Modelling Techniques to Improve the Quality of Food Using Artificial Intelligence
| Autor: | Rijwan Khan, Varsha Sahni, Sandeep Srivastava |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Food security
Sanitation business.industry Computer science Nutrition. Foods and food supply media_common.quotation_subject 04 agricultural and veterinary sciences 02 engineering and technology Matter of fact Food chain Realm Premise 040103 agronomy & agriculture 0202 electrical engineering electronic engineering information engineering 0401 agriculture forestry and fisheries 020201 artificial intelligence & image processing Quality (business) TX341-641 Applications of artificial intelligence Artificial intelligence Safety Risk Reliability and Quality business Food Science media_common |
| Zdroj: | Journal of Food Quality, Vol 2021 (2021) |
| ISSN: | 1745-4557 0146-9428 |
| Popis: | Artificial intelligence (AI), or AI/machine vision, is assuming an overwhelming part in the realm of food handling and quality affirmation. As indicated by Mordor Intelligence, AI in the food and refreshments market is required to enlist a CAGR of 28.64%, during the conjecture time frame 2018–2023. Artificial intelligence makes it workable for PCs to gain as a matter of fact, investigate information from the two data sources and yields, and perform most human assignments with an improved level of accuracy and proficiency. Here is a concise gander at how AI is expanding sanitation and quality activities. This exploration has along these lines tried to furnish policymakers with a way to assess new and existing strategies, while likewise offering a reasonable premise through which food chains orders can be made stronger through the thought of the executive’s practices and strategy choices. This survey centers on the AI applications according to four mainstays of food security that is food accessibility, food availability, food use, and strength. |
| Databáze: | OpenAIRE |
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