Issue(Feb.8) :64-64.DOI:10.1111/1541-4337.13296

Wageningen University and Research Reports Findings in Artificial Intelligence (Making food systems more resilient to food safety risks by including artificial intelligence, big data, and internet of things into food safety early warning and ...)

Robotics & Machine Learning Daily News2024,Issue(Feb.8) :64-64.DOI:10.1111/1541-4337.13296

Wageningen University and Research Reports Findings in Artificial Intelligence (Making food systems more resilient to food safety risks by including artificial intelligence, big data, and internet of things into food safety early warning and ...)

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Abstract

New research on Artificial Intelligence is the subject of a report. According to news originating from Wageningen, Netherlands, by NewsRx correspondents, research stated, “To enhance the resilience of food systems to food safety risks, it is vitally important for national authorities and international organizations to be able to identify emerging food safety risks and to provide early warning signals in a timely manner. This review provides an overview of existing and experimental applications of artificial intelligence (AI), big data, and internet of things as part of early warning and emerging risk identification tools and methods in the food safety domain.” Our news journalists obtained a quote from the research from Wageningen University and Research, “There is an ongoing rapid development of systems fed by numerous, real-time, and diverse data with the aim of early warning and identification of emerging food safety risks. The suitability of big data and AI to support such systems is illustrated by two cases in which climate change drives the emergence of risks, namely, harmful algal blooms affecting seafood and fungal growth and mycotoxin formation in crops. Automation and machine learning are crucial for the development of future real-time food safety risk early warning systems. Although these developments increase the feasibility and effectiveness of prospective early warning and emerging risk identification tools, their implementation may prove challenging, particularly for low- and middle-income countries due to low connectivity and data availability.”

Key words

Wageningen/Netherlands/Europe/Artificial Intelligence/Emerging Technologies/Food Poisoning/Food Safety/Foodborne Diseases and Conditions/Gastroenterology/Machine Learning/Risk and Prevention

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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参考文献量98
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