Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages

Перспективные технологии на основе искусственного интеллекта для оценки качества напитков и потребительских предпочтений
Frank R. Dunshea, Damir D. Torrico, Claudia Gonzalez Viejo, Sigfredo Fuentes
2019-11-01

Artificial intelligenceBiometricsComputer visionMachine learningRobotics
Beverages is a broad and important category within the food industry, which is comprised of a wide range of sub-categories and types of drinks with different levels of complexity for their manufacturing and quality assessment. Traditional methods to evaluate the quality traits of beverages consist of tedious, time-consuming, and costly techniques, which do not allow researchers to procure results in real-time. Therefore, there is a need to test and implement emerging technologies in order to automate and facilitate those analyses within this industry. This paper aimed to present the most recent publications and trends regarding the use of low-cost, reliable, and accurate, remote or non-contact techniques using robotics, machine learning, computer vision, biometrics and the application of artificial intelligence, as well as to identify the research gaps within the beverage industry. It was found that there is a wide opportunity in the development and use of robotics and biometrics for all types of beverages, but especially for hot and non-alcoholic drinks. Furthermore, there is a lack of knowledge and clarity within the industry, and research about the concepts of artificial intelligence and machine learning, as well as that concerning the correct design and interpretation of modeling related to the lack of inclusion of relevant data, additional to presenting over- or under-fitted models.
1
Beverage modeling studies often lack relevant data and may produce overfitted or underfitted models because of inadequate design and interpretation.
2
Recent research highlights low-cost, reliable, accurate, remote, and non-contact approaches using robotics, machine learning, computer vision, biometrics, and artificial intelligence.
3
Robotics and biometric technologies offer substantial development opportunities across beverage categories, particularly for hot and non-alcoholic drinks.
4
The beverage industry has insufficient conceptual clarity regarding artificial intelligence and machine learning applications.
5
Traditional beverage-quality assessment is tedious, costly, time-consuming, and generally unsuitable for real-time analysis.

Beverages and their quality-assessment and consumer-preference evaluation processes

Applications, trends, opportunities, and research gaps of artificial-intelligence-based emerging technologies for automated, real-time, low-cost, reliable, and accurate beverage quality and consumer-preference assessment

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2019-11-01
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Frank R. Dunshea
Damir D. Torrico
Claudia Gonzalez Viejo
Sigfredo Fuentes
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