ABRAΗAM, a Semiautomatic Trainable Connoisseur Lab, as a Big Data Collection Platform

Michael Agrafiotis, Athanasios Zisopoulos, Konstantinos Spinthiropoulos

Abstract


The main idea of the invention is an expert system to execute a specific recipe through a food container and a moving and tilting pot with gases and visible cooking analysis. Details used to achieve professional results are: food preprocessing and weighted, normal warehouse, fridge, and deep fridge, overall positioning, computer control, monitoring the cooking gases and light spectrum and trainability. The machinery line has been designed for the semi-professional market but it has capabilities for catering, military operation, gourmet cooking and serving. The modular design permits an entry system with a few food containers, two pots, an oven and the base software running on a single PC while the advanced option uses thousands of food boxes, tenths of pots, pans, ovens and high expert systems intelligence running on real time industrial computers. All these give unlimited futuristic capabilities covering the 10-year time for Return on Investment. The cooking on this machine is a statistical Big Data cooking with Data Science principles.


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DOI: https://doi.org/10.5296/jfs.v8i1.14302

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Copyright (c) 2018 Michael Agrafiotis, Athanasios Zisopoulos, Konstantinos Spinthiropoulos

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Journal of Food Studies (ISSN 2166-1073)

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