September 2025
Intermediate to advanced
496 pages
15h 3m
English
Content preview from Food Engineering Automation with Robotics and AI
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Chapter 9Online Spectroscopy Techniques to Access Food Quality and Safety, SCADA and HMI Examples
After reading this chapter, you should be able to:
There are ML techniques that improve monitoring and forecasting food safety. The main points in the paper that can be listed are as follows:
Importance of ML in Food Safety: Combining information types using ML improves food safety surveillance quality and cost. It incorporates prior experience and historical data to prioritize monitoring efforts along the food supply chain.
Of course, much research has been done on the application of ML in food-borne diseases and deep learning in food science; however, until this day, a specific overview of the topic has not been done specifically on ML for the monitoring and prediction of food safety. This paper aims to fill the gap by summarizing the relevant studies.
Types of Data and Algorithms: The data types that may occur in ML applications can be divided into structured and ...
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